* examples: support desk agent + blog walkthrough
A real-world, runnable example (examples/support): customers/tickets/notify
services become the agent's tools, a flow turns a ticket.created event into
the agent's work, and an approval gate guards the one action that touches a
customer. Runs with no API key (mock model) or against a live provider.
Adds blog/28 'Building a Support Agent in Go' and indexes both.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CmdEY7pYmV5zzwCjNJ4ykL
* fix(new): protoless services by default; fix @latest install (#2985)
micro new now scaffolds a reflection-based service by default — plain Go
types registered via service.Handle, no .proto, no Makefile proto target.
The generated project builds and runs with 'go run .' and zero external
tooling. Protocol Buffers move behind --proto (the crud/pubsub/api
templates imply it). When the proto workflow is used and protoc /
protoc-gen-go / protoc-gen-micro are missing, print exact install
instructions instead of failing with a cryptic plugin error.
Also fixes the 'go install go-micro.dev/v6/cmd/micro@latest' version
constraint conflict: the vanity go-import meta still advertised /v5, so Go
fell back to the bare module and resolved an ancient v1.x tag. Advertise
/v6 (keeping /v5 for existing users) and add a version-pin fallback note to
the install docs.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CmdEY7pYmV5zzwCjNJ4ykL
* fix(new,install): pin generated go.mod to current go-micro; lead install with prebuilt binary (#2985)
- micro new now requires the exact go-micro version the CLI was built from
(via build info), falling back to 'latest' for dev builds. An explicit
require is also more robust than a bare import: 'go mod tidy' reliably
resolves it, where a requireless go.mod could fail vanity discovery.
- Make the precompiled binary (curl install.sh) the recommended install in
the docs; demote 'go install' to a from-source option with the version-pin
fallback note.
- Sync the stale internal/scripts/install.sh to the working website script
(it expected an old micro-OS-ARCH asset name; releases ship
micro_OS_ARCH.tar.gz).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CmdEY7pYmV5zzwCjNJ4ykL
* website: add corrected nginx vanity-import config (#2985)
The live go-micro.dev handler echoed the full request path into the
go-import prefix ($host$1), so go install go-micro.dev/v6/cmd/micro@latest
got prefix go-micro.dev/v6/cmd/micro — a package, not the module root — and
Go fell back to the ancient v1.x tags (version constraints conflict).
Add a dedicated /vN location that emits the module root (go-micro.dev/vN)
for any sub-path, and make the catch-all advertise the current module roots
instead of echoing arbitrary paths.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CmdEY7pYmV5zzwCjNJ4ykL
---------
Co-authored-by: Claude <noreply@anthropic.com>
A real-world, runnable example (examples/support): customers/tickets/notify
services become the agent's tools, a flow turns a ticket.created event into
the agent's work, and an approval gate guards the one action that touches a
customer. Runs with no API key (mock model) or against a live provider.
Adds blog/28 'Building a Support Agent in Go' and indexes both.
Claude-Session: https://claude.ai/code/session_01CmdEY7pYmV5zzwCjNJ4ykL
Co-authored-by: Claude <noreply@anthropic.com>
A real-world, runnable example (examples/support): customers/tickets/notify
services become the agent's tools, a flow turns a ticket.created event into
the agent's work, and an approval gate guards the one action that touches a
customer. Runs with no API key (mock model) or against a live provider.
Adds blog/28 'Building a Support Agent in Go' and indexes both.
Claude-Session: https://claude.ai/code/session_01CmdEY7pYmV5zzwCjNJ4ykL
Co-authored-by: Claude <noreply@anthropic.com>
Replace the drifted, contradictory roadmap set (two public roadmaps, the
AI-native-era business-model doc, stale status snapshots) with one
canonical roadmap focused on agentic development and developer experience.
- internal/website/docs/roadmap.md — the single source of truth: where we
are (v6), the principles (build into what people run; CLI-first; the
0->1 and 0->hero getting-started contract; interaction; battle-tested),
and prioritized work (cross-provider conformance + resilience now;
durable agent loop, streaming, observability next).
- ROADMAP.md — concise, points to the canonical.
- roadmap-2026 + the internal ROADMAP_2026/STATUS docs — collapsed to
pointers (keeps blog/CLAUDE links alive, removes drift).
- CLAUDE.md — references the single roadmap + CHANGELOG for status.
Co-authored-by: Claude <noreply@anthropic.com>
Updated the blog post to reflect the journey of Go Micro, including its revival and the integration of agents into the framework. Enhanced clarity and structure throughout the text.
Closes the remaining ask in #2980 without adding a parallel callback API.
ToolResult.Refused tags a guardrail block with a reason (ai.RefusedLoop /
RefusedMaxSteps / RefusedApproval) so a wrapper can switch on it instead of
parsing the message. ai.RunInfo (RunID, ParentID, Agent) rides on the
context passed to the tool handler, giving wrappers run correlation and
delegation lineage. Before/after/retry/failure were already covered by
AgentWrapTool; this adds the metadata. Docs + tests included.
Co-authored-by: Claude <noreply@anthropic.com>
A first-person journey of Go Micro from January 2015 through the
VC/company era, the platform pivot, the quiet years, and the revival via
the Claude Code grant — into v6 and the services/agents/flows model.
Co-authored-by: Claude <noreply@anthropic.com>
TestSingleEvent intermittently failed on cleanup with 'directory not
empty': the embedded NATS JetStream server was still releasing files when
t.TempDir's RemoveAll ran at test end. Own the store dir (os.MkdirTemp)
and remove it only after server.Shutdown()+WaitForShutdown(). Also report
setup errors with Errorf instead of Fatalf/require, which are unsafe from
the non-test goroutine (go vet).
Co-authored-by: Claude <noreply@anthropic.com>
* test(harness): read agent plan from the scoped store
The store-scoping change moved an agent's plan from the default table
key agent/{name}/plan to its own table (database "agent", table {name},
key "plan"). The plan-delegate harness tests still read the old key and
failed with 'not found'; read through store.Scope(mem, "agent", name)
like the agent does.
* docs: orient agents-first across README, landing, and docs overview
Lead with agents (then services and flows), surface MCP + A2A as the
interop story, and frame agents as services. Landing hero and feature
grid reordered agents-first with an A2A gateway card.
* v6: module path go-micro.dev/v6, TLS secure by default, NewService
Cut v6. Three breaking changes, bundled so the major bump is paid once:
- Module path go-micro.dev/v5 -> go-micro.dev/v6 across all imports + go.mod.
- TLS verification on by default (was off). MICRO_TLS_SECURE removed;
MICRO_TLS_INSECURE=true opts out for self-signed/dev.
- micro.NewService(name, opts...) is the canonical service constructor,
symmetric with NewAgent/NewFlow; micro.New kept as a deprecated alias;
the old name-less NewService(opts...) removed. Generators emit NewService.
Also ports the JWT auth token provider in-module (go-micro.dev/v6/auth/jwt/token
on golang-jwt/jwt/v5), dropping the v5-pinned github.com/micro/plugins/v5/auth/jwt
and the deprecated dgrijalva/jwt-go.
Docs/README/landing updated to v6 and @latest; v5->v6 migration guide added;
CHANGELOG cut as [6.0.0]. Blog posts left at their historical versions.
---------
Co-authored-by: Claude <noreply@anthropic.com>
The store-scoping change moved an agent's plan from the default table
key agent/{name}/plan to its own table (database "agent", table {name},
key "plan"). The plan-delegate harness tests still read the old key and
failed with 'not found'; read through store.Scope(mem, "agent", name)
like the agent does.
Co-authored-by: Claude <noreply@anthropic.com>
Refactor the A2A handler into a reusable dispatcher + Invoke seam and
expose NewAgentHandler(card, invoke) + Card(). An agent now serves its
own A2A endpoint with AgentA2A(addr) / WithA2A — handling tasks
in-process (no RPC hop, no separate gateway). The gateway and embedded
agent share the same handler; the only difference is RPC vs in-process
invocation. Docs, README, and changelog cover both deployment modes.
Co-authored-by: Claude <noreply@anthropic.com>
* feat(a2a): Agent2Agent protocol gateway
Add gateway/a2a — exposes registered agents over the open A2A protocol so
agents on other frameworks can discover and call them. Agent Cards are
generated from registry metadata (the same way the MCP gateway derives
tools from service endpoints); incoming A2A tasks translate to the
agent's existing Agent.Chat RPC, so there's no per-agent code.
v1 is the synchronous JSON-RPC binding: message/send returns a completed
Task, tasks/get retrieves it, and Agent Cards are served for discovery;
streaming and push notifications are advertised as unsupported. Run with
'micro a2a serve' (cmd/micro/a2a). Tests cover card generation,
message/send, tasks/get, listing, and unknown-method errors.
* docs: A2A guide, README contents + A2A section, universe A2A check
- Add a Contents table of contents at the top of the README and an A2A
subsection under Building Agents.
- Add the Agent2Agent (A2A) guide and register it in the docs nav.
- Exercise the A2A gateway in the universe harness: the concierge agent
is reached over A2A (message/send -> Agent.Chat -> completed task).
* feat(a2a): outbound client — call external A2A agents
Add a2a.Client (Send/Card) so a Go Micro agent or flow can call an agent
on any framework by URL — the outbound counterpart to the gateway. Wired
in two places: flow.A2A(url) as a workflow step (the cross-framework
Dispatch), and agent delegate to an http(s) URL routes over A2A. The
universe harness now drives the gateway through the client, exercising
both directions. Tests cover client send/card and the round trip.
* docs: A2A both-directions — guide, README, changelog, blog #26
---------
Co-authored-by: Claude <noreply@anthropic.com>
* docs: changelog catch-up + retrospective blog (agentic development)
Add the headline agentic features that shipped this quarter but were
never logged (agents, plan/delegate, guardrails, workflows, x402) to the
changelog, and add blog #25 — a three-month progress reflection on Go
Micro becoming a framework for agentic development.
* docs: tighten retrospective post — cut slogans, triads, and filler
* docs: tighten retrospective intro, bridge, and conclusion for a single through-line
* docs: frame Go Micro as how you build a distributed system, not run one
---------
Co-authored-by: Claude <noreply@anthropic.com>
* docs: design note for flow steps + Checkpoint durable execution
* docs: fold in durable-execution decisions (State struct, single Step, run retention, retry)
* docs: rename State.Payload to State.Data
* feat(flow): ordered steps + Checkpoint durable execution
A flow can now be an ordered list of steps (a task with stages) instead
of a single LLM turn. State carries typed Data plus a Stage marker; each
step is checkpointed before and after via a pluggable Checkpoint
(store-backed by default), so a run survives a crash and resumes where it
stopped without re-running completed steps. Flow-level Retry with a
per-step override; runs retained for audit unless DeleteOnSuccess.
Step actions: Call (RPC), LLM (augmented turn), Dispatch (to an agent),
or any StepFunc. Single-step and agent-dispatch flows are unchanged.
* feat(flow): top-level re-exports + durable flow example
Expose the step/checkpoint API from the micro package (FlowSteps,
FlowStep, FlowState, FlowRetry, FlowWithCheckpoint, FlowCall/LLM/Dispatch,
Checkpoint, StoreCheckpoint) and add a runnable, key-free example
demonstrating crash + resume.
* docs: document durable flow steps (guide, README, CLI help)
* docs: blog post + changelog for durable workflows
* fix(flow): scope checkpoint keys by flow name (flow/{name}/runs/{id})
Run keys were flow/runs/{id} — a single global keyspace shared by every
flow on the default store. Namespace them by flow name so each flow's
state is kept apart. StoreCheckpoint now takes a scope argument (the flow
passes its name by default).
* feat(store): Scope handle; scope agent and flow state by name
Add store.Scope(s, database, table) — a store handle that confines every
operation to a database/table without mutating the shared store, so
co-located components don't clobber each other's table (the failure mode
of the global Init(Table(...)) approach).
Use it to keep each agent's memory and plan in its own table
(agent/{name}) and each flow's runs in its own (flow/{name}), instead of
one global table partitioned only by key prefix. Services already scope
by service name.
* feat: consistent state model — service store scoping, flow registry, list/history CLI
- service: scope store via store.Scope (database service / table name),
retiring the Init(store.Table(name)) global-mutation hack; bridge the
default store so handlers using store.DefaultStore stay isolated.
- flow: register in the registry as type=flow while running (with trigger
and step count), deregister on Stop. Live discovery, like agents.
- cli: micro flow list (registry), micro flow runs <name> (durable store),
micro agent history <name> (durable store). list = running, runs/history
= durable, mirroring the service model.
* test: mini-universe end-to-end harness + scheduled GitHub Action
internal/harness/universe boots a small but real go-micro world — four
services, a durable checkout flow that crashes at payment and resumes,
and a guardrailed agent with a tool wrapper reached over RPC — drives the
scenario, asserts the end state (10 checks), and shuts down. Everything
is real except the LLM (mocked), so it's deterministic and needs no key;
-provider anthropic runs it live. Exits non-zero on failure, so it's an
end-to-end test, not just a demo.
Adds .github/workflows/universe.yml (push/PR/daily/dispatch) running the
universe + existing harnesses on the mock provider, plus an opt-in job
that runs live when ANTHROPIC_API_KEY is set. 'make harness' runs them
locally.
* ci: run the live universe job against AtlasCloud (ATLASCLOUD_API_KEY)
* ci: run the live universe job only on schedule or manual dispatch
The deterministic mock job still runs on push/PR/daily; the live
(AtlasCloud) job runs daily and on manual workflow_dispatch only, so
changes don't burn API credits on every PR but can still be checked
against a real model on demand.
---------
Co-authored-by: Claude <noreply@anthropic.com>
* feat(agent): tool-execution wrappers via WrapTool
Restructure ai.ToolHandler to the structured, ctx-carrying shape that
mirrors a go-micro RPC handler:
func(ctx context.Context, call ai.ToolCall) ai.ToolResult
This reuses the existing ToolCall (with its correlation ID) and
ToolResult types instead of the flat (name, input)->(any, string)
signature, and adds ToolCall.Scan for typed argument access.
Add ai.ToolWrapper and the agent option WrapTool / micro.AgentWrapTool —
the tool-side analogue of client.CallWrapper and server.HandlerWrapper.
Reframe the built-in guardrails (MaxSteps, LoopLimit, ApproveTool) as
composed wrappers around a base handler; developer wrappers compose
outermost, so they observe every call and result, including refusals.
Update all provider call sites, the MCP server and chat handlers, the
integration harnesses, and docs to the new signature.
* examples: add agent-wrap-tool showing AgentWrapTool
A runnable example of tool-execution middleware: an observe wrapper that
times calls and records per-tool metrics (correlated by call ID), and a
retry wrapper that recovers a flaky service call before the model sees
it. Demonstrates outermost-first composition and the wrapper/guardrail
interaction (retries are seen by loop detection).
* docs: note AgentWrapTool in README capabilities and CHANGELOG
* fix(generate): pin scaffolded go.mod to one version constant
The two generators pinned different, stale go-micro versions (v5.24.0
for services, v5.25.0 for agents). Centralize on a single
goMicroVersion constant (v5.29.0) so generated services and agents stay
in sync with the framework and there's one place to bump on release.
---------
Co-authored-by: Claude <noreply@anthropic.com>
* feat(agent): tool-execution wrappers via WrapTool
Restructure ai.ToolHandler to the structured, ctx-carrying shape that
mirrors a go-micro RPC handler:
func(ctx context.Context, call ai.ToolCall) ai.ToolResult
This reuses the existing ToolCall (with its correlation ID) and
ToolResult types instead of the flat (name, input)->(any, string)
signature, and adds ToolCall.Scan for typed argument access.
Add ai.ToolWrapper and the agent option WrapTool / micro.AgentWrapTool —
the tool-side analogue of client.CallWrapper and server.HandlerWrapper.
Reframe the built-in guardrails (MaxSteps, LoopLimit, ApproveTool) as
composed wrappers around a base handler; developer wrappers compose
outermost, so they observe every call and result, including refusals.
Update all provider call sites, the MCP server and chat handlers, the
integration harnesses, and docs to the new signature.
* examples: add agent-wrap-tool showing AgentWrapTool
A runnable example of tool-execution middleware: an observe wrapper that
times calls and records per-tool metrics (correlated by call ID), and a
retry wrapper that recovers a flaky service call before the model sees
it. Demonstrates outermost-first composition and the wrapper/guardrail
interaction (retries are seen by loop detection).
---------
Co-authored-by: Claude <noreply@anthropic.com>
Restructure ai.ToolHandler to the structured, ctx-carrying shape that
mirrors a go-micro RPC handler:
func(ctx context.Context, call ai.ToolCall) ai.ToolResult
This reuses the existing ToolCall (with its correlation ID) and
ToolResult types instead of the flat (name, input)->(any, string)
signature, and adds ToolCall.Scan for typed argument access.
Add ai.ToolWrapper and the agent option WrapTool / micro.AgentWrapTool —
the tool-side analogue of client.CallWrapper and server.HandlerWrapper.
Reframe the built-in guardrails (MaxSteps, LoopLimit, ApproveTool) as
composed wrappers around a base handler; developer wrappers compose
outermost, so they observe every call and result, including refusals.
Update all provider call sites, the MCP server and chat handlers, the
integration harnesses, and docs to the new signature.
Co-authored-by: Claude <noreply@anthropic.com>
Add LoopLimit: refuse a tool call repeated with identical arguments in
one Ask, with a self-heal message so the model changes approach. Catches
the no-progress loop that MaxSteps (count) and the gateway circuit
breaker (failures) miss. Enforced at the same tool-handler choke point as
MaxSteps/ApproveTool; on by default (lenient 3); AgentLoopLimit(0) to
disable. Tests cover repeats, distinct calls, disabled, and default-on.
Docs: new Agent Guardrails guide (MaxSteps/LoopLimit/ApproveTool, the
ApproveTool integration seam for external policy engines, and the
gateway's RateLimit/CircuitBreaker), nav + README + AGENT_DESIGN updates,
and blog/23 'Agent Guardrails'.
Co-authored-by: Claude <noreply@anthropic.com>
* feat(mcp): advertise x402 payment requirements in the tool catalog
/mcp/tools now includes each priced tool's payment requirements (amount,
network, asset, payTo) when payments are enabled, so an agent can see the
cost before calling and choose by price — a shoppable catalog, the
foundation for a tool marketplace. Free tools carry no payment block; the
shared Tool struct is copied when pricing so it isn't mutated. Tests cover
priced/free tools and payments-disabled. Documented in the payments guide.
* feat(x402): consumer client with a spend budget (pay-and-retry)
Add x402.Client, the consumer counterpart to Middleware: it settles 402
challenges automatically via a pluggable Payer, up to a spend Budget. A
call that would exceed the budget is refused before any payment is made,
and spend accumulates across calls — the spend cap that keeps an
autonomous, paying caller in bounds. Tests cover pay-within-budget,
refuse-over-budget, budget accumulation, and free endpoints, end to end
against the server Middleware with a mock facilitator and payer. Guide
documents the consumer side; agent-level AgentMaxSpend is the next step.
* chore: gofmt gateway/mcp/benchmark_test.go (trailing newline)
---------
Co-authored-by: Claude <noreply@anthropic.com>
Follow-up to the merged x402 integration (#2964). Drop the commerce-y
'price' vocabulary for the protocol's own 'amount', and add per-tool
pricing as an operator concern (the way scopes/rate-limits are set at the
gateway).
- x402.Config: Price -> Amount (default), plus Amounts map for per-tool
overrides; AmountFor(tool) resolves per-tool -> default. Add a Require
primitive (per-request enforcement) and LoadConfig for an operator
config file.
- MCP gateway: enforce payment per-tool inside /mcp/call (where scopes
are enforced) using AmountFor, instead of a flat path-based middleware.
- CLI: --x402-price -> --x402-amount; add --x402-config (per-tool file)
to micro mcp serve and micro-mcp-gateway.
- docs: new Payments (x402) guide + nav + README section; blog/22
updated to Amount/Amounts and the config-file model.
Co-authored-by: Claude <noreply@anthropic.com>
Integrate the x402 payment protocol (HTTP 402) so a tool can require a
stablecoin payment and an agent can settle it — the next step after
autonomous agents (blog 21): agents that act, and pay.
- wrapper/x402: HTTP middleware enforcing the 402 challenge/verify flow,
with a pluggable Facilitator interface. Go Micro carries no chain or
crypto code — verification/settlement is delegated to a facilitator
(Coinbase CDP, Alchemy, self-hosted), so Base and Solana are just
different facilitators behind one interface. HTTPFacilitator default;
tests cover challenge / accept / reject via a mock facilitator.
- MCP gateway: optional Options.Payment gates /mcp/call (listing tools
and health stay free); off unless configured.
- micro mcp serve and micro-mcp-gateway: opt-in --x402-pay-to/-price/
-network/-facilitator flags (env vars on the standalone binary).
- blog/22 'Integrating x402: Payments for Agents'; README feature row.
Pricing is flat per call for now; richer models and an agent-side spend
cap (next to MaxSteps/ApproveTool) are follow-ups.
Co-authored-by: Claude <noreply@anthropic.com>
The autonomy direction: agents that run on events, not human prompts.
- internal/harness/agent-flow: a runnable, deterministic demo — a
user.created broker event drives a Flow that hands off to a registered
agent (FlowAgent), which creates a workspace and sends a welcome over
real RPC. Only the LLM is mocked; passes under -race.
- blog/21: 'When the Event Is the Prompt' — the shift from agents you
talk to, to agents that act on their own; where microagents become
real; and the honest bar autonomy raises (guardrails, observability,
durable/resumable execution — the next things to build).
Co-authored-by: Claude <noreply@anthropic.com>
* docs: add 'become a sponsor' call-to-action linking to Discord
Now that there are a couple of sponsors, invite more: a short CTA under
the Sponsors section in the README and on the landing page, pointing to
the Discord to get in touch.
* fix(health): remove duplicate RegistryCheck declaration
Two PRs (#2957 and #2958) each added a RegistryCheck to the health
package, leaving the package uncompilable on master (RegistryCheck
redeclared: health/registry.go vs health/health.go). Keep the
health.go implementation — it honors the check's context timeout so a
hung registry (e.g. an unreachable etcd) reports down instead of
blocking the probe — and remove the duplicate registry.go and its test.
registry_check_test.go already covers healthy/down/nil/timeout/not-ready.
* feat(agent): pluggable memory and custom tools
Make agents compose the way services do — pluggable pieces with working
defaults — by adding the two abstractions an agent needs beyond the model:
- Memory: a pluggable interface for conversation memory. The default is
store-backed and durable across restarts (the previous hardcoded
behavior, now behind an interface); supply your own with WithMemory
(in-memory, database, semantic store). NewMemory / NewInMemory provided.
- Custom tools: WithTool registers any function as a tool the agent can
call, so agents are no longer limited to orchestrating RPC services.
Both exposed at the micro package (AgentMemory, AgentTool, NewMemory,
NewInMemory). Behavior-preserving refactor of the agent's history into
the default Memory; tests cover persistence, in-memory, clear, custom
tool dispatch and errors. README + AGENT_DESIGN document the pluggable
composition (model / memory / tools / guardrails).
* blog: 'Doubling Down on Agents' (#20)
The vision post for making agents a first-class framework the way
services were: opinionated, batteries-included, pluggable. Frames an
agent as a composition of model + memory + tools + guardrails with
working defaults; introduces the new pluggable memory and custom tools;
makes the microagents argument (an agent for everything, distributed
like microservices); and lays out the three primitives — services,
agents, workflows — as one substrate, with an honest list of the gaps
still to fill (knowledge/retrieval, streaming, explicit loop).
---------
Co-authored-by: Claude <noreply@anthropic.com>
Now that there are a couple of sponsors, invite more: a short CTA under
the Sponsors section in the README and on the landing page, pointing to
the Discord to get in touch.
Co-authored-by: Claude <noreply@anthropic.com>
* Initial plan
* feat(health): add RegistryCheck for registry connectivity health checks
Add a RegistryCheck function to the health package that creates a health
check verifying connectivity to the service registry. This enables
Kubernetes readiness probes to detect when a service loses its connection
to the registry (e.g. etcd).
Usage:
health.Register("registry", health.RegistryCheck(reg))
* fix(health): simplify error assertion in registry check test
---------
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
* perf: convert generated PNGs to optimized JPEGs (12MB -> 1.5MB)
The landing and docs loaded 18 AI-generated PNGs at 0.5-1MB each. They're
1200x800 RGB illustrations with no transparency, so they recompress ~8x
as progressive JPEG (quality 82) with no visible loss. Convert all,
update every reference (.png -> .jpg), and drop the originals (including
the unused hero.png). Generated images: 12.3MB -> 1.5MB.
* fix(registry/etcd): re-register when a lease silently expires (#2956)
The keepalive rework (long-lived KeepAlive instead of KeepAliveOnce)
moved lease renewal entirely onto the keepalive goroutine; the 30s
periodic Register now skips on the 'unchanged' check. The goroutine only
reacted to the keepalive channel closing, so a lease that expired
server-side without a prompt channel close (e.g. a partition that
outlasted the 90s TTL) left the node de-registered from etcd while the
cache still believed it was registered — and nothing re-registered it.
That is the hidden-failure mode reported in #2956.
React to a non-positive TTL keepalive response the same as a channel
close: drop the cached lease/hash so the next Register performs a full
re-registration. Extract the loop into keepAliveLoop and unit-test the
TTL-expired, channel-closed, and healthy paths (no etcd required).
---------
Co-authored-by: Claude <noreply@anthropic.com>
A go-micro service can keep running while it has silently lost its
connection to the registry (etcd, Consul, …) — the process looks healthy
but other services can no longer discover it, and Kubernetes sees the
pod as fine. health.RegistryCheck(reg) probes connectivity via
ListServices and, registered as a critical check, makes /health/ready
report not-ready so a readiness probe can pull the pod from rotation.
- Works with any registry implementation (no interface change).
- Honors the check timeout: an unreachable/hung registry is reported
down rather than blocking the probe.
- Tests cover healthy, down, timeout, nil, and the not-ready integration.
- Documented in the health guide with the Kubernetes readiness example.
Co-authored-by: Claude <noreply@anthropic.com>
* docs: group README features by section (AI / Framework / DX)
The features table repeated 'AI' down the Category column. Split into
three grouped tables — AI, Framework, Developer experience & deployment —
dropping the repetitive column. Adds a Guardrails row (MaxSteps,
ApproveTool).
* test: flow-to-agent end-to-end in the harness
Proves 'Flow triggers, Agent reasons': a workflow with FlowAgent hands an
event to the registered conductor agent over RPC, which plans, creates
tasks, and delegates to comms — the whole chain over real RPC with only
the LLM mocked. Deterministic (shared in-memory registry, no sleeps),
passes under -race.
* blog: 'The Evolution of Microservices' (#19)
A technical history of distributed-systems eras — the monolith's
coordination cost, the distributed-systems tax, containers and
declarative orchestration, the service mesh, and the modular-monolith
correction — establishing the durable unit (named, typed, discoverable,
independently deployable) that every runtime wave required. Then the
technical argument for agents: an LLM tool call needs exactly a service
interface, so the caller shifts from deterministic code to a reasoner
that composes typed capabilities from intent, with the honest caveats
(non-determinism, cost, guardrails). Not a product pitch.
* docs: bump install version to v5.27.0
---------
Co-authored-by: Claude <noreply@anthropic.com>
* docs: group README features by section (AI / Framework / DX)
The features table repeated 'AI' down the Category column. Split into
three grouped tables — AI, Framework, Developer experience & deployment —
dropping the repetitive column. Adds a Guardrails row (MaxSteps,
ApproveTool).
* test: flow-to-agent end-to-end in the harness
Proves 'Flow triggers, Agent reasons': a workflow with FlowAgent hands an
event to the registered conductor agent over RPC, which plans, creates
tasks, and delegates to comms — the whole chain over real RPC with only
the LLM mocked. Deterministic (shared in-memory registry, no sleeps),
passes under -race.
* blog: 'The Evolution of Microservices' (#19)
A technical history of distributed-systems eras — the monolith's
coordination cost, the distributed-systems tax, containers and
declarative orchestration, the service mesh, and the modular-monolith
correction — establishing the durable unit (named, typed, discoverable,
independently deployable) that every runtime wave required. Then the
technical argument for agents: an LLM tool call needs exactly a service
interface, so the caller shifts from deterministic code to a reasoner
that composes typed capabilities from intent, with the honest caveats
(non-determinism, cost, guardrails). Not a product pitch.
---------
Co-authored-by: Claude <noreply@anthropic.com>
* blog: 'Not Everything Should Be an Agent' (#18) on workflows
The workflow counterpart to the plan/delegate post: when the path is
known, use a deterministic Flow, not an autonomous agent. Frames flow vs
agent as two modes of the same building blocks, covers flow-triggers-
agent dispatch and the agent guardrails, and gives the simplest-first
guidance (single call -> workflow -> agent). Continues the arc from
blog 14/16/17; references Building Effective Agents in passing.
* docs: fix new-user onboarding friction
- README: lead Quick Start with a no-key 30-second path (micro new ->
micro run -> curl), then the AI --prompt path with an explicit
'export ANTHROPIC_API_KEY' so the headline command no longer fails
silently for users without a key.
- Unify all install versions to v5.26.0 (README + docs were split across
v5.16.0 / v5.25.0).
- Refresh the docs landing overview from the old 'microservices
framework' framing to 'services and agents', matching the README.
- getting-started: add Prerequisites (Go 1.21+, and that a provider key
is only needed for AI features).
- README features: Flows -> Workflows wording.
---------
Co-authored-by: Claude <noreply@anthropic.com>
* docs: map go-micro onto Anthropic's workflows-vs-agents taxonomy
- new guide 'Agents and Workflows': adopts Anthropic's Building Effective
Agents vocabulary — workflow (predefined path) = flow, agent (dynamic
self-direction) = agent — maps the augmented-LLM building block and the
five workflow patterns onto go-micro, and shows routing (chat router)
and orchestrator-workers (conductor + plan/delegate) are already native.
- flow package doc reframed as a workflow (predefined path) per the same
taxonomy, with guidance on flow vs agent.
- nav + README link the new guide.
* feat: agent guardrails — step limit and tool approval hook
Anthropic's Building Effective Agents stresses stopping conditions and
human-in-the-loop checkpoints for autonomous agents. Add both as plain
options enforced at the tool-handler choke point — no provider changes,
no new abstraction:
- MaxSteps(n): bound tool executions per Ask; beyond the limit, actions
are refused and the model is told to stop and summarize.
- ApproveTool(fn): gate each action before it runs; returning false
blocks it and surfaces the reason to the model. The internal plan tool
is never gated.
Exposed at the micro package (AgentMaxSteps, AgentApproveTool, ApproveFunc).
Tests cover the limit, blocking, and that plan is not gated. Guardrails
section of the agents-and-workflows guide updated from 'active work' to
documented options.
* feat: flow can dispatch to an agent (flow triggers, agent reasons)
Unify the engine without collapsing the workflow/agent distinction. A
Flow with Agent set hands each event's rendered prompt to a named
registered agent over RPC (Agent.Chat) instead of running its own LLM
step — so the workflow stays the deterministic trigger and the agent is
the reasoning engine, with its plan, delegate, memory, and guardrails.
A plain flow is unchanged (single augmented-LLM step).
- flow.Agent(name) / micro.FlowAgent(name); flow stores the client and
skips model setup when dispatching.
- test: dispatch routes to comms.Agent.Chat with the rendered prompt and
records the reply.
- guide: 'Flow triggers, Agent reasons' section.
---------
Co-authored-by: Claude <noreply@anthropic.com>
* rename coordinator agent to conductor in example and docs
* add plan & delegate integration harness
Runs the real go-micro stack end to end — services, registry, RPC, the
agent loop, store, and delegate-first routing — with only the LLM mocked
by a deterministic provider. Proves discovery, tool execution, plan
persistence, and agent-to-agent delegation over RPC work without an API
key; swap the provider to run the same flow against a live model.
* test: deterministic CI integration test + provider flag for harness
- main_test.go: TestPlanDelegateEndToEnd drives the full real stack
(services, RPC, agent loop, store, delegate-first routing) over a
shared in-memory registry — no mDNS, no sleeps. Asserts 3 tasks
created via RPC, plan persisted to the store, and delegation reaching
the comms agent (notify called once). Passes under -race, ~0.03s.
- main.go: add -provider flag (defaults to mock) and key detection so the
same harness runs against a live model with no code change.
* chore: gitignore built harness/example binaries
---------
Co-authored-by: Claude <noreply@anthropic.com>
* feat: add plan and delegate as built-in agent tools
Give agents two self-capabilities, expressed as plain tools wired into
the existing tool handler — no harness or graph, consistent with
"services are the only abstraction":
- plan: record/update an ordered plan, persisted to store-backed memory
and surfaced in the system prompt on later turns (externalized
planning).
- delegate: hand a self-contained subtask to another agent.
Delegate-first — if the target names a registered agent it is called
via RPC; otherwise a focused ephemeral sub-agent is created with
agent.New + Ask in a fresh, isolated context (loads/persists no
history, no built-in tools, so it cannot re-delegate).
Both are added automatically to any non-ephemeral agent, so existing
micro.NewAgent services and micro chat routing get them for free.
Tests are hermetic (memory store + memory registry).
* feat: add agent-plan-delegate example and document plan/delegate
- examples/agent-plan-delegate: coordinator that plans multi-step work,
creates tasks with its own tools, and delegates notification to a
separate registered comms agent over RPC.
- integration tests driving the full Ask loop through a fake provider:
plan tool exposure + persistence, ephemeral delegation with isolated
context, delegate-first RPC routing to a registered agent.
- docs: README (Building Agents + features + examples), AGENT_DESIGN
(Built-in Capabilities), agent-patterns guide (Pattern 9), CLAUDE.md.
* docs: blog post and guide for plan & delegate
- blog/17: "Plan & Delegate: Deep Agents in Go" — what the feature is,
how plan and delegate work, and a runnable getting-started path.
- guides/plan-delegate: reference guide with the smallest-agent snippet,
plan/delegate semantics, and the multi-agent example; linked in nav.
- example: auto-detect provider/key from common env vars (ANTHROPIC_API_KEY,
OPENAI_API_KEY, ...) so 'export KEY && go run main.go' just works.
- onboarding: getting-started paths now include go mod init / go get and a
clone-and-run path, so a reader can actually run it from a cold start.
* refactor: reframe plan/delegate blog and clean up sub-agent construction
- blog/17 retitled "Agents That Plan and Delegate" and reframed around
intent (plan = state intent, delegate = direct it), positioned as the
next beat after blog 15/16 and tied to the existing store + agent RPC
rather than re-announcing them. "Deep agents" now a single in-passing
nod, matching how blog 14 references LangChain.
- agent: add unexported newEphemeral constructor for sub-agents instead
of type-asserting the public Agent interface to set an internal field;
matches the options-only construction idiom used elsewhere.
* feat: expose plan & delegate in the micro chat fallback
Add agent.Builtins(opts...) — returns the built-in tools plus a handler,
so the plan/delegate capabilities can be wired into a tool loop that
isn't a running Agent. micro chat's direct-service fallback now reuses
it (single source of truth, no duplicated handler logic), so planning
and delegation are available there too, not just for registered agents.
Adds a test for the accessor; notes CLI availability in the guide.
---------
Co-authored-by: Claude <noreply@anthropic.com>
Run Tests / Etcd Integration Tests (push) Has been cancelled
goreleaser / goreleaser (push) Has been cancelled
* perf: compress hero image — 1.4MB to 80KB
Resized from 1536px to 1200px, converted to JPEG at quality 80.
80KB loads instantly vs 1.4MB stalling on slower connections.
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
* docs: micro run drops into interactive console
One command does everything — generate, start, and chat. No
separate micro chat step. The landing page shows micro run
dropping straight into the > prompt.
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
* feat: interactive console in micro run, -d for detached mode
micro run now drops into an interactive chat console after services
start. The console discovers services, exposes them as tools, and
lets you talk to them through an LLM — same as micro chat but
built into the run experience.
- Detects MICRO_AI_PROVIDER and MICRO_AI_API_KEY from environment
- Falls back to provider-specific env vars (ANTHROPIC_API_KEY, etc.)
- If no API key, prints hint and blocks on Ctrl-C (no console)
- -d / --detach flag skips the console (background mode)
- Ctrl-C always shuts everything down
Removed adopters section from README.
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
---------
Co-authored-by: Claude <noreply@anthropic.com>
* docs: reposition hero — framework for services and agents
Landing page: "Build Services and Agents in Go" — positions as a
framework, not a code generator. Tagline: "A framework for
microservices that AI agents can discover, use, and manage."
Hero command reverts to go get (the framework) instead of
micro run --prompt (a feature).
README matches: "framework for building services and agents in Go."
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
* perf: compress hero image — 1.4MB to 80KB
Resized from 1536px to 1200px, converted to JPEG at quality 80.
80KB loads instantly vs 1.4MB stalling on slower connections.
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
---------
Co-authored-by: Claude <noreply@anthropic.com>
* docs: remove code references from landing page feature grid
Landing page describes concepts, not APIs. Removed micro.NewAgent()
and micro.NewFlow() code references. Features described in plain
language — what they do, not how to code them.
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
* fix: update micro flow CLI to import from go-micro.dev/v5/flow
The flow package moved to top-level but the CLI still imported
from the old ai/flow path. Fixed to use go-micro.dev/v5/flow.
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
---------
Co-authored-by: Claude <noreply@anthropic.com>
* docs: remove code references from landing page feature grid
Landing page describes concepts, not APIs. Removed micro.NewAgent()
and micro.NewFlow() code references. Features described in plain
language — what they do, not how to code them.
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
* fix: update micro flow CLI to import from go-micro.dev/v5/flow
The flow package moved to top-level but the CLI still imported
from the old ai/flow path. Fixed to use go-micro.dev/v5/flow.
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
---------
Co-authored-by: Claude <noreply@anthropic.com>
* docs: update blog posts 15 and 16 to reflect RPC-based agents
Blog 15: replaced broker-based agent communication with RPC —
agents are services, they communicate via standard RPC, no pub/sub
hacks. Updated the framework mapping section.
Blog 16: added proto definition, micro call example, and explanation
that agents are real services with proto-defined endpoints. Updated
Ask() method name.
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
* docs: update agent design doc and blog posts for RPC-based agents
Rewrote AGENT_DESIGN.md — agents are services with proto-defined
Agent.Chat endpoints, communicate via RPC, no broker dependency.
Includes proto definition, CLI examples, generation output.
Blog 15: replaced broker references with RPC.
Blog 16: added proto definition and micro call example.
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
* docs: purge all stale broker-based agent references
Updated across all surfaces:
- README: agents described as services with RPC, Ask() not Chat(),
micro call example instead of micro agent chat
- Blog 15: replaced broker communication with RPC description
- Blog 16: replaced "coordinate through the broker" with RPC
- Getting started: agent is a service with proto endpoint, Ask()
not Chat(), added micro flow CLI commands (run/exec), expanded
CLI workflow table
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
---------
Co-authored-by: Claude <noreply@anthropic.com>
Blog 15: replaced broker-based agent communication with RPC —
agents are services, they communicate via standard RPC, no pub/sub
hacks. Updated the framework mapping section.
Blog 16: added proto definition, micro call example, and explanation
that agents are real services with proto-defined endpoints. Updated
Ask() method name.
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
Co-authored-by: Claude <noreply@anthropic.com>
* docs: Agent interface design sketch
Proposes Agent as a top-level abstraction alongside Service in the
micro package. Agent manages services — scoped tools, system prompt,
conversation memory, registry-discoverable.
Design only, no implementation.
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
* feat: Agent as a first-class abstraction
Introduce micro.NewAgent() alongside micro.New() — Agent is to
intelligence what Service is to capability.
Agent interface:
- Chat(ctx, message) (*Response, error) — core interaction method
- Run() — registers in registry, subscribes to broker, blocks
- Stop() — graceful shutdown
- Scoped tools — only sees endpoints of its assigned services
- Persistent memory — conversation history stored in store
- Agent-to-agent — communication via broker topics
Top-level API:
agent := micro.NewAgent("task-mgr",
micro.AgentServices("task"),
micro.AgentPrompt("You manage tasks."),
micro.AgentProvider("anthropic"),
)
agent.Run()
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
* feat: wire agents into chat router, add micro agent CLI, expose Flow
Three top-level abstractions:
micro.New("task") — Service (capability)
micro.NewAgent("task-mgr") — Agent (intelligence)
micro.NewFlow("onboard-user") — Flow (event-driven orchestration)
micro chat as router:
- Discovers agents from registry on startup
- Single agent: routes directly
- Multiple agents: LLM classifies intent, dispatches to right agent
via route_to_agent tool
- No agents: falls back to current direct-service behaviour
- Banner shows discovered agents
micro agent CLI:
- micro agent list — shows registered agents and their services
- micro agent describe <name> — shows agent details from registry
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
* feat: move flow to top level, update docs for three abstractions
Package structure now consistent:
service/ — Service (capability)
agent/ — Agent (intelligence)
flow/ — Flow (event-driven orchestration)
ai/flow/ kept as backward-compatible re-export.
Updated across all surfaces:
- CLAUDE.md: added agent/ and flow/ to project structure
- README: added "Building Agents" section with NewAgent() examples,
updated features table (Agents, Flows, Chat router), CLI table
(agent list, agent describe), docs links
- Website: features grid shows Services, Agents, Flows as the three
pillars alongside generation, MCP, and pluggable architecture
- micro.go: Flow imported from top-level flow/ package
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
* docs: rewrite getting-started, fix ai-integration import paths
Getting started now covers all three abstractions:
- Service (write handlers, micro run, templates)
- Agent (micro.NewAgent, scoped tools, memory, CLI)
- Flow (event-driven LLM orchestration)
Leads with prompt-based generation, then manual service creation.
ai-integration.md: fixed flow import path from go-micro.dev/v5/ai/flow
to go-micro.dev/v5/flow, updated stack diagram to show agent/flow/chat.
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
* blog: Introducing micro.NewAgent()
Post 16 — announces Agent as a first-class abstraction. Shows the
API (NewAgent, AgentServices, AgentPrompt, AgentProvider), scoped
tools, persistent memory, multi-service agents, multi-agent systems,
and the three-abstraction comparison table (Service/Agent/Flow).
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
* feat: fix agent registration, blog post 16
Agent registration:
- Add node with address so mDNS can discover agents
- Store type and services in node metadata (mDNS requirement)
- Connect broker before subscribing, non-fatal if broker unavailable
- Print registration confirmation on Run()
Agent/chat discovery:
- Check both service-level and node-level metadata for type=agent
(mDNS stores metadata on nodes, not services)
Blog post 16: "Introducing micro.NewAgent()" — announces the Agent
abstraction with code examples, comparison table, multi-agent patterns.
Tested end-to-end: micro run → micro agent list discovers the agent →
micro chat routes to it → agent calls service endpoints.
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
* feat: agents are proper services with RPC Chat endpoint
Refactored agent to use server.Server instead of fake registry entries.
An agent now:
- Creates a real RPC server with server.Name(agentName)
- Registers an Agent.Chat handler callable via standard RPC
- Sets server metadata type=agent, services=x,y for discovery
- No more fake addresses or broker hacks
micro chat calls agents via RPC (client.Call) instead of creating
local agent instances. The registry stays clean — agents are real
services with real endpoints.
Removed broker dependency from agent options. Agent-to-agent
communication is just RPC like everything else.
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
* feat: agent uses proto-defined RPC interface
Added agent/proto/agent.proto with Agent service definition:
rpc Chat(ChatRequest) returns (ChatResponse)
Agent now implements the generated AgentHandler interface and
registers via pb.RegisterAgentHandler. The Chat endpoint is a
standard proto-based RPC callable by any go-micro client.
Renamed the programmatic API from Chat() to Ask() to avoid
collision with the proto handler method name.
micro chat calls agents via standard RPC with JSON-encoded
request/response — no special types needed on the caller side.
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
* feat: generate agent alongside services, update all docs
micro run --prompt now generates an agent binary that manages all
the generated services. The agent reads MICRO_AI_PROVIDER and
MICRO_AI_API_KEY from the environment. micro run propagates these
when started with --prompt.
Run banner shows services and agents separately.
Updated README, getting-started guide, and landing page to show
the complete flow: generate → services + agent start → micro chat
routes to agent → agent orchestrates services.
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
---------
Co-authored-by: Claude <noreply@anthropic.com>
* docs: update landing hero — describe it, run it, talk to it
Lead with the AI-first experience instead of "write services in Go."
The entry point is now describing what you need, not writing code.
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
* blog: Agents for Services — a new model for microservices
Post 15 — explores the concept of distributed agents managing
services. Each service has an agent assigned to it (not embedded
in it). Agents are the intelligence layer; services are the
capability layer. Multi-service agents span domain boundaries.
Agent-to-agent communication through the broker.
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
---------
Co-authored-by: Claude <noreply@anthropic.com>
* chore: update Discord invite link everywhere
Replace discord.gg/jwTYuUVAGh and discord.gg/go-micro with
discord.gg/WeMU5AGxD across all docs, blog posts, issue templates,
security policy, and contrib READMEs.
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
* docs: update landing hero — describe it, run it, talk to it
Lead with the AI-first experience instead of "write services in Go."
The entry point is now describing what you need, not writing code.
https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd
---------
Co-authored-by: Claude <noreply@anthropic.com>
Asim Aslam