* feat(website): redesign docs and blog layouts, add blog header images
Redesign both layouts to match the new landing page:
- Consistent nav bar with logo, Docs, Blog, GitHub, Reference, Home
- Consistent footer with copyright and links
- CSS custom properties for theming
- Updated typography, spacing, and code block styling
- Active sidebar link highlighting in docs
- Dark mode support preserved
Generate 4 blog header images via Atlas Cloud:
- blog-deploy.png for post 1 (micro deploy)
- blog-mcp.png for posts 2, 3, 7 (MCP-related)
- blog-agents-demo.png for post 4 (agents demo)
- blog-dx.png for post 5 (DX cleanup)
- Reuse data-model.png for post 6 (model package)
All 7 existing blog posts now have header images.
* fix(website): prevent horizontal scroll on mobile landing page
Add overflow-x: hidden on html and body. Set max-width: 100% and
height: auto on all section and two-col images. Add overflow:
hidden to .two-col grid. Constrain hero pre with max-width and
overflow-x. Reduce font sizes and padding at mobile breakpoint.
* feat(website): add images to remaining core doc pages
Generate 5 more images via Atlas Cloud for docs:
- registry.png: service discovery diagram
- broker.png: pub/sub message broker pattern
- transport.png: multi-transport layers (HTTP, gRPC, NATS)
- config.png: dynamic configuration from multiple sources
- observability.png: monitoring dashboard with metrics/traces
Add images to registry.md, broker.md, transport.md, config.md,
observability.md, and architecture.md. All 11 main doc pages
now have header images.
* feat: add sponsor logos to landing page, README images, and flows blog post
Add Anthropic and Atlas Cloud sponsor logos to the landing page
with links to their respective blog posts. Logos display at 0.7
opacity with hover effect.
Add architecture and MCP agent images to the GitHub README for
the Overview and MCP sections.
Write blog post 9: "From Chat to Flows" — explores the concept
of LLM-powered service orchestration. Compares micro chat's
interactive model with persistent event-driven flows, shows how
the existing building blocks (ai/tools, History, broker) could
compose into a flow engine, discusses tradeoffs vs traditional
orchestration (Step Functions, Temporal), and includes a working
15-line code example. Explicitly positions it as a concept for
community feedback, not an announcement.
* feat(website): add animated hero video to landing page
Generate a 6-second hero video via Atlas Cloud's image-to-video
API (gemini-omni-flash). Shows the microservices network diagram
animating with data flowing between nodes.
Replace the static hero image with an autoplay muted looping
video element. Falls back to the static image via poster
attribute and img fallback for browsers without video support.
* feat(ai): add VideoModel interface with Atlas Cloud provider
Add ai.VideoModel interface for video generation alongside Model
and ImageModel. Supports text-to-video and image-to-video via
VideoRequest with prompt, reference images, duration, aspect
ratio, and resolution fields.
Implement GenerateVideo for Atlas Cloud using their async API:
POST /api/v1/model/generateVideo → poll /api/v1/model/prediction.
Default model is gemini-omni-flash image-to-video. Polls every
5 seconds until completion or context cancellation.
Register Atlas Cloud as a video provider via ai.RegisterVideo.
Add 3 tests: registration, no-key error, compile-time interface
check. Update ai/README.md with VideoModel docs.
The ai package now covers all three modalities:
- Model (text) — 7 providers
- ImageModel (image) — 2 providers (Atlas Cloud, OpenAI)
- VideoModel (video) — 1 provider (Atlas Cloud)
---------
Co-authored-by: Claude <noreply@anthropic.com>
Use height="26" on both logos for consistent alignment. Switch
Anthropic to the Wikimedia wordmark SVG (no padding) instead of
the logo.wine version which had excessive whitespace.
Co-authored-by: Claude <noreply@anthropic.com>
Add blog/8 announcing Atlas Cloud as an official Go Micro sponsor.
Covers the sponsorship, Atlas Cloud's platform (300+ models, OpenAI
compatibility, enterprise compliance), and how the integration
works with the ai package, ai/tools, micro chat, and micro run.
Add guides/atlascloud-integration.md with full setup instructions:
quick start, configuration options, environment variables, model
selection, tool calling with services, and provider swapping.
Add Atlas Cloud and AI Provider guides to the docs sidebar
navigation. Add sponsorship link to README header.
Co-authored-by: Claude <noreply@anthropic.com>
* docs: add AI provider integration guide and Supported AI Providers section
Add a step-by-step guide for AI infrastructure companies to implement
ai.Model and contribute a provider to go-micro. Covers the full
lifecycle: skeleton, tool call handling, tests, registration, and PR
checklist.
Add a "Supported AI Providers" section to the project README that lists
current providers (Anthropic, OpenAI) in a table and links to the
integration guide with a call-to-action for new providers and sponsors.
Streamline the "Adding a New Provider" section in ai/README.md to point
to the new guide instead of duplicating a full code listing.
* fix: remove nonexistent Discord link from README
* fix(website): set content container width to 800px on desktop
Move the 800px max-width from .markdown-body up to .content so
the entire content pane (not just the inner body) is sized
correctly. The container now fills up to 800px beside the sidebar.
* feat(ai): wire Atlas Cloud into server and auto-detection
Import atlascloud provider in the micro server so it is available
when running micro run / micro server. Add atlascloud to
AutoDetectProvider so --ai_base_url with an atlascloud domain
selects the right provider automatically.
* feat(ai): add Google Gemini provider
Add ai/gemini implementing ai.Model for Google's Gemini API. Uses
the native generateContent endpoint with system_instruction,
contents/parts, and functionDeclarations — not an OpenAI shim.
Default model gemini-2.5-flash, auth via x-goog-api-key header.
Wire into micro server imports and AutoDetectProvider (matches
googleapis.com and google in base URL).
Update README.md and ai/README.md with provider listing.
* feat(ai): add Groq, Mistral, and Together AI providers
Add three new OpenAI-compatible providers:
- ai/groq: ultra-fast inference, default model llama-3.3-70b-versatile
- ai/mistral: Mistral AI, default model mistral-large-latest
- ai/together: Together AI, default model Llama-3.3-70B-Instruct-Turbo
All three are wired into the micro server imports and
AutoDetectProvider. README and ai/README updated with the full
provider table.
* feat(ai): add ai/tools helper and 'micro chat' interactive agent
Extract the registry-discovery + RPC-execution loop from the web
agent playground into a reusable ai/tools package:
- tools.New(reg) creates a Set bound to a registry
- Set.Discover() walks the registry and returns []ai.Tool with
LLM-safe (underscored) names, remembering the mapping back to
the original dotted form
- Set.Handler(client) returns an ai.ToolHandler that resolves
the safe name and issues the RPC
Add cmd/micro/chat — an interactive 'micro chat' REPL that uses
ai/tools to let users talk to their services through any
registered AI provider. Supports --prompt for single-shot use,
auto-detects the provider from --base_url, and falls back to the
provider's conventional env var (ANTHROPIC_API_KEY, etc).
Update README with the new command and the programmatic example.
* feat(examples): add gRPC interop example
Add examples/grpc-interop showing that any standard gRPC client can
call a go-micro service — no go-micro SDK required on the client
side. Includes:
- proto/greeter.proto with generated Go, gRPC, and micro stubs
- server/ using go-micro gRPC transport
- client/ using stock google.golang.org/grpc (no go-micro imports)
- README with Python example and explanation of how routing works
Addresses the confusion from issue #2818 where users didn't know
that go-micro gRPC services are callable by any gRPC client.
* fix: strip /api prefix from MCP routes
Change /api/mcp/tools and /api/mcp/call to /mcp/tools and
/mcp/call. MCP is a first-class feature, not a sub-path of the
API proxy. Update server routes, playground template, scopes
template, run.go output, README, CLI README, and all docs.
---------
Co-authored-by: Claude <noreply@anthropic.com>
* docs: add AI provider integration guide and Supported AI Providers section
Add a step-by-step guide for AI infrastructure companies to implement
ai.Model and contribute a provider to go-micro. Covers the full
lifecycle: skeleton, tool call handling, tests, registration, and PR
checklist.
Add a "Supported AI Providers" section to the project README that lists
current providers (Anthropic, OpenAI) in a table and links to the
integration guide with a call-to-action for new providers and sponsors.
Streamline the "Adding a New Provider" section in ai/README.md to point
to the new guide instead of duplicating a full code listing.
* fix: remove nonexistent Discord link from README
* fix(website): set content container width to 800px on desktop
Move the 800px max-width from .markdown-body up to .content so
the entire content pane (not just the inner body) is sized
correctly. The container now fills up to 800px beside the sidebar.
* feat(ai): wire Atlas Cloud into server and auto-detection
Import atlascloud provider in the micro server so it is available
when running micro run / micro server. Add atlascloud to
AutoDetectProvider so --ai_base_url with an atlascloud domain
selects the right provider automatically.
* feat(ai): add Google Gemini provider
Add ai/gemini implementing ai.Model for Google's Gemini API. Uses
the native generateContent endpoint with system_instruction,
contents/parts, and functionDeclarations — not an OpenAI shim.
Default model gemini-2.5-flash, auth via x-goog-api-key header.
Wire into micro server imports and AutoDetectProvider (matches
googleapis.com and google in base URL).
Update README.md and ai/README.md with provider listing.
* feat(ai): add Groq, Mistral, and Together AI providers
Add three new OpenAI-compatible providers:
- ai/groq: ultra-fast inference, default model llama-3.3-70b-versatile
- ai/mistral: Mistral AI, default model mistral-large-latest
- ai/together: Together AI, default model Llama-3.3-70B-Instruct-Turbo
All three are wired into the micro server imports and
AutoDetectProvider. README and ai/README updated with the full
provider table.
* feat(ai): add ai/tools helper and 'micro chat' interactive agent
Extract the registry-discovery + RPC-execution loop from the web
agent playground into a reusable ai/tools package:
- tools.New(reg) creates a Set bound to a registry
- Set.Discover() walks the registry and returns []ai.Tool with
LLM-safe (underscored) names, remembering the mapping back to
the original dotted form
- Set.Handler(client) returns an ai.ToolHandler that resolves
the safe name and issues the RPC
Add cmd/micro/chat — an interactive 'micro chat' REPL that uses
ai/tools to let users talk to their services through any
registered AI provider. Supports --prompt for single-shot use,
auto-detects the provider from --base_url, and falls back to the
provider's conventional env var (ANTHROPIC_API_KEY, etc).
Update README with the new command and the programmatic example.
* feat(examples): add gRPC interop example
Add examples/grpc-interop showing that any standard gRPC client can
call a go-micro service — no go-micro SDK required on the client
side. Includes:
- proto/greeter.proto with generated Go, gRPC, and micro stubs
- server/ using go-micro gRPC transport
- client/ using stock google.golang.org/grpc (no go-micro imports)
- README with Python example and explanation of how routing works
Addresses the confusion from issue #2818 where users didn't know
that go-micro gRPC services are callable by any gRPC client.
---------
Co-authored-by: Claude <noreply@anthropic.com>
* docs: add AI provider integration guide and Supported AI Providers section
Add a step-by-step guide for AI infrastructure companies to implement
ai.Model and contribute a provider to go-micro. Covers the full
lifecycle: skeleton, tool call handling, tests, registration, and PR
checklist.
Add a "Supported AI Providers" section to the project README that lists
current providers (Anthropic, OpenAI) in a table and links to the
integration guide with a call-to-action for new providers and sponsors.
Streamline the "Adding a New Provider" section in ai/README.md to point
to the new guide instead of duplicating a full code listing.
* feat(ai): add Atlas Cloud provider
Add ai/atlascloud implementing ai.Model for Atlas Cloud's
OpenAI-compatible chat completions API. Registers as "atlascloud"
with default model llama-3.3-70b and base URL
https://api.atlascloud.ai. Supports tool calling via ToolHandler.
Includes 7 unit tests covering registration, defaults, init,
generate-without-key, and stream-not-implemented.
Update the Supported AI Providers table in README.md and the
Supported Providers section in ai/README.md.
* fix: remove nonexistent Discord link from README
---------
Co-authored-by: Claude <noreply@anthropic.com>
* feat: add prometheus monitoring wrapper
Reintroduces the Prometheus metrics wrapper previously available in the
plugins repository, updated for go-micro v5. Exposes request count and
latency histograms for handlers, subscribers, and outgoing client calls
via NewHandlerWrapper, NewSubscriberWrapper, NewCallWrapper and
NewClientWrapper, labelled with service/endpoint/status.
Options cover namespace, subsystem, const labels, histogram buckets and
a custom registerer; duplicate collectors (e.g. from multiple wrappers
sharing the same config) are reused transparently via a cached
metrics bundle.
Fixes#2893
* fix(registry/etcd): clear lease/register caches on KeepAlive channel closure
When the etcd client's long-lived KeepAlive channel closes (e.g. because
the lease expired on the server side during a network partition), the
previous cleanup only removed the channel bookkeeping. The stale entries
in `leases` and `register` caused the next registerNode() heartbeat to
hit the "unchanged hash" short-circuit and skip re-registration entirely,
so the service permanently disappeared from etcd.
Extract the cleanup into handleKeepAliveClosed and also drop the cached
lease id and hash so the next heartbeat performs a full Grant+Put and
the service recovers within one RegisterInterval.
Regression introduced by #2822; fix is symmetric with the existing
synchronous KeepAliveOnce recovery path that propagates
rpctypes.ErrLeaseNotFound.
* docs: add AI provider integration guide and Supported AI Providers section
Add a step-by-step guide for AI infrastructure companies to implement
ai.Model and contribute a provider to go-micro. Covers the full
lifecycle: skeleton, tool call handling, tests, registration, and PR
checklist.
Add a "Supported AI Providers" section to the project README that lists
current providers (Anthropic, OpenAI) in a table and links to the
integration guide with a call-to-action for new providers and sponsors.
Streamline the "Adding a New Provider" section in ai/README.md to point
to the new guide instead of duplicating a full code listing.
* Update contribution guidelines in README.md
Removed Discord contact information for platform contributions.
---------
Co-authored-by: Claude <noreply@anthropic.com>
* feat: add agent platform showcase and blog post
Add a complete platform example (Users, Posts, Comments, Mail) that
mirrors micro/blog, demonstrating how existing microservices become
AI-accessible through MCP with zero code changes.
Includes blog post "Your Microservices Are Already an AI Platform"
walking through real agent workflows: signup, content creation,
commenting, tagging, and cross-service messaging.
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* refactor: rename handler types to drop redundant Service suffix
UserService → Users, PostService → Posts, CommentService → Comments,
MailService → Mail. Matches micro/blog naming convention.
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* refactor: consolidate top-level directories, reduce framework bloat
Move internal/non-public packages behind internal/ or into their
parent packages where they belong:
- deploy/ → gateway/mcp/deploy/ (Helm charts belong with the gateway)
- profile/ → service/profile/ (preset plugin profiles are a service concern)
- scripts/ → internal/scripts/ (install script is not public API)
- test/ → internal/test/ (test harness is not public API)
- util/ → internal/util/ (internal helpers shouldn't be imported externally)
Also fixes CLAUDE.md merge conflict markers and updates project
structure documentation.
All import paths updated. Build and tests pass.
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* refactor: redesign model package to match framework conventions
Rename model.Database interface to model.Model (consistent with
client.Client, server.Server, store.Store). Remove generics in
favor of interface{}-based API with reflection.
Key changes:
- model.Model interface: Register once, CRUD infers table from type
- DefaultModel + NewModel() + package-level convenience functions
- Schema registered via Register(&User{}), no per-call schema passing
- Memory implementation as default (in model package, like store)
- memory/sqlite/postgres backends updated for new interface
- protoc-gen-micro generates RegisterXModel() instead of generic factory
- All docs, blog, and README updated
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
---------
Co-authored-by: Claude <noreply@anthropic.com>
* docs: update all four documentation guides and mark Q2 complete
- ai-native-services: add WithMCP one-liner, standalone gateway,
WebSocket client example, and OpenTelemetry observability section
- mcp-security: add OTel distributed tracing, WebSocket authentication
(connection-level and per-message), DeniedReason audit field
- tool-descriptions: add manual overrides with WithEndpointDocs and
export formats section
- agent-patterns: add LangChain/LlamaIndex SDK pattern and standalone
gateway production pattern with Docker example
- Update roadmap: mark Q2 documentation as complete, Q2 at 100%
- Update status: reflect all recent completions, shift priorities
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* feat: add agent demo example and blog post
Add examples/agent-demo with a multi-service project management app
(projects, tasks, team) that demonstrates AI agents interacting with
Go Micro services through MCP. Includes seed data and example prompts.
Add blog post 4 "Agents Meet Microservices: A Hands-On Demo" walking
through the example code and showing cross-service agent workflows.
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* feat: enable multiple services in a single binary
Remove global state mutations from service and cmd option functions so
that configuring one service no longer overwrites another's settings.
Key changes:
- service/options.go: remove all DefaultXxx global writes from option
functions; newOptions() now creates fresh Server, Client, Store, and
Cache per service while sharing Registry, Broker, and Transport
- cmd/cmd.go: newCmd() uses local copies instead of pointers to package
globals; Before() no longer mutates DefaultXxx vars
- cmd/options.go: remove global mutations from all option functions
- service/service.go: export ServiceImpl type for cross-package use
- service/group.go: new Group type for multi-service lifecycle
- micro.go: add Start/Stop to Service interface, expose Group and
NewGroup convenience function
- examples/multi-service: working example with two services
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* docs: highlight multi-service binary support
Add multi-service section to README with code example, update features
list, add to examples index, and note in status summary.
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* feat: unify service API and clean up developer experience
- Unified service creation: micro.New("name", opts...) as canonical API
- Clean handler registration: service.Handle(handler, opts...) accepts
server.HandlerOption args directly, no need to reach through Server()
- Unexported serviceImpl: users interact through Service interface only
- Service groups use Service interface (not concrete type)
- Fixed Stop() to properly propagate BeforeStop/AfterStop errors
- Fixed store init: error-level log instead of fatal on init failure
- Updated all examples to use consistent patterns
- Updated README, getting-started, MCP docs, and guides
- Added blog post about the DX cleanup
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* fix: add blog post 5 to blog index
Blog post 5 (Developer Experience Cleanup) existed as a file but was
missing from the blog index page.
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* feat: make micro new generate MCP-enabled services by default
- main.go template includes mcp.WithMCP(":3001") by default
- Handler template has agent-friendly doc comments with @example tags
- Proto template has descriptive field comments
- README includes MCP usage, Claude Code config, and tool description tips
- Makefile adds mcp-tools, mcp-test, mcp-serve targets
- go.mod updated to Go 1.22
- Added --no-mcp flag to opt out of MCP integration
- Post-create output shows MCP endpoint URLs
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* docs: add MCP migration guide and troubleshooting guide
- Migration guide: 3 approaches to add MCP to existing services
(WithMCP one-liner, standalone gateway, CLI)
- Troubleshooting guide: common issues with agents, WebSocket,
Claude Code, auth, rate limiting, and performance
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* refactor: rename model/ package to ai/ for AI model providers
The model/ package name conflicted with the conventional use of "model"
for data models. Renamed to ai/ which better describes the package's
purpose (AI provider abstraction for Anthropic, OpenAI, etc.) and frees
up model/ for future data model layer use.
- Rename model/ → ai/ with package name change
- Update all Go imports from go-micro.dev/v5/model to go-micro.dev/v5/ai
- Update cmd/micro/server/server.go references (model.X → ai.X)
- Update all documentation and roadmap references
- All tests pass, CLI builds successfully
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* feat: add model package for typed data access with CRUD and queries
New model/ package provides a typed data model layer using Go generics.
Supports structured CRUD operations, WHERE filters, ordering, pagination,
and automatic schema creation from struct tags.
Three backends:
- memory: in-memory for development and testing
- sqlite: embedded SQL for dev and single-node production
- postgres: full PostgreSQL for production deployments
Key features:
- Generic Model[T] with Create/Read/Update/Delete/List/Count
- Query builder: Where(), WhereOp(), OrderAsc/Desc(), Limit(), Offset()
- Struct tags: model:"key" for primary key, model:"index" for indexes
- Auto table creation from struct schema
- 19 tests passing across memory and sqlite backends
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* feat: add model code generation to protoc-gen-micro
Extend the micro plugin to generate model structs from proto messages
annotated with // @model. Generated alongside client/server code in
the same .pb.micro.go file.
For a proto message like:
// @model
message User { string id = 1; string name = 2; }
Generates:
- UserModel struct with model:"key" and json tags
- NewUserModel(db) factory returning *model.Model[UserModel]
- UserModelFromProto(*User) *UserModel converter
- (*UserModel).ToProto() *User converter
Supports @model(table=custom_table, key=custom_field) options.
Adds GetComments() to generator for plugin comment inspection.
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* feat: add Model() to Service interface for Client/Server/Model trifecta
Every service now exposes Client(), Server(), and Model() — call services,
handle requests, and save/query data from the same interface. Includes
README docs, blog post, and a full model guide on the docs site.
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
---------
Co-authored-by: Claude <noreply@anthropic.com>
* docs: update all four documentation guides and mark Q2 complete
- ai-native-services: add WithMCP one-liner, standalone gateway,
WebSocket client example, and OpenTelemetry observability section
- mcp-security: add OTel distributed tracing, WebSocket authentication
(connection-level and per-message), DeniedReason audit field
- tool-descriptions: add manual overrides with WithEndpointDocs and
export formats section
- agent-patterns: add LangChain/LlamaIndex SDK pattern and standalone
gateway production pattern with Docker example
- Update roadmap: mark Q2 documentation as complete, Q2 at 100%
- Update status: reflect all recent completions, shift priorities
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* feat: add agent demo example and blog post
Add examples/agent-demo with a multi-service project management app
(projects, tasks, team) that demonstrates AI agents interacting with
Go Micro services through MCP. Includes seed data and example prompts.
Add blog post 4 "Agents Meet Microservices: A Hands-On Demo" walking
through the example code and showing cross-service agent workflows.
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* feat: enable multiple services in a single binary
Remove global state mutations from service and cmd option functions so
that configuring one service no longer overwrites another's settings.
Key changes:
- service/options.go: remove all DefaultXxx global writes from option
functions; newOptions() now creates fresh Server, Client, Store, and
Cache per service while sharing Registry, Broker, and Transport
- cmd/cmd.go: newCmd() uses local copies instead of pointers to package
globals; Before() no longer mutates DefaultXxx vars
- cmd/options.go: remove global mutations from all option functions
- service/service.go: export ServiceImpl type for cross-package use
- service/group.go: new Group type for multi-service lifecycle
- micro.go: add Start/Stop to Service interface, expose Group and
NewGroup convenience function
- examples/multi-service: working example with two services
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* docs: highlight multi-service binary support
Add multi-service section to README with code example, update features
list, add to examples index, and note in status summary.
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* feat: unify service API and clean up developer experience
- Unified service creation: micro.New("name", opts...) as canonical API
- Clean handler registration: service.Handle(handler, opts...) accepts
server.HandlerOption args directly, no need to reach through Server()
- Unexported serviceImpl: users interact through Service interface only
- Service groups use Service interface (not concrete type)
- Fixed Stop() to properly propagate BeforeStop/AfterStop errors
- Fixed store init: error-level log instead of fatal on init failure
- Updated all examples to use consistent patterns
- Updated README, getting-started, MCP docs, and guides
- Added blog post about the DX cleanup
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
---------
Co-authored-by: Claude <noreply@anthropic.com>
* docs: update all four documentation guides and mark Q2 complete
- ai-native-services: add WithMCP one-liner, standalone gateway,
WebSocket client example, and OpenTelemetry observability section
- mcp-security: add OTel distributed tracing, WebSocket authentication
(connection-level and per-message), DeniedReason audit field
- tool-descriptions: add manual overrides with WithEndpointDocs and
export formats section
- agent-patterns: add LangChain/LlamaIndex SDK pattern and standalone
gateway production pattern with Docker example
- Update roadmap: mark Q2 documentation as complete, Q2 at 100%
- Update status: reflect all recent completions, shift priorities
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* feat: add agent demo example and blog post
Add examples/agent-demo with a multi-service project management app
(projects, tasks, team) that demonstrates AI agents interacting with
Go Micro services through MCP. Includes seed data and example prompts.
Add blog post 4 "Agents Meet Microservices: A Hands-On Demo" walking
through the example code and showing cross-service agent workflows.
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* feat: enable multiple services in a single binary
Remove global state mutations from service and cmd option functions so
that configuring one service no longer overwrites another's settings.
Key changes:
- service/options.go: remove all DefaultXxx global writes from option
functions; newOptions() now creates fresh Server, Client, Store, and
Cache per service while sharing Registry, Broker, and Transport
- cmd/cmd.go: newCmd() uses local copies instead of pointers to package
globals; Before() no longer mutates DefaultXxx vars
- cmd/options.go: remove global mutations from all option functions
- service/service.go: export ServiceImpl type for cross-package use
- service/group.go: new Group type for multi-service lifecycle
- micro.go: add Start/Stop to Service interface, expose Group and
NewGroup convenience function
- examples/multi-service: working example with two services
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* docs: highlight multi-service binary support
Add multi-service section to README with code example, update features
list, add to examples index, and note in status summary.
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
---------
Co-authored-by: Claude <noreply@anthropic.com>
Major Features:
- Unified gateway architecture (micro run + micro server use same code)
- MCP (Model Context Protocol) integration as library package
- AI-accessible microservices with 3 lines of code
Gateway Unification:
- Created reusable gateway module (cmd/micro/server/gateway.go)
- Updated micro run to use unified gateway (removed duplicate code)
- Conditional authentication (disabled in dev, required in prod)
- Reduced code duplication, simplified maintenance
MCP Integration:
- New library package: gateway/mcp
- Automatic service discovery → MCP tools
- HTTP/SSE transport support (stdio coming soon)
- Works for both library users and CLI users
- CLI flags: --mcp-address for micro run and micro server
Documentation:
- ADR-010: Unified Gateway Architecture
- CLI & Gateway Guide for users
- MCP Gateway README and examples
- Blog post: Making Your Microservices AI-Native with MCP
Breaking Changes: None (fully backward compatible)
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
* Add systemd-based deployment support
- micro init --server: Initialize server to receive deployments
- Creates /opt/micro/{bin,data,config} directories
- Generates systemd template unit (micro@.service)
- Creates 'micro' system user
- micro deploy: Deploy services via SSH + systemd
- Builds linux/amd64 binaries automatically
- Copies via rsync/scp to server
- Manages services via systemctl
- Helpful error messages for common issues
- micro status --remote: Check remote service status
- micro logs --remote: Stream remote logs via journalctl
- micro stop --remote: Stop services on remote server
- Config: Added 'deploy' blocks to micro.mu for named targets
The deployment model:
- systemd is the process supervisor (battle-tested)
- SSH is the transport (standard, secure)
- No custom daemons or platforms needed
Co-authored-by: Shelley <shelley@exe.dev>
* Add deployment documentation
- docs/deployment.md: Comprehensive guide for server deployment
- README.md: Updated deployment section with full workflow
Co-authored-by: Shelley <shelley@exe.dev>
* Add deployment section to CLI documentation
Co-authored-by: Shelley <shelley@exe.dev>
* Fix systemd template escaping and rsync permission warnings
- Fix %i escaping in systemd template (was being interpreted by fmt.Sprintf)
- Handle rsync exit code 23/24 gracefully (metadata permission warnings)
- Add --omit-dir-times to rsync to avoid directory timestamp errors
Co-authored-by: Shelley <shelley@exe.dev>
* Add install script for micro CLI
Co-authored-by: Shelley <shelley@exe.dev>
* Fix non-constant format string in deploy error
Co-authored-by: Shelley <shelley@exe.dev>
---------
Co-authored-by: Shelley <shelley@exe.dev>
micro build:
- Default: builds Go binaries to ./bin/
- Cross-compile with --os and --arch
- Docker is optional via --docker flag
micro deploy:
- Requires --ssh user@host
- Copies pre-built binaries (if ./bin/ exists)
- Or syncs source and builds on remote
- No Docker dependency
Go binaries are self-contained. No runtime needed.
Co-authored-by: Shelley <shelley@exe.dev>
Provides a test harness for running micro services in isolation:
h := testing.NewHarness(t)
defer h.Stop()
h.Name("users").Register(new(UsersHandler))
h.Start()
var rsp Response
h.Call("UsersHandler.Create", &req, &rsp)
Features:
- Isolated registry, transport, and broker per harness
- Simple API: Name(), Register(), Start(), Stop()
- Call helpers: Call(), CallContext()
- Assertions: AssertServiceRunning(), AssertCallSucceeds(), AssertCallFails()
- Access to underlying Client(), Server(), Registry()
Note: Due to go-micro's global defaults, each harness tests one service.
For multi-service testing, use integration tests or mocks.
Also fixes README.md example showing conflicting port 8080.
Co-authored-by: Shelley <shelley@exe.dev>
micro run now starts an HTTP gateway alongside your services:
- Web dashboard at http://localhost:8080
- API proxy at /api/{service}/{method}
- Health checks at /health
- Service listing at /services
The experience is now:
$ micro new helloworld
$ cd helloworld
$ micro run
Open http://localhost:8080 to see and call your services.
New flags:
--address :3000 # Custom gateway port
--no-gateway # Disable gateway (services only)
Updated documentation to make this the central experience.
Co-authored-by: Shelley <shelley@exe.dev>
Asim Aslam