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Asim Aslam c7657f73f4
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Refactor agent plan storage, update docs, and release v6 (#2977)
* 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>
2026-06-18 11:55:35 +01:00

199 行
6.1 KiB
Markdown

---
layout: default
title: AI Integration
---
# AI Integration
Go Micro is an AI-native microservices framework. Every service you build is automatically accessible to AI agents, and every service can call AI models. This page explains how the pieces fit together.
<img src="/images/generated/mcp-agent.jpg" alt="AI integration architecture" style="width: 100%; border-radius: 8px; margin: 1rem 0 1.5rem;" />
## The Stack
```
Your Services → write Go handlers, register with the framework
Registry → automatic service discovery (mDNS, Consul, etcd)
Gateways → micro api (HTTP→RPC) / micro mcp (MCP tools)
ai.Tools → discovers services + executes RPCs programmatically
ai.Model → calls LLMs (Anthropic, OpenAI, Gemini, Atlas Cloud, ...)
agent / flow / micro chat → agent-managed, event-driven, or interactive orchestration
```
Every layer is optional. You can use go-micro without AI. You can use the `ai` package without MCP. But when you stack them, you get services that AI agents can discover and orchestrate automatically.
## Layer by Layer
### 1. Services (your code)
Write normal Go handlers. Add doc comments for AI tool descriptions:
```go
// CreateUser creates a new user account.
// @example {"name": "Alice", "email": "alice@example.com"}
func (h *Users) CreateUser(ctx context.Context, req *pb.CreateRequest, rsp *pb.CreateResponse) error {
// your business logic
}
```
The doc comment becomes the tool description. The `@example` tag gives the LLM a usage hint. No AI-specific code in your handler.
### 2. Registry (service discovery)
Services register automatically. The registry is the source of truth for what's running:
```go
service := micro.NewService("users")
service.Handle(handler.New())
service.Run() // registers with the registry
```
Pluggable: mDNS (default, zero config), Consul, etcd, NATS.
### 3. MCP Gateway (services → tools)
The MCP gateway walks the registry and exposes every endpoint as a tool via the [Model Context Protocol](https://modelcontextprotocol.io/):
```go
// One line to expose all services as AI tools
service := micro.NewService("myservice", mcp.WithMCP(":3001"))
```
Or run it standalone:
```bash
micro mcp serve # stdio for Claude Code
micro mcp serve --address :3000 # HTTP for web agents
```
Any MCP-compatible agent (Claude Code, ChatGPT, custom agents) can discover and call your services.
### 4. ai.Tools (discover + execute)
`ai.Tools` turns registered services into LLM-callable tools — discovery plus RPC execution in one type:
```go
tools := ai.NewTools(service.Registry())
discovered, _ := tools.Discover() // []ai.Tool from all registered services
// Wire execution into a model with one option:
m := ai.New("anthropic", ai.WithAPIKey(key), ai.WithTools(tools))
```
This is what powers `micro chat` and the agent playground. You can use it directly in your own services to build agentic workflows.
### 5. ai.Model (LLM providers)
The `ai` package provides a pluggable interface for calling LLMs:
```go
import (
"go-micro.dev/v6/ai"
_ "go-micro.dev/v6/ai/anthropic"
)
m := ai.New("anthropic", ai.WithAPIKey(key))
resp, _ := m.Generate(ctx, &ai.Request{
Prompt: "What users are in the system?",
Tools: discovered, // from ai.Tools
})
```
Seven text providers, two image providers, one video provider. Same interface, swap with an import.
| Provider | Text | Image | Video |
|----------|------|-------|-------|
| Anthropic | yes | | |
| OpenAI | yes | yes | |
| Google Gemini | yes | | |
| Atlas Cloud | yes | yes | yes |
| Groq | yes | | |
| Mistral | yes | | |
| Together AI | yes | | |
### 6. micro chat (orchestration)
The CLI ties it all together — discovers services, builds the tool list, and lets you talk to your services:
```bash
ANTHROPIC_API_KEY=sk-ant-... micro chat --provider anthropic
> list all users
> send a welcome email to alice@example.com
> create an order for product-42
```
Multi-turn conversation with `ai.History` — the model remembers context across turns. Type `reset` to clear history.
### 7. micro flow (event-driven orchestration)
Subscribe to broker events and let an LLM orchestrate the response:
```go
import "go-micro.dev/v6/flow"
f := flow.New("onboard",
flow.Trigger("events.user.created"),
flow.Prompt("New user: {{.Data}}. Send welcome email and create workspace."),
flow.Provider("anthropic"),
flow.APIKey(key),
)
f.Register(service.Registry(), service.Options().Broker, service.Client())
```
Or from the CLI:
```bash
micro flow run --trigger events.user.created \
--prompt "New user: {{.Data}}. Send welcome email." \
--provider anthropic
micro flow exec --prompt "List all users" --provider anthropic
```
### 8. micro api (HTTP gateway)
A standalone HTTP-to-RPC gateway for exposing services over HTTP without the full dashboard:
```bash
micro api # listen on :8080
micro api --address :3000 # custom port
# Call services through the gateway
curl -XPOST -d '{"name":"Alice"}' http://localhost:8080/greeter/Greeter.Hello
```
## What You Don't Need
- **No agent framework** — the building blocks compose; you don't need a LangChain or CrewAI equivalent
- **No special handler code** — your services are normal Go handlers with doc comments
- **No API key to use MCP** — external agents bring their own models; your services just expose tools
- **No vendor lock-in** — every provider implements the same interface; swap with one import
## Getting Started
The fastest path:
```bash
# Create a service with MCP enabled
micro new myservice --template crud
cd myservice
# Run it
micro run
# Chat with it
ANTHROPIC_API_KEY=sk-ant-... micro chat --provider anthropic
> list all records
```
See also:
- [MCP Documentation](/docs/mcp.html) — detailed MCP gateway guide
- [Atlas Cloud Integration](/docs/guides/atlascloud-integration.html) — using Atlas Cloud as a provider
- [AI Provider Guide](/docs/guides/ai-provider-guide.html) — adding new providers
- [gRPC Interop Example](https://github.com/micro/go-micro/tree/master/examples/grpc-interop) — calling go-micro from standard gRPC clients