* 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>
7.0 KiB
layout
| layout |
|---|
| default |
micro run - Local Development
micro run provides a complete development environment for Go microservices.
Note
: This guide focuses on
micro runfeatures. For a comparison withmicro serverand gateway architecture details, see the CLI & Gateway Guide.
Quick Start
micro new helloworld
cd helloworld
micro run
Open http://localhost:8080 to see your service.
What You Get
When you run micro run, you get:
| URL | Description |
|---|---|
| http://localhost:8080 | Web dashboard - browse and call services |
| http://localhost:8080/agent | Agent playground - AI chat with MCP tools |
| http://localhost:8080/api | API explorer - browse endpoints and schemas |
| http://localhost:8080/api/{service}/{method} | API gateway - HTTP to RPC proxy |
| http://localhost:8080/mcp/tools | MCP tools - list all services as AI tools |
| http://localhost:8080/auth/tokens | Token management - create and manage API tokens |
| http://localhost:8080/auth/scopes | Scope management - restrict endpoint access |
| http://localhost:8080/auth/users | User management - create and manage users |
| http://localhost:8080/health | Health checks - aggregated service health |
| http://localhost:8080/services | Service list - JSON |
Plus:
- Authentication - JWT auth enabled with default credentials (
admin/micro) - Hot Reload - File changes trigger automatic rebuild
- Dependency Ordering - Services start in the right order
- Environment Management - Dev/staging/production configs
- MCP Gateway - Optional dedicated MCP protocol listener via
--mcp-address
Features
API Gateway
The gateway converts HTTP requests to RPC calls. All API calls require authentication:
# Log in at http://localhost:8080 with admin/micro to get a session
# Or use a token for programmatic access:
curl -X POST http://localhost:8080/api/helloworld/Say.Hello \
-H "Authorization: Bearer <token>" \
-d '{"name": "World"}'
# Response
{"message": "Hello World"}
Create tokens at /auth/tokens. The default admin token has * scope (full access).
Agent Playground
The agent playground at /agent lets you interact with your services using AI. Your services are automatically exposed as MCP (Model Context Protocol) tools — no configuration needed.
- Open http://localhost:8080/agent
- Configure your API key in Agent Settings (supports OpenAI and Anthropic)
- Chat with the AI agent — it can discover and call your services as tools
The MCP tools API is available at:
/mcp/tools— list all services as AI-callable tools/mcp/call— invoke a tool (service endpoint) by name
For a dedicated MCP protocol listener (for external AI clients), use:
micro run --mcp-address :3000
Hot Reload
By default, micro run watches for .go file changes and automatically rebuilds and restarts affected services.
micro run # Hot reload enabled (default)
micro run --no-watch # Disable hot reload
Changes are debounced (300ms) to handle rapid saves from editors.
Configuration File
For multi-service projects, create a micro.mu file to define services, dependencies, and environments.
micro.mu (Recommended)
# Service definitions
service users
path ./users
port 8081
service posts
path ./posts
port 8082
depends users
service web
path ./web
port 8089
depends users posts
# Environment configurations
env development
STORE_ADDRESS file://./data
DEBUG true
env production
STORE_ADDRESS postgres://localhost/db
DEBUG false
micro.json (Alternative)
{
"services": {
"users": {
"path": "./users",
"port": 8081
},
"posts": {
"path": "./posts",
"port": 8082,
"depends": ["users"]
}
},
"env": {
"development": {
"STORE_ADDRESS": "file://./data"
}
}
}
Service Properties
| Property | Required | Description |
|---|---|---|
path |
Yes | Directory containing the service (with main.go) |
port |
No | Port the service listens on (enables health check waiting) |
depends |
No | Services that must start first (space-separated in .mu, array in .json) |
Dependency Ordering
When depends is specified, services start in topological order:
- Services with no dependencies start first
- Each service waits for its dependencies to be ready
- If a service has a
port, we wait for/healthto return 200 - Circular dependencies are detected and reported as errors
Environment Management
micro run # Uses 'development' (default)
micro run --env production # Uses 'production'
micro run --env staging # Uses 'staging'
MICRO_ENV=test micro run # Environment variable override
Environment variables from the config are injected into each service's environment.
Graceful Shutdown
On SIGINT (Ctrl+C) or SIGTERM:
- Services stop in reverse dependency order
- SIGTERM is sent first (graceful)
- After 5 seconds, SIGKILL if still running
- PID files are cleaned up
Without Configuration
If no micro.mu or micro.json exists:
- All
main.gofiles are discovered recursively - Each is built and run
- No dependency ordering
- Hot reload still works
Logs
Service logs are written to:
- Terminal: Colorized with service name prefix
- File:
~/micro/logs/{service}-{hash}.log
View logs:
micro logs # List available logs
micro logs users # Show logs for 'users' service
Process Management
micro status # Show running services
micro stop users # Stop a specific service
Example: micro/blog
The micro/blog project demonstrates a multi-service setup:
# micro.mu
service users
path ./users
port 8081
service posts
path ./posts
port 8082
depends users
service comments
path ./comments
port 8083
depends users posts
service web
path ./web
port 8089
depends users posts comments
Run it:
micro run github.com/micro/blog
Options
micro run # Gateway on :8080, hot reload
micro run --address :3000 # Custom gateway port
micro run --no-gateway # Services only, no HTTP gateway
micro run --no-watch # Disable hot reload
micro run --env production # Use production environment
micro run --mcp-address :3000 # Enable MCP protocol gateway for AI clients
Tips
- Browse First: Open http://localhost:8080 to explore your services
- Try the Agent: Open http://localhost:8080/agent to chat with your services via AI
- Port Configuration: Set
portfor services to enable health check waiting - Health Endpoint: Implement
/healthreturning 200 for reliable startup sequencing - Environment Separation: Keep secrets in production env, use file:// paths for development
- Hot Reload Scope: Only
.gofiles trigger rebuilds; static assets don't