Go Micro

Go Micro is a framework for distributed systems development.

Sponsors

Overview

Go Micro provides the core requirements for distributed systems development including RPC and Event driven communication. The Go Micro philosophy is sane defaults with a pluggable architecture. We provide defaults to get you started quickly but everything can be easily swapped out.

Features

Go Micro abstracts away the details of distributed systems. Here are the main features.

• Authentication - Auth is built in as a first class citizen. Authentication and authorization enable secure zero trust networking by providing every service an identity and certificates. This additionally includes rule based access control.

• Dynamic Config - Load and hot reload dynamic config from anywhere. The config interface provides a way to load application level config from any source such as env vars, file, etcd. You can merge the sources and even define fallbacks.

• Data Storage - A simple data store interface to read, write and delete records. It includes support for many storage backends in the plugins repo. State and persistence becomes a core requirement beyond prototyping and Micro looks to build that into the framework.

• Data Model - A typed data model layer with CRUD operations, queries, and multiple backends (memory, SQLite, Postgres). Define Go structs with tags and get type-safe Create/Read/Update/Delete/List/Count operations. Accessible via service.Model() alongside service.Client() and service.Server() for a complete service experience: call services, handle requests, save and query data.

• Service Discovery - Automatic service registration and name resolution. Service discovery is at the core of micro service development. When service A needs to speak to service B it needs the location of that service. The default discovery mechanism is multicast DNS (mdns), a zeroconf system.

• Load Balancing - Client side load balancing built on service discovery. Once we have the addresses of any number of instances of a service we now need a way to decide which node to route to. We use random hashed load balancing to provide even distribution across the services and retry a different node if there's a problem.

• Message Encoding - Dynamic message encoding based on content-type. The client and server will use codecs along with content-type to seamlessly encode and decode Go types for you. Any variety of messages could be encoded and sent from different clients. The client and server handle this by default. This includes protobuf and json by default.

• RPC Client/Server - RPC based request/response with support for bidirectional streaming. We provide an abstraction for synchronous communication. A request made to a service will be automatically resolved, load balanced, dialled and streamed.

• Async Messaging - PubSub is built in as a first class citizen for asynchronous communication and event driven architectures. Event notifications are a core pattern in micro service development. The default messaging system is a HTTP event message broker.

• MCP Integration - An MCP gateway you can integrate as a library, server or CLI command which automatically exposes services as tools for agents or other AI applications. Every service/endpoint get's converted into a callable tool.

• Multi-Service Binaries - Run multiple services in a single process with isolated state per service. Start as a modular monolith, split into separate deployments when you need independent scaling. Each service gets its own server, client, and store while sharing the registry and broker for inter-service communication.

• Pluggable Interfaces - Go Micro makes use of Go interfaces for each distributed system abstraction. Because of this these interfaces are pluggable and allows Go Micro to be runtime agnostic. You can plugin any underlying technology.

Getting Started

To make use of Go Micro

go get go-micro.dev/v5@v5.16.0

Create a service and register a handler

package main

import (
        "go-micro.dev/v5"
)

type Request struct {
        Name string `json:"name"`
}

type Response struct {
        Message string `json:"message"`
}

type Say struct{}

func (h *Say) Hello(ctx context.Context, req *Request, rsp *Response) error {
        rsp.Message = "Hello " + req.Name
        return nil
}

func main() {
        // create the service
        service := micro.New("helloworld")

        // register handler
        service.Handle(new(Say))

        // run the service
        service.Run()
}

Set a fixed address

service := micro.New("helloworld", micro.Address(":8080"))

Call it via curl

curl -XPOST \
     -H 'Content-Type: application/json' \
     -H 'Micro-Endpoint: Say.Hello' \
     -d '{"name": "alice"}' \
      http://localhost:8080

MCP & AI Agents

Go Micro is designed for an agent-first workflow. Every service you build automatically becomes a tool that AI agents can discover and use via the Model Context Protocol (MCP).

• 🤖 Agent Playground — Chat with your services through an interactive AI agent at /agent
• 🔧 MCP Tools Registry — Browse all services exposed as AI-callable tools at /mcp/tools
• 📖 MCP Documentation — Full guide to MCP integration, auth, and scopes

Services as Tools

Write a normal Go Micro service and it's instantly available as an MCP tool:

// SayHello greets a person by name.
// @example {"name": "Alice"}
func (g *GreeterService) SayHello(ctx context.Context, req *HelloRequest, rsp *HelloResponse) error {
    rsp.Message = "Hello " + req.Name
    return nil
}

Run with micro run and the agent playground and MCP tools registry are ready:

micro run
# Agent Playground:  http://localhost:8080/agent
# MCP Tools:         http://localhost:8080/mcp/tools

Use micro mcp serve for local AI tools like Claude Code, or connect any MCP-compatible agent to the HTTP endpoint.

micro chat

For an interactive terminal session that lets you talk to your services through an LLM:

ANTHROPIC_API_KEY=sk-ant-... micro chat --provider anthropic
> list all users
> create an order for product 42

micro chat discovers every service in the registry, exposes each endpoint as a tool, and lets the model orchestrate calls. The same building blocks (ai.Tools) work from your own services:

tools := ai.NewTools(service.Registry())
discovered, _ := tools.Discover()

m := ai.New("anthropic",
    ai.WithAPIKey(key),
    ai.WithTools(tools),
)
resp, _ := m.Generate(ctx, &ai.Request{
    Prompt: userInput,
    Tools:  discovered,
})

See the MCP guide for authentication, scopes, and advanced usage.

Multi-Service Binaries

Run multiple services in a single binary — start as a modular monolith, split into separate deployments later when you actually need to.

users := micro.New("users", micro.Address(":9001"))
orders := micro.New("orders", micro.Address(":9002"))

users.Handle(new(Users))
orders.Handle(new(Orders))

// Run all services together with shared lifecycle
g := micro.NewGroup(users, orders)
g.Run()

Each service gets its own server, client, store, and cache while sharing the registry, broker, and transport — so they can discover and call each other within the same process.

See the multi-service example for a working demo.

Data Model

Go Micro includes a typed data model layer for persistence. Define a struct, tag a key field, and get type-safe CRUD and query operations backed by memory, SQLite, or Postgres.

import (
        "go-micro.dev/v5/model"
        "go-micro.dev/v5/model/sqlite"
)

// Define your data type
type User struct {
        ID    string `json:"id" model:"key"`
        Name  string `json:"name"`
        Email string `json:"email" model:"index"`
        Age   int    `json:"age"`
}

Register your types and use the model:

service := micro.New("users")

// Register and use the service's model backend
db := service.Model()
db.Register(&User{})

// CRUD operations
db.Create(ctx, &User{ID: "1", Name: "Alice", Email: "alice@example.com", Age: 30})

user := &User{}
db.Read(ctx, "1", user)

user.Name = "Alice Smith"
db.Update(ctx, user)

db.Delete(ctx, "1", &User{})

Query with filters, ordering, and pagination:

var results []*User

// Find users by field
db.List(ctx, &results, model.Where("email", "alice@example.com"))

// Complex queries
db.List(ctx, &results,
        model.WhereOp("age", ">=", 18),
        model.OrderDesc("name"),
        model.Limit(10),
        model.Offset(20),
)

count, _ := users.Count(ctx, model.Where("age", 30))

Swap backends with an option:

// Development: in-memory (default)
service := micro.New("users")

// Production: SQLite or Postgres
db, _ := sqlite.New(model.WithDSN("file:app.db"))
service := micro.New("users", micro.Model(db))

Every service gets Client(), Server(), and Model() — call services, handle requests, and save data all from the same interface.

Examples

Check out /examples for runnable code:

• hello-world - Basic RPC service
• grpc-interop - Call go-micro from any gRPC client
• web-service - HTTP REST API
• multi-service - Multiple services in one binary
• mcp - MCP integration with AI agents

See all examples for more.

Protobuf

Install the code generator and see usage in the docs:

go install go-micro.dev/v5/cmd/protoc-gen-micro@v5.16.0

Note: Use a specific version instead of @latest to avoid module path conflicts. See releases for the latest version.

Docs: internal/website/docs/getting-started.md

Command Line

Install the CLI:

go install go-micro.dev/v5/cmd/micro@v5.16.0

Note: Use a specific version instead of @latest to avoid module path conflicts. See releases for the latest version.

Quick Start

micro new helloworld              # Create a new service
cd helloworld
micro run                          # Run with API gateway and hot reload

Then open http://localhost:8080 to see your service and call it from the browser.

Generate From a Prompt

Describe what you need in plain English. The AI designs services, writes handlers with real business logic, compiles them, and starts them:

micro run --prompt "a task management system with categories" --provider anthropic

Then talk to your services through an agent:

micro chat --provider anthropic
> Create a Work category, then add a task called 'Finish report' to it

The agent orchestrates across services automatically. When you need a capability that doesn't exist, the agent generates a new service mid-conversation. Read more.

Development Workflow

Stage	Command	Purpose
Create	micro new myservice	Scaffold a service (--template crud/pubsub/api)
Develop	micro run	Dev mode with hot reload and API gateway
Test	micro call	Call a service endpoint from the CLI
Chat	micro chat	Talk to your services through an LLM
Gateway	micro api	Standalone HTTP-to-RPC gateway
Build	micro build	Compile production binaries
Deploy	micro deploy	Push to a remote Linux server via SSH + systemd
Dashboard	micro server	Production web UI with auth

Inspecting the Framework

Every core interface has a matching command — inspect the registry, broker, store, and config from the terminal:

micro registry list                  # list services
micro broker subscribe events        # stream a topic
micro broker publish events 'hello'  # publish a message
micro store write greeting hello     # write a record
micro store read greeting            # read it back
micro config get database.host       # read config (from DATABASE_HOST)

These mirror the registry, broker, store, and config packages.

micro run

micro run starts your services with:

• Web Dashboard - Browse and call services at /
• Agent Playground - AI chat with MCP tools at /agent
• API Explorer - Browse endpoints and schemas at /api
• API Gateway - HTTP to RPC proxy at /api/{service}/{method} (no auth in dev mode)
• MCP Tools - Services as AI tools at /mcp/tools
• Health Checks - Aggregated health at /health
• Hot Reload - Auto-rebuild on file changes

Note: micro run and micro server use a unified gateway architecture. See Gateway Architecture for details.

micro run                    # Gateway on :8080
micro run --address :3000    # Custom gateway port
micro run --no-gateway       # Services only
micro run --env production   # Use production environment

Configuration

For multi-service projects, create a micro.mu file:

service users
    path ./users
    port 8081

service posts
    path ./posts
    port 8082
    depends users

env development
    DATABASE_URL sqlite://./dev.db

The gateway runs on :8080 by default, so services should use other ports.

Deployment

Deploy to any Linux server with systemd:

# On your server (one-time setup)
curl -fsSL https://go-micro.dev/install.sh | sh
sudo micro init --server

# From your laptop
micro deploy user@your-server

The deploy command:

1. Builds binaries for Linux
2. Copies via SSH to the server
3. Sets up systemd services
4. Verifies services are healthy

Optionally run micro server on the deployed machine for a production web dashboard with JWT auth, user management, and API explorer.

Manage deployed services:

micro status --remote user@server    # Check status
micro logs --remote user@server      # View logs
micro logs myservice --remote user@server -f  # Follow specific service

No Docker required. No Kubernetes. Just systemd.

See internal/website/docs/deployment.md for full deployment guide.

See cmd/micro/README.md for full CLI documentation.

Docs: internal/website/docs

Package reference: https://pkg.go.dev/go-micro.dev/v5

User Guides:

• Getting Started
• AI Integration — how services, MCP, tools, and LLMs fit together
• MCP & AI Agents
• Data Model
• Plugins Overview
• Deployment Guide
• Learn by Example

Architecture & Performance:

• Performance Considerations
• Reflection Usage & Philosophy

Security:

• TLS Security Migration
• Security Migration Guide

Supported AI Providers

Go Micro’s ai package gives every provider the same interface: Init, Generate, Stream, and functional options. Swap providers with a single import.

Provider	Import	Default Model
Anthropic	go-micro.dev/v5/ai/anthropic	claude-sonnet-4-20250514
Google Gemini	go-micro.dev/v5/ai/gemini	gemini-2.5-flash
Groq	go-micro.dev/v5/ai/groq	llama-3.3-70b-versatile
Mistral	go-micro.dev/v5/ai/mistral	mistral-large-latest
OpenAI	go-micro.dev/v5/ai/openai	gpt-4o
Together AI	go-micro.dev/v5/ai/together	Llama-3.3-70B-Instruct-Turbo
Atlas Cloud	go-micro.dev/v5/ai/atlascloud	llama-3.3-70b

Any provider that exposes an OpenAI-compatible API can also be used directly:

m := ai.New("openai",
    ai.WithAPIKey("your-key"),
    ai.WithBaseURL("https://api.yourprovider.com"),
)

Want to add your platform? See the AI Provider Integration Guide for how to implement ai.Model and submit a PR. We welcome both code contributions and sponsorships from AI infrastructure companies — reach out via a GitHub issue.

Adopters

• Sourse - Work in the field of earth observation, including embedded Kubernetes running onboard aircraft, and we’ve built a mission management SaaS platform using Go Micro.