Go Micro

Go Micro is a framework for building services and agents in Go.

Write services — they register, discover each other, and communicate via RPC and events. Every endpoint is automatically an AI-callable tool via MCP. Build agents to manage them intelligently. Both are Go code, both use the same primitives, both deploy the same way.

Sponsors

  

Quick Start

Install the CLI:

# Binary (no Go required)
curl -fsSL https://go-micro.dev/install.sh | sh

# Or with Go
go install go-micro.dev/v5/cmd/micro@v5.27.0

Fastest start — no API key

Scaffold a service, run it, call it:

micro new helloworld
cd helloworld
micro run

Then in another terminal:

curl -X POST http://localhost:8080/api/helloworld/Helloworld.Call \
  -H 'Content-Type: application/json' -d '{"name":"World"}'

Generate from a prompt — with an LLM key

Set a provider key, describe what you want, and the AI designs services, writes handlers, compiles, and starts them:

export ANTHROPIC_API_KEY=sk-ant-...   # or OPENAI_API_KEY, GEMINI_API_KEY, ...
micro run --prompt "a task management system with categories" --provider anthropic

The AI designs the architecture, you review it, then it generates handlers with real business logic, compiles them, and starts them:

Services:
  ● task — Task management with status tracking
  ● project — Project organization

Generate? [Y/n]

Micro
  Services:
    ● task
    ● project
  Agents:
    ◆ agent

Then talk to your services from the console:

> Create a project called Launch, then add three tasks to it

→ project_Project_Create({"name":"Launch"})
← {"record":{"id":"p1..."},"success":true}
→ task_Task_Create({"title":"Design specs","project_id":"p1..."})
→ task_Task_Create({"title":"Write code","project_id":"p1..."})
→ task_Task_Create({"title":"Ship it","project_id":"p1..."})

Created Work category and added 'Finish report' task to it.

When you need a capability that doesn't exist, the agent generates a new service mid-conversation:

> I need to track shipping. Create a shipment for order 123 to London.

  ⚡ generating shipping service...
  ✓ shipping
  → shipping_Shipping_Create({"order_id":"123","destination":"London"})
  ← {"record":{"id":"xyz...","status":"pending"}}

  Created shipment for order 123 going to London.

Edit the generated code by hand at any time — re-running preserves your changes. Read more.

Writing Services

Under the hood, a service is a struct with methods. Doc comments and @example tags become tool descriptions for AI agents automatically.

package main

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

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

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

type Say struct{}

// Hello greets a person by name.
// @example {"name": "Alice"}
func (h *Say) Hello(ctx context.Context, req *Request, rsp *Response) error {
    rsp.Message = "Hello " + req.Name
    return nil
}

func main() {
    service := micro.New("greeter")
    service.Handle(new(Say))
    service.Run()
}

Run it and everything is accessible — REST, gRPC, MCP, agent playground:

micro run
# Dashboard:   http://localhost:8080
# API:         http://localhost:8080/api/{service}/{method}
# Agent:       http://localhost:8080/agent
# MCP Tools:   http://localhost:8080/mcp/tools

You can also scaffold a service from a template:

micro new helloworld
micro new contacts --template crud

Building Agents

An Agent is a service with an LLM inside it. It has a proto-defined Agent.Chat RPC endpoint, registers in the registry, and is callable like any service:

agent := micro.NewAgent("task-mgr",
    micro.AgentServices("task", "project"),
    micro.AgentPrompt("You manage tasks and projects. You understand deadlines and priorities."),
    micro.AgentProvider("anthropic"),
)
agent.Run()

The agent discovers its services from the registry, scopes its tools to their endpoints, and maintains conversation memory in the store. It registers itself so micro chat and other agents can find it.

// Programmatic interaction
resp, _ := agent.Ask(ctx, "What tasks are overdue?")
fmt.Println(resp.Reply)

Multiple agents coordinate via RPC — each is a service with an Agent.Chat endpoint. micro chat routes to the right one.

micro agent list                    # list registered agents
micro call task-mgr Agent.Chat '{"message": "What tasks are overdue?"}'

Plan & Delegate

Every agent gets two built-in capabilities, exposed as tools — no extra setup, no harness:

• plan — for multi-step work, the agent records an ordered plan in its store-backed memory and stays oriented across turns.
• delegate — the agent hands a self-contained subtask to another agent. If a registered agent already owns the relevant services, the hand-off goes over RPC to that agent; otherwise a focused, short-lived sub-agent is created for the subtask with its own isolated context.

This keeps intelligence distributed: an agent doesn't need to know how to do everything, only who does. See examples/agent-plan-delegate.

// A sub-agent is just an agent — created with New, talked to with Ask.
// delegate-first: reuse a registered agent, or spin up a focused one.
resp, _ := agent.Ask(ctx, "Plan the launch, create the tasks, and have comms notify the owner.")

Features

AI

Feature	Details
Agents	micro.NewAgent() — intelligent layer that manages services
Plan & delegate	Built-in agent tools — plan multi-step work, delegate subtasks to other agents
Guardrails	MaxSteps (stopping condition) and ApproveTool (human-in-the-loop) on every agent
Workflows	micro.NewFlow() — event-driven; runs a step or triggers an agent
MCP gateway	Every endpoint is an AI tool automatically
7 LLM providers	Anthropic, OpenAI, Gemini, Groq, Mistral, Together, Atlas Cloud
Interactive console	micro run includes a chat console for talking to services
Service generation	micro run --prompt — describe a system, get running services

Framework

Feature	Details
Service registry	mDNS (default), Consul, etcd
RPC client/server	gRPC transport, load balancing, streaming
Pub/sub events	NATS, RabbitMQ, HTTP broker
Key-value store	File (bbolt), Postgres, NATS KV
Typed model layer	CRUD + queries, SQLite/Postgres backends
Everything swappable	All abstractions are Go interfaces

Developer experience & deployment

Feature	Details
Hot reload	micro run watches files, rebuilds on change
Templates	micro new --template crud/pubsub/api
One-command deploy	micro deploy user@server — SSH + systemd, no Docker

CLI

Command	Purpose
micro run --prompt "..."	Generate services + agent, start with interactive console
micro run	Dev mode: hot reload, gateway, interactive console
micro run -d	Detached mode (no console)
micro chat	Standalone chat (when not using micro run)
micro agent list	List registered agents
micro new myservice	Scaffold a service
micro call service endpoint '{}'	Call a service or agent from the CLI
micro build	Compile production binaries
micro deploy user@server	Deploy via SSH + systemd

Multi-Service Projects

Run multiple services together:

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

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

g := micro.NewGroup(users, orders)
g.Run()

Or use a micro.mu config file:

service users
    path ./users

service orders
    path ./orders
    depends users

Data Model

Typed persistence with CRUD and queries:

type User struct {
    ID    string `json:"id" model:"key"`
    Name  string `json:"name"`
    Email string `json:"email" model:"index"`
}

db := service.Model()
db.Register(&User{})
db.Create(ctx, &User{ID: "1", Name: "Alice", Email: "alice@example.com"})

var results []*User
db.List(ctx, &results, model.Where("email", "alice@example.com"))

Backends: memory (default), SQLite, Postgres.

AI Providers

Swap providers with a single import — same interface everywhere:

Provider	Default Model
Anthropic	claude-sonnet-4-20250514
OpenAI	gpt-4o
Google Gemini	gemini-2.5-flash
Groq	llama-3.3-70b-versatile
Mistral	mistral-large-latest
Together AI	Llama-3.3-70B-Instruct-Turbo
Atlas Cloud	llama-3.3-70b

m := ai.New("anthropic", ai.WithAPIKey(key))
resp, _ := m.Generate(ctx, &ai.Request{Prompt: "hello"})

Examples

• hello-world — Basic RPC service
• multi-service — Multiple services in one binary
• mcp — MCP integration with AI agents
• agent-plan-delegate — Agent planning and multi-agent delegation
• grpc-interop — Call go-micro from any gRPC client

See all examples.

Docs

• Getting Started
• AI Integration
• Agents and Workflows
• Agent Design
• Plan & Delegate
• MCP & AI Agents
• Data Model
• Deployment
• Plugins

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