MCP CLI Command Examples

This document provides examples of using the micro mcp commands for AI agent integration.

List Available Tools
Test a Tool
Generate Documentation
Export to Different Formats

Prerequisites

You need at least one microservice running with the go-micro framework. The service will automatically be discovered via the registry (mdns by default).

Example service:

bash

cd examples/mcp/hello
go run main.go

List Available Tools

Human-readable list

bash

micro mcp list

Output:

Available MCP Tools:

Service: greeter
  • greeter.Greeter.SayHello

Total: 1 tools

JSON output

bash

micro mcp list --json

Output:

json

{
  "count": 1,
  "tools": [
    {
      "description": "Call SayHello on greeter service",
      "endpoint": "Greeter.SayHello",
      "name": "greeter.Greeter.SayHello",
      "service": "greeter"
    }
  ]
}

Test a Tool

Basic test

bash

micro mcp test greeter.Greeter.SayHello '{"name": "Alice"}'

Output:

Testing tool: greeter.Greeter.SayHello
Service: greeter
Endpoint: Greeter.SayHello
Input: {"name": "Alice"}

✅ Call successful!

Response:
{
  "message": "Hello Alice!"
}

Test with default empty input

bash

micro mcp test greeter.Greeter.SayHello

This will call the tool with an empty JSON object {}.

Generate Documentation

Markdown documentation (stdout)

bash

micro mcp docs

Output:

markdown

# MCP Tools Documentation

Generated: 2026-02-13 14:30:00

Total Tools: 1

## Service: greeter

### greeter.Greeter.SayHello

**Description:** Greets a person by name. Returns a friendly greeting message.

**Example Input:**
\`\`\`json
{"name": "Alice"}
\`\`\`

Markdown documentation (save to file)

bash

micro mcp docs --output mcp-tools.md

This creates a mcp-tools.md file with the documentation.

JSON documentation

bash

micro mcp docs --format json

Output:

json

{
  "count": 1,
  "tools": [
    {
      "description": "Greets a person by name. Returns a friendly greeting message.",
      "endpoint": "Greeter.SayHello",
      "example": "{\"name\": \"Alice\"}",
      "metadata": {
        "description": "Greets a person by name. Returns a friendly greeting message.",
        "example": "{\"name\": \"Alice\"}"
      },
      "name": "greeter.Greeter.SayHello",
      "scopes": null,
      "service": "greeter"
    }
  ]
}

JSON documentation (save to file)

bash

micro mcp docs --format json --output tools.json

Export to Different Formats

Export to LangChain (Python)

Generate Python code with LangChain tool definitions:

bash

micro mcp export langchain

Output:

python

# LangChain Tools for Go Micro Services
# Auto-generated from MCP service discovery

from langchain.tools import Tool
import requests
import json

# Configure your MCP gateway endpoint
MCP_GATEWAY_URL = 'http://localhost:3000/mcp'

def call_mcp_tool(tool_name, arguments):
    """Call an MCP tool via HTTP gateway"""
    response = requests.post(
        f'{MCP_GATEWAY_URL}/call',
        json={'name': tool_name, 'arguments': arguments}
    )
    response.raise_for_status()
    return response.json()

# Define tools
tools = []

def greeter_Greeter_SayHello(arguments: str) -> str:
    """Greets a person by name. Returns a friendly greeting message."""
    args = json.loads(arguments) if isinstance(arguments, str) else arguments
    return json.dumps(call_mcp_tool('greeter.Greeter.SayHello', args))

tools.append(Tool(
    name='greeter.Greeter.SayHello',
    func=greeter_Greeter_SayHello,
    description='Greets a person by name. Returns a friendly greeting message.'
))

# Example usage:
# from langchain.agents import initialize_agent, AgentType
# from langchain.llms import OpenAI
#
# llm = OpenAI(temperature=0)
# agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION)
# agent.run('Your query here')

Save to file:

bash

micro mcp export langchain --output langchain_tools.py

Export to OpenAPI 3.0

Generate an OpenAPI specification:

bash

micro mcp export openapi

Output:

json

{
  "components": {
    "securitySchemes": {
      "bearerAuth": {
        "scheme": "bearer",
        "type": "http"
      }
    }
  },
  "info": {
    "description": "Auto-generated OpenAPI spec from MCP service discovery",
    "title": "Go Micro MCP Services",
    "version": "1.0.0"
  },
  "openapi": "3.0.0",
  "paths": {
    "/mcp/call/greeter/Greeter/SayHello": {
      "post": {
        "description": "Greets a person by name. Returns a friendly greeting message.",
        "operationId": "greeter_Greeter_SayHello",
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "type": "object"
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "type": "object"
                }
              }
            },
            "description": "Successful response"
          }
        },
        "summary": "greeter.Greeter.SayHello"
      }
    }
  },
  "servers": [
    {
      "description": "MCP Gateway",
      "url": "http://localhost:3000"
    }
  ]
}

Save to file:

bash

micro mcp export openapi --output openapi.json

Export to raw JSON

Export raw tool definitions:

bash

micro mcp export json

This is similar to micro mcp docs --format json but specifically for export purposes.

Save to file:

bash

micro mcp export json --output tools.json

Using with Different Registries

By default, the commands use mdns registry. You can specify a different registry:

bash

# Using consul
micro mcp list --registry consul --registry_address consul:8500

# Using etcd
micro mcp list --registry etcd --registry_address etcd:2379

Integration Examples

Using LangChain Export with Claude

Export your tools to LangChain format:

bash

micro mcp export langchain --output my_tools.py

Use in your Python agent:

python

from my_tools import tools
from langchain.agents import initialize_agent, AgentType
from langchain.chat_models import ChatAnthropic

llm = ChatAnthropic(model="claude-3-sonnet-20240229")
agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION)

result = agent.run("Greet Alice")
print(result)

Using OpenAPI Export with GPT

Export to OpenAPI:

bash

micro mcp export openapi --output openapi.json

Upload to ChatGPT as a custom GPT action or use with OpenAI Assistants API.

Documentation for AI Agents

Generate documentation that AI agents can read to understand your services:

bash

micro mcp docs --format json --output service-catalog.json

This JSON file can be fed to AI agents for service discovery and understanding.

Advanced Usage

Piping and Processing

You can pipe the output to other tools:

bash

# Count tools per service
micro mcp list --json | jq '.tools | group_by(.service) | map({service: .[0].service, count: length})'

# Extract all tool names
micro mcp list --json | jq -r '.tools[].name'

# Filter tools by service
micro mcp list --json | jq '.tools[] | select(.service == "greeter")'

Monitoring and CI/CD

Use these commands in your CI/CD pipeline:

bash

# Validate all services are discoverable
SERVICE_COUNT=$(micro mcp list --json | jq '.count')
if [ "$SERVICE_COUNT" -lt 5 ]; then
  echo "Error: Expected at least 5 services, found $SERVICE_COUNT"
  exit 1
fi

# Generate documentation on each deployment
micro mcp docs --output docs/mcp-services.md
git add docs/mcp-services.md
git commit -m "Update MCP service documentation"

Testing in Development

Create a script to test all your tools:

bash

#!/bin/bash
# test-all-tools.sh

TOOLS=$(micro mcp list --json | jq -r '.tools[].name')

for tool in $TOOLS; do
  echo "Testing $tool..."
  micro mcp test "$tool" "{}" || echo "Failed: $tool"
done

Troubleshooting

No tools found

If micro mcp list shows 0 tools:

Verify services are running:

bash

ps aux | grep "your-service"

Check registry (mdns might need time to discover):

bash

# Wait a few seconds and try again
sleep 3
micro mcp list

Use a different registry if mdns is unreliable:

bash

# Start services with consul
micro --registry consul server

# List with consul
micro mcp list --registry consul

Service not responding in tests

If micro mcp test fails:

Verify the tool name is correct:

bash

micro mcp list

Check the JSON input format:

bash

# Invalid
micro mcp test service.Handler.Method '{invalid}'

# Valid
micro mcp test service.Handler.Method '{"key": "value"}'

Check service logs for errors.

Next Steps

Read the MCP Documentation
Try the MCP Examples
Learn about Tool Scopes and Security
Explore Agent SDKs (coming soon)

MCP CLI Command Examples

MCP CLI Command Examples

Table of Contents

Prerequisites

List Available Tools

Human-readable list

JSON output

Test a Tool

Basic test

Test with default empty input

Generate Documentation

Markdown documentation (stdout)

Markdown documentation (save to file)

JSON documentation

JSON documentation (save to file)

Export to Different Formats

Export to LangChain (Python)

Export to OpenAPI 3.0

Export to raw JSON

Using with Different Registries

Integration Examples

Using LangChain Export with Claude

Using OpenAPI Export with GPT

Documentation for AI Agents

Advanced Usage

Piping and Processing

Monitoring and CI/CD

Testing in Development

Troubleshooting

No tools found

Service not responding in tests

Next Steps