LangChainGo MCP Adapter

Created By

i2ya year ago

A Go adapter that bridges LangChain Go tools with Model Context Protocol (MCP) servers.

# go

# agent

Overview Content Comments

Content

LangChainGo MCP Adapter

A Go adapter that bridges LangChain Go tools with Model Context Protocol (MCP) servers.

Overview

This adapter allows you to use tools defined on an MCP server with the LangChain Go library. It implements the necessary interfaces to integrate MCP tools seamlessly with LangChain Go's agent infrastructure.

Features

Connect to any MCP server
Automatically discover MCP tools from a specified MCP server and make them available to LangChain Go
Wrap MCP tools as LangChain Go tools

Installation

go get github.com/i2y/langchaingo-mcp-adapter

Usage

package main

import (
    "context"
    "log"
    "os"

    "github.com/i2y/langchaingo-mcp-adapter"
    "github.com/mark3labs/mcp-go/client"
    "github.com/tmc/langchaingo/agents"
    "github.com/tmc/langchaingo/chains"
    "github.com/tmc/langchaingo/llms/googleai"
    "github.com/tmc/langchaingo/tools"
)

func main() {
    // Create an MCP client using stdio
    mcpClient, err := client.NewStdioMCPClient(
        "./an-mcp-server",  // Path to an MCP server
        nil,                // Additional environment variables if needed
    )
    if err != nil {
        log.Fatalf("Failed to create MCP client: %v", err)
    }
    defer mcpClient.Close()

    // Create the adapter
    adapter, err := langchaingo_mcp_adapter.New(mcpClient)
    if err != nil {
        log.Fatalf("Failed to create adapter: %v", err)
    }

    // Get all tools from MCP server
    mcpTools, err := adapter.Tools()
    if err != nil {
        log.Fatalf("Failed to get tools: %v", err)
    }

    ctx := context.Backgorund()

    // Create a Google AI LLM client
    llm, err := googleai.New(
        ctx,
        googleai.WithDefaultModel("gemini-2.0-flash"),
        googleai.WithAPIKey(os.Getenv("GOOGLE_API_KEY")),
    )
    if err != nil {
        log.Fatalf("Create Google AI client: %v", err)
    }

    // Create a agent with the tools
    agent := agents.NewOneShotAgent(
        llm,
        mcpTools,
        agents.WithMaxIterations(3),
    )
    executor := agents.NewExecutor(agent)

    // Use the agent
    question := "Can you help me analyze this data using the available tools?"
    result, err := chains.Run(
        ctx,
        executor,
        question,
    )
    if err != nil {
        log.Fatalf("Agent execution error: %v", err)
    }

    log.Printf("Agent result: %s", result)
}