MCP LangGraph Tools

v1.0.0Coding Agentsstable

MCP Tools Langraph Integration

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What is MCP LangGraph Tools?

MCP LangGraph Tools is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to mcp tools langraph integration

MCP Tools Langraph Integration

This server falls under the Coding Agents category on MCPgee, the world's largest MCP server directory with 33,000+ servers.

Features

  • MCP Tools Langraph Integration

Use Cases

LangGraph integration for agent workflows
Python-based agent tool composition
paulrobello

Maintainer

LicenseMIT
Languagepython
Versionv1.0.0
UpdatedMar 11, 2026
Statushealthy
Maintenanceactive

Works with

ClaudeOpenAIwindowsmacoslinux

Installation

Manual Installation

npx mcp-langgraph-tools

Configuration

Configuration Details

Config File

claude_desktop_config.json

Performance

Response Metrics

Response Time< 200ms
ThroughputMedium

Resource Usage

Memory UsageLow
CPU UsageLow

How to Set Up and Use MCP LangGraph Tools

MCP LangGraph Tools is a Python project that demonstrates how to integrate MCP server tools directly into LangGraph agent workflows, bridging the two frameworks so LangGraph agents can call any MCP-exposed capability as a native tool. It implements a two-node agent/tool graph pattern that connects to MCP servers (such as Brave Search) at runtime and routes tool calls through the graph. This is useful for developers who want to build LangGraph-powered agents that consume the rich ecosystem of MCP servers without writing custom tool wrappers.

Prerequisites

  • Python 3.11+ installed
  • Node.js and npx available on your PATH (for MCP server processes)
  • uv package manager installed (https://github.com/astral-sh/uv)
  • Brave Search API key from https://brave.com/search/api/ (for the example)
  • Anthropic API key (or alternate LLM provider key) for the agent LLM
1

Clone the repository

Clone the mcp_langgraph_tools repository to your local machine.

git clone https://github.com/paulrobello/mcp_langgraph_tools.git
cd mcp_langgraph_tools
2

Install uv and project dependencies

Install uv if you do not have it, then use it to set up the project environment.

curl -LsSf https://astral.sh/uv/install.sh | sh
uv sync
3

Configure environment variables

Create a .env file at the repository root with your API keys. The project defaults to Anthropic as the LLM provider.

BRAVE_API_KEY=your_brave_search_api_key
ANTHROPIC_API_KEY=your_anthropic_api_key
4

Run the LangGraph agent

Execute the project using uv run to launch the LangGraph agent, which will connect to MCP servers and expose their tools to the graph.

uv run mcp_langgraph_tools
5

Explore multi-server configuration

Switch to the multi-server branch to see how multiple MCP servers can be wired into a single LangGraph agent simultaneously.

git checkout multi-server

MCP LangGraph Tools Examples

Client configuration

This project runs as a standalone Python script rather than an MCP server. Configure the MCP servers it consumes inside __main__.py or the equivalent config block.

{
  "mcpServers": {
    "brave-search": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-brave-search"],
      "env": {
        "BRAVE_API_KEY": "your_brave_search_api_key"
      }
    }
  }
}

Prompts to try

When running the LangGraph agent, these are example queries you can pass to exercise the Brave Search tool through the graph.

- "Search the web for the latest news on Model Context Protocol"
- "Find recent Python 3.12 release notes using Brave Search"
- "What are the top LangGraph tutorials available online?"
- "Search for Apache Airflow 3.0 migration guides"

Troubleshooting MCP LangGraph Tools

Agent fails with 'BRAVE_API_KEY not set' or similar error

Ensure your .env file exists at the project root and contains the correct key names BRAVE_API_KEY and ANTHROPIC_API_KEY. The project uses python-dotenv to load this file automatically at startup.

npx command not found when starting the MCP server subprocess

Node.js and npx must be installed and on your PATH. Run node --version and npx --version to verify. On macOS, install Node.js via Homebrew: brew install node.

LangGraph graph terminates without calling any tools

Check that the MCP server process started successfully — errors in the server subprocess are often logged to stderr. Confirm the tool names returned by the MCP server match what the agent node expects, and that your LLM API key is valid.

Frequently Asked Questions about MCP LangGraph Tools

What is MCP LangGraph Tools?

MCP LangGraph Tools is a Model Context Protocol (MCP) server that mcp tools langraph integration It connects AI assistants to external tools and data sources through a standardized interface.

How do I install MCP LangGraph Tools?

Follow the installation instructions on the MCP LangGraph Tools GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.

Which AI clients work with MCP LangGraph Tools?

MCP LangGraph Tools works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.

Is MCP LangGraph Tools free to use?

Yes, MCP LangGraph Tools is open source and available under the MIT license. You can use it freely in both personal and commercial projects.

Browse More Coding Agents MCP Servers

Explore all coding agents servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.

Quick Config Preview

{ "mcpServers": { "mcp-langgraph-tools": { "command": "npx", "args": ["-y", "mcp-langgraph-tools"] } } }

Add this to your claude_desktop_config.json or .cursor/mcp.json

Read the full setup guide →

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