Mcp Langgraph Tools
What is Mcp Langgraph Tools
mcp_langgraph_tools is a project that demonstrates how to integrate MCP endpoint tools into a Langgraph tool node, consisting of two nodes: ‘agent’ and ‘tool’.
Use cases
Use cases include building AI-driven applications that require access to external search tools, creating data pipelines that utilize multiple MCP servers, and developing prototypes for testing Langgraph integrations.
How to use
To use mcp_langgraph_tools, ensure you have Python 3.11 installed. You can run the project using the command ‘uv run mcp_langgraph_tools’ after setting up the necessary API keys in a .env file.
Key features
Key features include integration with MCP endpoint tools, support for multiple MCP servers, and the ability to utilize Brave Search tools via the MCP Server sample.
Where to use
mcp_langgraph_tools can be used in fields such as AI development, data processing, and any application that requires integration of external tools with Langgraph.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Mcp Langgraph Tools
mcp_langgraph_tools is a project that demonstrates how to integrate MCP endpoint tools into a Langgraph tool node, consisting of two nodes: ‘agent’ and ‘tool’.
Use cases
Use cases include building AI-driven applications that require access to external search tools, creating data pipelines that utilize multiple MCP servers, and developing prototypes for testing Langgraph integrations.
How to use
To use mcp_langgraph_tools, ensure you have Python 3.11 installed. You can run the project using the command ‘uv run mcp_langgraph_tools’ after setting up the necessary API keys in a .env file.
Key features
Key features include integration with MCP endpoint tools, support for multiple MCP servers, and the ability to utilize Brave Search tools via the MCP Server sample.
Where to use
mcp_langgraph_tools can be used in fields such as AI development, data processing, and any application that requires integration of external tools with Langgraph.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
MCP Tool Langgraph Integration
Description
Example project of how to integrate MCP endpoint tools into a Langgraph tool node
The graph consists of only 2 nodes, agent and tool.
Prerequisites
To use this project, make sure you have Python 3.11.
uv is recommended
Linux and Mac
curl -LsSf https://astral.sh/uv/install.sh | sh
Windows
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
MCP Server requirements
- This example uses the MCP Server sample
@modelcontextprotocol/server-brave-searchto add Brave Search tools. This requires that you havenodeandnpxinstalled.
API Keys
- The MCP Server sample used is for Brave Search, you can get a free API key from https://brave.com/search/api/
- You will need and API key for the chosen AI provider which defaults to Anthropic but can be changed by editing the
__main__.pyfile - Put all api keys in a .env file in the repository root.
From source Usage
uv run mcp_langgraph_tools
Multiple MCP servers at one time
Check the multi_server branch for a more advanced example of how to use multiple MCP servers at once.
Whats New
- Version 0.1.0:
- Initial release
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Author
Paul Robello - [email protected]
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.
