Claude Langgraph Mcp
What is Claude Langgraph Mcp
claude-langgraph-mcp is a Multi-Agent Control Protocol tool built with LangGraph, designed to facilitate complex workflows between different AI agents, with Claude serving as the primary orchestrator.
Use cases
Use cases for claude-langgraph-mcp include task planning and execution in collaborative environments, integrating different AI functionalities to enhance productivity, and creating interactive AI-driven applications.
How to use
To use claude-langgraph-mcp, clone the repository, install the required dependencies, configure your API key in the .env file, and run the application using the command ‘chainlit run main.py’.
Key features
Key features include multi-agent workflow orchestration, integration with the Claude API, an extensible agent architecture, state management across workflow steps, and an interactive chat interface using Chainlit.
Where to use
claude-langgraph-mcp can be used in various fields that require coordination between multiple AI agents, such as project management, automated customer service, and complex data processing tasks.
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 Claude Langgraph Mcp
claude-langgraph-mcp is a Multi-Agent Control Protocol tool built with LangGraph, designed to facilitate complex workflows between different AI agents, with Claude serving as the primary orchestrator.
Use cases
Use cases for claude-langgraph-mcp include task planning and execution in collaborative environments, integrating different AI functionalities to enhance productivity, and creating interactive AI-driven applications.
How to use
To use claude-langgraph-mcp, clone the repository, install the required dependencies, configure your API key in the .env file, and run the application using the command ‘chainlit run main.py’.
Key features
Key features include multi-agent workflow orchestration, integration with the Claude API, an extensible agent architecture, state management across workflow steps, and an interactive chat interface using Chainlit.
Where to use
claude-langgraph-mcp can be used in various fields that require coordination between multiple AI agents, such as project management, automated customer service, and complex data processing tasks.
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
Claude LangGraph MCP Tool
A Multi-Agent Control Protocol tool built with LangGraph, designed to work with Claude and other AI agents. This tool enables complex workflows between different AI agents, with Claude as the primary orchestrator.
Features
- Multi-agent workflow orchestration
- Integration with Claude API
- Extensible agent architecture
- State management across workflow steps
- Interactive chat interface using Chainlit
Setup
- Clone the repository
- Install dependencies:
pip install -r requirements.txt - Copy
.env.exampleto.envand add your Anthropic API key - Run the application:
chainlit run main.py
Architecture
agents/: Contains agent implementationsbase_agent.py: Base agent classclaude_agent.py: Claude-specific agent implementation
workflow/: Workflow managementgraph.py: LangGraph workflow definition
main.py: Application entry point
Usage
The tool uses a three-agent system:
- Planner: Breaks down tasks into steps
- Executor: Carries out individual steps
- Synthesizer: Combines results into final output
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
MIT License
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.
