Langgraph Mcp Example
What is Langgraph Mcp Example
langgraph-mcp-example is a sample project that demonstrates how to use the langgraph library with MCP (Multi-Channel Processing).
Use cases
Use cases include building chatbots, developing AI-driven applications, and creating tools for data analysis that require processing multiple data streams simultaneously.
How to use
To use langgraph-mcp-example, create a .env file in the root directory with your OpenAI API key. Then, install the necessary packages using ‘pnpm install’, install tsx globally with ‘npm install -g tsx’, and run the MCP example with ‘tsx --watch ./src/langgrah_mcp/index.ts’.
Key features
Key features include integration with OpenAI’s API, real-time processing capabilities, and a structured example for developers to understand the usage of langgraph with MCP.
Where to use
langgraph-mcp-example can be used in fields such as natural language processing, AI development, and real-time data analysis where multi-channel processing is beneficial.
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 Langgraph Mcp Example
langgraph-mcp-example is a sample project that demonstrates how to use the langgraph library with MCP (Multi-Channel Processing).
Use cases
Use cases include building chatbots, developing AI-driven applications, and creating tools for data analysis that require processing multiple data streams simultaneously.
How to use
To use langgraph-mcp-example, create a .env file in the root directory with your OpenAI API key. Then, install the necessary packages using ‘pnpm install’, install tsx globally with ‘npm install -g tsx’, and run the MCP example with ‘tsx --watch ./src/langgrah_mcp/index.ts’.
Key features
Key features include integration with OpenAI’s API, real-time processing capabilities, and a structured example for developers to understand the usage of langgraph with MCP.
Where to use
langgraph-mcp-example can be used in fields such as natural language processing, AI development, and real-time data analysis where multi-channel processing is beneficial.
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
README.md
before debug all example , please create .env file in the root
# .env OPENAI_API_KEY=yours open ai key DEEPSEEK_API_KEY=yours deepseek key
langgraph example
./src/langgraph
mcp example
./src/langgrah_mcp
step1: pnpm install step2: npm install -g tsx step3: tsx --watch ./src/langgrah_mcp/index.ts
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.
