teddynote-lab/langgraph-mcp-agents
LangGraph-powered ReAct agent with Model Context Protocol (MCP) integration. A Streamlit web interface for dynamically configuring, deploying, and interacting with AI agents capable of accessing various data sources and APIs through MCP tools.
Overview
teddynote-lab/langgraph-mcp-agents is a Python MCP server. LangGraph-powered ReAct agent with Model Context Protocol (MCP) integration. A Streamlit web interface for dynamically configuring, deploying, and interacting with AI agents capable of accessing various data sources and APIs through MCP tools.
Ranked #3199 out of 25632 indexed tools.
Ecosystem
Python No license
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Stars 691
Freshness 11mo ago
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Forks 233
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From the README
# LangGraph Agents + MCP ## Project Overview `LangChain-MCP-Adapters` is a toolkit provided by **LangChain AI** that enables AI agents to interact with external tools and data sources through the Model Context Protocol (MCP). This project provides a user-friendly interface for deploying ReAct agents that can access various data sources and APIs through MCP tools. ### Features - **Streamlit Interface**: A user-friendly web interface for interacting with LangGraph `ReAct Agent` with MCP tools - **Tool Management**: Add, remove, and configure MCP tools through the UI (Smithery JSON format supported). This is done dynamically without restarting the application - **Streaming Responses**: View agent responses and tool calls in real-time - **Conversation History**: Track and manage conversations with the agent ## MCP Architecture The Model Context Protocol (MCP) consists of three main components: 1. **MCP Host**: Programs seeking to access data through MCP, such as Claude Desktop, IRead full README on GitHub →
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