mcp-langgraph-agents

SumanMadipeddi/mcp-langgraph-agents

3.2

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Model Context Protocol (MCP) is an open protocol that enables AI assistants to connect with external tools, databases, and services, enhancing their capabilities.

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MCP Server & LLM Integration

A practical guide to building MCP servers with FastMCP and integrating them with any LLM using mcp-use.

Project Structure

  • server/ - Basic weather MCP server using STDIO transport
  • mcpserver/ - Weather MCP server with SSE/HTTP transport, includes client examples and Streamlit UI
  • mcpagent/ - Simple MCP servers (math and weather) for agent integration examples
  • graph_agent/ - LangGraph integration examples
    • main.ipynb - Weather tool agent with LangSmith monitoring
    • main.py - Competitor ads flow analysis using Playwright and DuckDuckGo search MCP servers
  • app.py - Browser automation example using mcp-use with Groq LLM

Quick Start

# Install UV (if needed)
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"
curl -LsSf https://astral.sh/uv/install.sh | sh

# Install dependencies
uv sync

# Create .env file
echo "GROQ_API_KEY=your_key_here" > .env
echo "GEMINI_API_KEY=your_key_here" >> .env

# Run the weather MCP server
uv run python server/weather.py

# Run the LLM agent (in another terminal)
uv run python app.py

Resources