MCP Server with LangChain and AI Tools
Used for storing API keys and configuration settings for the MCP server
Enables the creation of multi-tool AI assistants using LangChain MCP Adapters to connect tools and services
Integrates with the system to create conversational AI agents that can interact with multiple MCP tools
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Server with LangChain and AI Toolscalculate 15% of 200 and tell me the weather in Tokyo"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
π§ MCP Server with LangChain and AI Tools
This project demonstrates how to build a multi-tool AI assistant using the Model Context Protocol (MCP), LangChain, and Groqβs Qwen model. It includes:
π A local Math MCP Server
π€οΈ A simulated Weather MCP Server
π€ A conversational AI agent (MCP client) that talks to both
π§° Features
Uses LangChain MCP Adapters to connect tools
Powered by Groq's Qwen LLM
Handles local and remote tool servers via MCP
Interactive CLI chat with tool usage detection
Related MCP server: MCP Server
π Prerequisites
Python >= 3.11
uvfor project/environment management (https://github.com/astral-sh/uv)Internet connection for loading LLM (Groq)
βοΈ Setup Instructions
1. Create Project
mkdir mcp_project
cd mcp_project
uv initSet Python version in .python-version and pyproject.toml to >=3.11
2. Create Virtual Environment
uv venv
source .venv/Scripts/activate3. Add Dependencies
Create a requirements.txt file:
langchain-mcp-adapters
langchain-groq
langgraph
mcpInstall them
uv add -r requirements.txtProject Structure
mcp_project/ β βββ math_server.py # MCP server for math tools βββ weather_server.py # MCP server for weather API simulation βββ client.py # MCP client with AI agent βββ requirements.txt βββ .python-version βββ .env # For storing Groq API key (GROQ_API_KEY)
How to Run
1. Run the Weather Server
python weather_server.py2. Run the Client (Automatically runs math server as sub process)
python client.pyExample Conversation
You: What is the output of 2*3/(4-2)
AI: The result is 3.0
You: What is the weather in New York?
AI: The current weather in New York is sunny.
You: thanks
AI: You're welcome! πNote
The weather server is simulated. Replace it with real API logic if needed.
You can add more MCP servers for documents, search, DBs, etc.
Use .env to store your GROQ_API_KEY.
This server cannot be deployed
Maintenance
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