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LangChain MCP Chat Platform

@BilalAltundag

Repository

Basic information

Category

AI & Agents

Last updated

Transports

stdio

Author

BilalAltundag

About LangChain MCP Chat Platform

A versatile chat platform that integrates LangChain, custom MCP servers, and various AI models for enhanced chat capabilities.

LangChain MCP Chat Platform config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "langchain-mcp-chat-platform": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

LangChain MCP Chat Platform tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is LangChain MCP Chat Platform?

LangChain MCP Chat Platform is a chat platform that integrates LangChain, custom MCP (Model Control Protocol) servers, and Google's Gemini AI model for enhanced conversational capabilities. It is designed for developers who want to build a multi-service conversational application with web search, email, and accounting integrations.

How to use LangChain MCP Chat Platform?

Clone the repository, create a Python virtual environment, install dependencies from requirements.txt, set up a .env file with your GOOGLE_API_KEY and SMITHERY_KEY, then run the application from the web_js directory with python main.py. Optionally, enable the Gmail API in Google Cloud Console for email features.

Key features of LangChain MCP Chat Platform

  • LangChain integration for advanced conversation management and tool usage
  • Powered by Google Gemini 2.0 Flash model
  • Custom MCP servers: Tavily web search, Gmail, and accounting (muhasebe)
  • Conversation history tracking for contextual responses
  • Responsive web UI built with FastAPI and WebSockets
  • Extensible architecture to add new tools and capabilities

Use cases of LangChain MCP Chat Platform

  • Build a personal assistant that can search the web via Tavily and extract content
  • Automate email operations such as sending, reading, or managing Gmail messages
  • Manage financial records through the integrated accounting system (muhasebe)
  • Create a conversational interface that maintains context across multiple interactions
  • Prototype and test new MCP server integrations with a ready-made web UI

Frequently asked questions

1

What API keys are required?

You need `GOOGLE_API_KEY` for Gemini and `SMITHERY_KEY` to run Gmail and Tavily MCP servers. The `SMITHERY_KEY` alone is sufficient; you do not need separate `TAVILY_API_KEY` or `GMAIL_API_KEY` in this application.

2

What runtime dependencies are needed?

The application requires Python 3 with packages listed in `requirements.txt`, Node.js and NPM (for Tavily/Gmail via Smithery CLI), and a Google Cloud project with the Gmail API enabled if using email features.

3

How do I run only the custom accounting MCP server?

Modify `web_js/main.py` to include only the `custom_mcp` service in `MultiServerMCPClient` and comment out Tavily and Gmail entries. Start the application with `python main.py`.

4

What should I do if the application hangs during startup?

Try starting only with the custom MCP server, install Node.js globally, run `npm install -g @smithery/cli`, or run services manually in separate terminals to identify the cause.

5

Where does conversation data live?

The README does not specify a data storage backend beyond describing database operations in the `app/database/` folder, but no details on persistence location or format are provided.

Comments

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