Dvy246 Mcp Server

MCP Chat Application

A production-ready Streamlit and CLI-based chat interface that leverages the Model Context Protocol (MCP) to connect Google's Gemini LLM with various tools and servers.

Features

• Interactive Chat: Clean Streamlit-based web interface and CLI option
• Multi-Server Support: Connects to multiple MCP servers simultaneously
• Expense Server: Remote expense tracking server
• Manim Server: Local Manim server for generating math animations
• Math Server: Local math operations server (server.py)
• Configuration-Driven: YAML-based configuration with environment variable support
• Comprehensive Logging: Structured logging to files and console
• Error Handling: Robust error handling throughout the application
• Tested: Unit tests for all math operations
• Gemini Integration: Uses langchain-google-genai for conversational AI

Prerequisites

• Python 3.10+
• uv (optional, for running math server via fastmcp)
• A Google Gemini API Key

Installation

1. Clone the repository (if applicable) or navigate to the project directory.

1. Install Dependencies:

``bash pip install streamlit langchain-google-genai langchain-mcp-adapters python-dotenv pyyaml fastmcp pytest ``

1. Environment Setup:

Copy the example environment file and fill in your values: ``bash cp .env.example .env ``

Edit .env and add your Gemini API key: ``env GEMINI_API_KEY=your_api_key_here ``

Optionally, override default paths: ``env UV_PATH=/path/to/uv PYTHON_PATH=/path/to/python3 MANIM_EXECUTABLE=/path/to/manim MATH_SERVER_PATH=/path/to/server.py MANIM_SERVER_PATH=/path/to/manim_server.py ``

1. Configuration:

The config.yaml file defines server connections and application settings. You can:

• Enable/disable servers by setting enabled: true/false
• Modify server transport types and commands
• Adjust LLM settings (model, temperature)
• Configure logging levels

Usage

Running the Streamlit Chat Application

streamlit run app.py

The application will open in your default web browser. You can chat with the agent, which will use connected MCP tools to answer queries.

Running the CLI Application

python client1.py

Or use it programmatically:

from client1 import main
import asyncio

result = asyncio.run(main("What is 25 + 17?"))
print(result)

Running the Local Math Server

To run the math server standalone (for testing):

python server.py

To use it within the chat app, enable it in config.yaml:

servers:
  math:
    enabled: true
    # ... rest of configuration

Testing

Run the test suite:

pytest test_server.py -v

This will test all mathematical operations provided by the server.

Project Structure

mcp-server/
├── app.py              # Streamlit web interface
├── client1.py          # CLI interface
├── server.py           # Math MCP server
├── config.yaml         # Application configuration
├── config_loader.py    # Configuration loader utility
├── test_server.py      # Unit tests
├── .env                # Environment variables (not in git)
├── .env.example        # Example environment file
├── logs/               # Application logs
│   ├── mcp_chat.log
│   └── mcp_cli.log
├── README.md           # This file
├── LICENSE             # License file
└── pyproject.toml      # Python project metadata

Configuration

Server Configuration (config.yaml)

Servers are defined with the following structure:

servers:
  server-name:
    enabled: true
    transport: stdio  # or streamable_http
    command: ${PYTHON_PATH:-python3}
    args:
      - /path/to/server.py
    env:
      ENV_VAR: value

Environment variables in the format ${VAR_NAME:-default} are automatically expanded.

Logging

Logs are written to:

• logs/mcp_chat.log (Streamlit app)
• logs/mcp_cli.log (CLI app)

Configure logging level in config.yaml:

logging:
  level: INFO  # DEBUG, INFO, WARNING, ERROR

Troubleshooting

FileNotFoundError for uv or python3

Update your .env file with the correct paths:

UV_PATH=/Users/yourname/path/to/uv
PYTHON_PATH=/Users/yourname/path/to/python3

GEMINIAPIKEY not found

Ensure your .env file contains:

GEMINI_API_KEY=your_actual_api_key

MCP Server Connection Errors

Check the logs in logs/ directory for detailed error messages. Ensure:

• Server paths are correct in .env
• Servers are enabled in config.yaml
• Required dependencies are installed

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests for new functionality
5. Run the test suite
6. Submit a pull request

License

See LICENSE file for details.

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: dvy246
• Source: dvy246/Mcp-server
• License: MIT

Install and usage instructions live in the source repository linked above.