About Brest MCP Server
Brest MCP Server is an MCP implementation for the Brest region, aimed at developers deploying or debugging MCP interactions. It includes a web inspector and supports agent-to-agent communication.
Key features
- 01Implement MCP interactions
- 02Built-in web inspector
- 03Support A2A agent communication
- 04Include client and debugging tools
- 05Use Python with uv package management
Use cases
- 01Debug an MCP server through the web interface
- 02Monitor server behavior
- 03Connect Brest Expert Agent to an A2A conversation
- 04Connect to the server with the included client
MCP support
The server implements MCP and includes an inspector for debugging and monitoring. The project also supports A2A agent-to-agent communication and provides client tools for connecting to the server.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEBrest MCP Server
A robust Model Context Protocol (MCP) server implementation for the Brest region, providing infrastructure for MCP-based interactions with built-in debugging and monitoring capabilities.
Table of Contents
- Description
- Features
- Prerequisites
- Technologies
- Installation
- Usage
- Development
- Troubleshooting
- Contributing
- License
Description
Brest MCP Server is a server implementation of the Model Context Protocol (MCP) for the Brest region. It provides a robust infrastructure for managing MCP-based interactions and includes an MCP inspector for debugging and monitoring.
The goal of this project is to facilitate the deployment and management of MCP services with a focus on simplicity and reliability.
Features
- 🚀 MCP Protocol Implementation: Full compliance with Model Context Protocol standards
- 🔍 Built-in Inspector: Debug and monitor your MCP server with the integrated web interface
- 🤖 AI Agent Integration: Support for A2A protocol and agent-to-agent communication
- 🐍 Python-based: Built with Python 3.12+ for modern development practices
- 📦 UV Package Management: Fast and reliable dependency management
- 🔧 Development Tools: Client tools and debugging utilities included
Prerequisites
Before installing Brest MCP Server, ensure you have:
- Python 3.12.3 or higher
- Node.js (for MCP Inspector)
- Git (for cloning the repository)
- uv package manager (installation instructions below)
Technologies
- Language: Python 3.12.3 or compatible
- Dependency Management: uv
- Inspector: MCP Inspector via Node.js (
npx) - Environment: Virtual environment managed by
uv - Protocol: Model Context Protocol (MCP) and A2A (Agent-to-Agent)
Installation
To install and configure Brest MCP Server locally, follow these steps:
-
Install
uv(if not already installed):- On Linux/macOS:
curl -LsSf https://astral.sh/uv/install.sh | sh - On Windows:
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
- On Linux/macOS:
-
Clone the repository:
git clone https://github.com/Nijal-AI/Brest-mcp-server.git cd Brest-mcp-server -
Create and activate the virtual environment:
uv venv source .venv/bin/activate # On Windows: .venv\Scripts\activate -
Install the dependencies:
uv sync
Usage
Running the Server
To run the server locally, proceed as follows:
-
Ensure the virtual environment is activated:
source .venv/bin/activate # On Windows: .venv\Scripts\activate -
Start the server with the MCP Inspector:
npx @modelcontextprotocol/inspector uv run brest-mcp -
Access the MCP Inspector in your browser:
- Proxy:
http://localhost:3000 - Web interface:
http://localhost:5173
- Proxy:
Example output:
Starting MCP inspector...
Proxy server listening on port 3000
🔍 MCP Inspector is up and running at http://localhost:5173 🚀
Using the Client
If you want to communicate with an AI agent using the Brest MCP Server, you can use the client provided in the tools directory:
uv run python tools/client.py src/server.py
AI Agent Integration
You can also chat with an AI agent using Brest MCP Server on A2A protocol.
-
Setup the agent:
echo "MCP_TRANSPORT=stdio" > src/.env -
Run the agent:
uv run agent -
Use with A2A samples demo (optional):
# Setup git clone https://github.com/google-a2a/a2a-samples.git echo "GOOGLE_API_KEY=your_api_key_here" > a2a-samples/demo/ui/.env # Run cd a2a-samples/demo/ui uv run main.pyThen navigate to
http://localhost:12000, go to "Agents" and connect your Brest Expert Agent atlocalhost:10030. You can add other agents if you want, then go to Home and create a new conversation to discuss with your agent(s).
Development
For developers wishing to contribute or work on advanced features, follow these additional steps:
-
Ensure the virtual environment is set up and dependencies are installed:
uv venv uv sync -
Use the MCP Inspector to debug and monitor the server:
npx @modelcontextprotocol/inspector uv run brest-mcp -
Refer to the
pyproject.tomlfile for details on dependencies and configurations.
Troubleshooting
Common Issues
Virtual environment activation fails
- Ensure
uvis properly installed and in your PATH - Try recreating the virtual environment:
uv venv --force
MCP Inspector not starting
- Ensure Node.js is installed:
node --version - Clear npm cache:
npm cache clean --force - Try installing the inspector globally:
npm install -g @modelcontextprotocol/inspector
Connection errors with A2A samples
- Verify your Google API key is correctly set in the
.envfile - Check that the Brest Expert Agent is running on
localhost:10030 - Ensure all required ports are available and not blocked by firewall
Dependencies installation fails
- Update
uvto the latest version:uv self update - Clear the cache:
uv cache clean - Try installing with verbose output:
uv sync -v
Getting Help
If you encounter issues not covered here:
- Check the Issues section on GitHub
- Review the MCP protocol documentation
- Create a new issue with detailed error messages and your environment details
Contributing
Contributions are welcome! To propose changes:
- Fork the repository
- Create a feature branch:
git checkout -b feature/your-feature-name - Make your changes and ensure tests pass
- Follow the coding standards defined in the project
- Submit a pull request with a clear description of your changes
Please refer to the CONTRIBUTING.md file for detailed guidelines.
License
This project is licensed under the MIT License. See the LICENSE file for details.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.