MCP Server
This is a Python project designed to serve as an MCP (Multi-Cloud Platform) server. It utilizes FastAPI for the web framework and Uvicorn as the ASGI server. The project also includes an agents-library
for managing agent-related rules and prompts.
: Technologies Used
- Python
- FastAPI: Web framework for building APIs.
- Uvicorn: ASGI server.
- mcp: Multi-Cloud Platform SDK.
: Project Structure
Dockerfile
: Used for containerizing the application.compose.yaml
: Used for running the application with Docker Compose.requirements.txt
: Lists Python dependencies.app/
:server.py
: The main application server.
agents-library/
:dev_rules.agents.md
: Development-related agent rules.security_checks.agents.md
: Security-related agent checks.common_prompts.agents.md
: Common prompts for agents.
: Getting Started
To get started with this project, you need to have Python 3.10+ and Docker installed on your system.
Prerequisites
- Python 3.10+
- Docker
- pip
Installation
- Create and Activate Virtual Environment:
- Install Dependencies:
: Building and Running
You can run the server using Docker Compose or directly with Uvicorn.
Using Docker Compose
To run the server with Docker Compose, use the following command:
Using Uvicorn
To run the server with Uvicorn, use the following command:
: Development Conventions
- Virtual Environments: Always use a virtual environment for dependency management.
- Dependencies: All Python dependencies should be listed in
requirements.txt
.
: API Endpoints
The following API endpoints are available:
POST /test/call_tool
: Test endpoint for direct tool invocation.POST /test/read_resource
: Test endpoint for direct resource invocation.
The MCP server also exposes the following tools:
get_agents_instructions
: Retrieves a specific AGENTS.md file for providing AI with instructions and context.list_agents_instructions
: Lists all available AGENTS.md files.
: Adding to gemini-cli
To add this server to gemini-cli
, you need to edit your settings.json
file. You can find this file in ~/.gemini/settings.json
(user settings) or in .gemini/settings.json
(project settings).
Add the following to your settings.json
file:
Using the mcp
tool
Once the mcp-server
is configured in gemini-cli
, you can use the mcp
tool to interact with the server. For example, to list all available agent instructions:
To retrieve a specific agent instruction file:
See reference.
: License
This project is licensed under the Apache License 2.0.
: Author
This project was started in 2025 by Nicholas Wilde.
This server cannot be installed
remote-capable server
The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.
Enables access to agent instruction files and prompts for AI development workflows. Provides tools to retrieve and list development rules, security checks, and common prompts from an agents library through MCP protocol.
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