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Click on "Install 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., "@Agents Library MCP Servershow me the security check prompts for API development"
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.
:robot: MCP Server :computer:
An MCP (Multi-Cloud Platform) server that provides a library of reusable agent instructions and scripts to a generative AI model.
This project is in a development stage. Features and configurations are subject to change.
:book: Documentation
For comprehensive documentation, please visit the MkDocs site.
Related MCP server: MCP Starter
:mag: TL;DR
The MCP Server uses FastAPI to expose a set of tools that can be consumed by a compatible AI model (like Google's Gemini). It provides a library of standardized instructions (AGENTS.md files) and utility scripts (.sh files) to enable the AI to perform complex, context-aware tasks.
To bootstrap the project
task bootstrapTo run the server locally:
task runAdd to gemini-cli settings:
{
"mcpServers": {
"sharedAgents": {
"httpUrl": "http://<ip-address>:8080"
}
}
}:mag: Overview
This server uses FastAPI to expose a set of tools that can be consumed by a compatible AI model (like Google's Gemini). The primary purpose is to provide the AI with a library of standardized instructions (AGENTS.md files) and utility scripts (.sh files). This allows the AI to perform complex, context-aware tasks consistently by drawing from a central, version-controlled library.
The core components are:
app/server.py: The FastAPI application that serves the tools.agents-library/: The central repository for agent instructions and scripts.
:balance_scale: License
This project is licensed under the Apache License 2.0.
:pencil: Author
This project was started in 2025 by Nicholas Wilde.
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