Fastmcp Agents Project
Project description
FastMCP 🚀 Agents 🤖
FastMCP Agents bridges the gap between the generic tools in MCP servers and the specialized tools you need to solve your problem and gives you a straight-forward way to manage tool sprawl:
- It turns generic tools in any MCP server into specialized tools that you can use anywhere
- It can (optionally) embed an expert Agent into any MCP server
Whether you wrote the MCP server or GitHub did, FastMCP Agents can "wrap" any MCP server.
How do I use it?
Follow our quickstart guide to get started.
Why Agents as Tools?
Bad Tools make bad Agents
Every MCP Server has a set of tools. It's up to the AI Agent to figure out, based on the provided names, descriptions, and arguments for the tools, how to leverage them to solve the user's question. When there's a problem with the instructions, the AI Agent's performance suffers.
Generic Tools are Bad Tools
With MCP, you run around and hook in all of these generic Tools to your various AI Agents and you let the AI Agent decide which ones are the right ones. A simple 3 MCP Server workflow can easily have 100+ tools. Each one is a shiny distraction on the path to solving the user's problem. These tools do almost the right thing almost most of the time.
Specialized Tools don't scale
So like me, you decide that your AI Agents shouldn't have 100 tools, they should only know about the exact tools they need to complete the task at hand. So you give up on MCP servers, write all your own tools.
How's it work?!
Simply take your existing MCP Server
"mcp-server-tree-sitter": {
"command": "uvx",
"args": ["mcp-server-tree-sitter"]
}
And wrap it with an Agent:
"mcp-server-tree-sitter": {
"command": "uvx",
"args": [
"fastmcp_agents", "cli",
"agent",
"--name","ask_tree_sitter",
"--description", "Ask the tree-sitter agent to find items in the codebase.",
"--instructions", "You are a helpful assistant that provides users a simple way to find items in their codebase.",
"wrap",
"uvx", "mcp-server-tree-sitter"
]
}
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