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Try Fastmcp MCP Server

@iAbdelRahim

代码仓库

基本信息

分类

AI 与智能体

传输方式

stdio

作者

iAbdelRahim

关于 Try Fastmcp MCP Server

chat with a llm having access to a mcp server.

#mcp-chat#llm#mcp-server

Try Fastmcp MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp_chat": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "env"
      ]
    }
  }
}

Try Fastmcp MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is try_fastmcp?

try_fastmcp is a Python application that uses the FastMCP library to create an MCP server. It integrates with the OpenAI API and provides tools for dataset retrieval, news search, and mathematical operations, as well as a greeting resource. It is intended for developers who need a lightweight MCP server with these capabilities.

How to use try_fastmcp?

Clone the repository, create and activate a virtual environment, install dependencies with pip install -r requirements.txt, and set your OpenAI API key in the .env file. Run the server with python server.py and the client with streamlit run client.py.

Key features of try_fastmcp?

  • Retrieve all public datasets from data.gouv.ci catalog.
  • Fetch news articles based on user queries.
  • Perform 13 mathematical operations (add, subtract, multiply, divide, etc.)
  • Generate personalized greetings via a resource endpoint.
  • Uses FastMCP library and OpenAI API.

Use cases of try_fastmcp?

  • Automating dataset discovery from a government open data portal.
  • Performing quick arithmetic or scientific calculations through an MCP tool.
  • Integrating news search into a larger AI‑powered workflow.
  • Demonstrating how to build and run a FastMCP server with Python.

常见问题

1

What Python version is required?

Python 3.6 or higher is required.

2

How do I set the OpenAI API key?

Rename the `.env.example` file to `.env` and fill in your `OPENAI_API_KEY`.

3

What tools does the server provide?

It provides `get_all_datasets`, `websearch_newssearch`, and 11 math tools (add, subtract, multiply, divide, power, sqrt, cbrt, factorial, log, remainder, sin, cos, tan).

4

How do I run the client?

Execute `streamlit run client.py` in the activated virtual environment.

5

What is the greeting resource?

The resource `greeting://{name}` returns a personalized greeting for the given name.

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