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Fastmcp Learning Demo

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Scored 5 months ago · breakdown

About Fastmcp Learning Demo

Fastmcp Learning Demo is an MCP server published by ZackX1014 in the Documentation category.

Recent commit activity is the strongest signal that reported issues will get attention.

Install

From source
git clone https://github.com/ZackX1014/fastmcp-learning-demo

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Tools (3)

Client / Workflow串联能力的调用方和流程控制器

Parameters not published.

Prompt可复用的 AI 指令模板

Parameters not published.

Resource可读取的上下文资料

Parameters not published.

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README

fastmcp-learning-demo

Project Overview

fastmcp-learning-demo 是一个独立的 FastMCP / MCP 学习项目。

它通过一组小 Demo,学习 MCP Server、Tool、Client、HTTP Transport、Resource、Prompt 和简单 Workflow。

这是学习项目,不是生产系统。

项目不接入真实 LLM,不接入真实 QuoteAgent,不使用数据库,也不做部署配置。

Learning Goals

本项目用于学习:

  • FastMCP Server
  • MCP Tool
  • MCP Client
  • HTTP Transport
  • CLI inspect / list
  • MCP Resource
  • MCP Prompt
  • Tool + Resource + Prompt workflow
  • QuoteAgent-style simulated workflow

What This Project Demonstrates

当前已完成的 Demo:

  • hello Tool:最小 Tool 示例。
  • calculate_quote_price Tool:本地假价格规则的报价计算。
  • Error handling demo:演示错误参数调用和结构化错误返回。
  • project://summary Resource:只读项目摘要。
  • analyze_quote_request Prompt:报价需求分析提示模板。
  • Resource → Prompt → Tool workflow demo:组合 MCP 能力的模拟 Agent 流程。
  • QuoteAgent-style simulation demo:完整与不完整报价请求的模拟处理流程。

Project Structure

fastmcp-learning-demo/
  src/
    server.py
    client.py
    client_error_demo.py
    client_resource_demo.py
    client_prompt_demo.py
    client_agent_workflow_demo.py
    client_quote_agent_simulation_demo.py

  docs/
    context/      项目事实和边界
    guides/       环境与验证指南
    rules/        Tool 设计和错误处理规则
    learning/     按步骤整理的学习笔记
    logs/         简洁开发记录

Environment

本项目使用:

  • Python 3.12
  • uv
  • FastMCP
  • MCP

约定:

  • 使用 pyproject.toml 管理依赖。
  • 使用 uv.lock 锁定依赖版本。
  • 不使用全局 pip install。
  • 不创建 requirements.txt。
  • 不使用 Docker。

详细环境说明见:

docs/guides/ENVIRONMENT.md

How to Run

1. 检查环境

uv run fastmcp version

2. 启动 Server

uv run python src/server.py

Server 地址:

http://127.0.0.1:8000/mcp

3. 运行 Demo Client

另开一个终端运行:

uv run python src/client.py
uv run python src/client_error_demo.py
uv run python src/client_resource_demo.py
uv run python src/client_prompt_demo.py
uv run python src/client_agent_workflow_demo.py
uv run python src/client_quote_agent_simulation_demo.py

4. CLI 检查

uv run fastmcp inspect src/server.py
uv run fastmcp list src/server.py

更完整的验证说明见:

docs/guides/TESTING.md

MCP Concepts in This Project

概念 可以理解为 本项目例子
Tool 可调用的动作 calculate_quote_price
Resource 可读取的上下文资料 project://summary
Prompt 可复用的 AI 指令模板 analyze_quote_request
Client / Workflow 串联能力的调用方和流程控制器 client_quote_agent_simulation_demo.py

简单记法:

  • Tool 负责做事。
  • Resource 负责提供资料。
  • Prompt 负责提供分析指令。
  • Client / Workflow 负责把它们按顺序用起来。

Relationship to QuoteAgent

本项目借用了 QuoteAgent 风格的报价业务场景。

但它只是本地学习 Demo:

  • 不接入真实 QuoteAgent。
  • 不调用 ASP.NET Core API。
  • 不读取真实邮箱。
  • 不连接数据库。
  • 不接入真实 LLM。

QuoteAgent 风格 Demo 的目的,是帮助理解 MCP 能力如何服务业务 Agent 工作流。

Documentation Map

  • docs/context/PROJECT_CONTEXT.md:项目事实、目标和边界。
  • docs/guides/ENVIRONMENT.md:uv、Python 和依赖管理说明。
  • docs/guides/TESTING.md:环境、CLI 和各 Demo 的验证命令。
  • docs/rules/MCP_TOOL_DESIGN.md:Tool 设计规则。
  • docs/rules/ERROR_HANDLING.md:错误处理规则。
  • docs/learning/:按步骤整理的学习笔记。
  • docs/logs/DEV_LOG.md:简洁开发记录。

Project Status

当前项目已完成 Step 0 到 Step 10。

  • Step 0:项目初始化。
  • Step 1-8:FastMCP / MCP 核心 Demo。
  • Step 9:CLI inspect / list / 测试与文档整理。
  • Step 10:项目总结与 README 优化。

Notes / Boundaries

  • This is not a production system.
  • This project does not use a real LLM.
  • This project does not connect to a real QuoteAgent system.
  • This project does not use a database.
  • This project does not provide a Web API.
  • This project focuses on learning MCP concepts through small demos.

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About Fastmcp Learning Demo

How do I install Fastmcp Learning Demo?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Fastmcp Learning Demo safe to use with an AI agent?

Its trust score is 30 out of 100 (low). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Fastmcp Learning Demo still maintained?

Yes — the last commit was 5 months ago. The repository has 0 stars and 0 forks.