agent-project
Agent 早期探索：智能路由、任务拆解和链路工程
Install / Use
claude mcp add luochang212 -- npx -y github:luochang212/agent-projectIf the server publishes to npm under a different name, use that package instead — check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
AI & Machine LearningSupported Platforms
Tags
Our assessment of agent-project
agent-project scores 51/100 on our quality scale, 933rd of 963 AI & Machine Learning skills we index.
Its MCP Server is 2.4 KB long, well organised into 10 sections with 2 code examples: moderately detailed.
It has 10 GitHub stars, so there is little community track record yet; judge it on its content.
Maintenance, license and trust
- The repository was last updated about 17 months ago. Expect some instructions to reference tool versions or APIs that have since changed.
- Our last check on 2026-10-21 found the source still online.
- No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
- Its trust signals score 68/100, with 3 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-09-24. Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
agent-project compared with similar skills
All 4 of these similar skills score higher than agent-project; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| agent-project (this skill)by luochang212 | 51 | 10 | 17mo ago | MCP Server |
| claude-memby thedotmack | 100 | 113.6k | today | CLAUDE.md |
| Agent-Reachby Panniantong | 100 | 109.3k | today | CLAUDE.md |
| Understand-Anythingby Egonex-AI | 100 | 91.0k | 10d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 79.0k | today | CLAUDE.md |
Frequently asked questions
- How do I install agent-project?
- Run
claude mcp add luochang212 -- npx -y github:luochang212/agent-project. The install tabs above show the steps for each supported agent. - Which AI agents does agent-project work with?
- It is written for Claude Code and Claude Desktop, as a MCP Server file. Other agents that read the same format can often use it too.
- Is agent-project safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It declares no license and scores 68/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is agent-project still maintained?
- The repository was last updated about 17 months ago. Expect some instructions to reference tool versions or APIs that have since changed.
Skill content
View source on GitHubagent-project
Agent 实战
一、技术栈
- 前端:
Gradio - 后端:
Qwen Agent - 数据库:
PostgreSQL/MySQL - MCP:
server-postgres/mysql-mcp-server
二、正式项目
三、配置文件
LLM 和 数据库 配置在 .env 文件中，按律不上传。它的格式如下：
DB_HOST=localhost
DB_PORT=5432
DB_NAME=ecommerce_orders
DB_USER=admin
DB_PASSWORD=admin-password
Note: 请在项目根目录下创建
.env文件
四、本地运行
前置步骤：
- 启动本地 LLM 服务，或者配置服务商的 API_KEY
- 安装 & 构造 Postgres 样例数据
启动 Gradio：
# 简单的聊天 APP，无 SQL 查询功能
python gradio_app.py
# [Agent] 简单查询，无定制工作流
python gradio_postgres_agent.py
# [Workflow] 定制工作流，可以降低错误率，但查询速度较慢
python gradio_postgres_workflow.py
启动后，打开浏览器访问 http://localhost:7860/
如果你用了我的样例数据，可以用以下问题测试：
- 数据库中有哪些表
- 订单表中随便取几条uid我看看
- uid为104的用户有哪些订单
- 查询一下订单1004的物流状态
- 查询uid为104的用户的所有订单的物流状态
五、预研计划
MCP 只是 LLMs 生态中的一环，实现 MCP 需要多种前置服务的支持（比如 vLLM, LangChain）。为了事先了解这些可能我也很陌生的服务，我必须像 Agent 一样，将任务拆分成多个子任务，再逐个进行预研。
本仓库的预研项目如下：
- Qwen3 推理脚本 (/test_qwen3):
- 基于 vLLM 开发 qwen3 大模型推理服务
- 基于 Ollama 开发 bge-m3 文本 embedding 推理服务
- 简单的 RAG (/test_rag):
- 基于 LangChain 开发 RAG
- 开发 bge-m3 推理服务
- 使用 chroma 作为向量数据库
- 简单的 Qwen Agent (/test_qwen_agent):
- 对 SQLite 进行 CRUD 操作
- 对 Redis 进行 CRUD 操作
- 查询 PostgreSQL 数据库
- 查询 MySQL 数据库
- 使用 Qwen Agent 调用 FastAPI
- 运行模型编排 Demo
- 简单的 OpenAI Agent (/test_openai_agent):
- 使用
chat_completionsAPI 连接本地 vLLM 服务 - 开发 Function Calling 示例
- 开发 MCP 示例（SSE 方法）
- 开发 Handoffs 示例
- 开发 Central Agent 示例
- 使用
[!NOTE] 预研项目存放在以
test_前缀命名的文件夹中。
六、开发日志
- [x] intelligent_routing Python Package
- [x] Postgres / MySQL 数据库元数据查询工具
- [x] Postgres / MySQL Qwen Agent 函数调用 Function Calling
- [x] Postgres / MySQL 带查询功能的简单 Agent（非流式输出）
- [x] Postgres / MySQL 用于优化查询的工作流
- [x] gradio_ui 定义 WebUI 样式
- [x] gradio_app 简单的 LLM Chat APP（流式输出）
- [x] gradio_postgres_agent Postgres APP（流式输出）
- [x] gradio_postgres_workflow Postgres Workflow APP（流式输出）
Related Skills
claude-mem
113.6kPersistent Context Across Sessions for Every Agent – Captures everything your agent does during sessions, compresses it with AI, and injects relevant context back into future sessions. Works with Claude Code, OpenClaw, Codex, Gemini, Hermes, Copilot, OpenCode + More
Agent-Reach
109.3kGive your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.
Understand-Anything
91.0kGraphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
headroom
79.0kCompress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.
Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.