
AI Workbench MCP
io.github.alptugharunv0.1.0a1更新于 Oct 3, 2026
Read-only MCP server for reusable AI prompts and assistant blueprints.
概览
一个只读的本地 MCP 服务器,用于列出、渲染并返回内置的 AI 提示词模板和助手蓝图。
- 功能
- 它通过 stdio 提供三个只读工具:list_prompts 列出内置的提示词模板和助手蓝图,render_prompt 用显式字符串变量填充内置模板,get_assistant 返回一个适用于 ChatGPT、Claude、Gemini、Grok 或可移植 Agent Skill 格式的助手蓝图。目录是本地内置的;服务器不发起网络请求、不执行 shell 命令,也不写入文件。
- 适用场景
- 当你希望助手从一个小型、可检查的本地目录中获取可复用的提示词或助手蓝图,而不是手动粘贴时,适合添加。它适合偏好只读、无需账户或外部服务的窄工具面的用户。
- 运行要求
- 需要本地 Python 运行时;该包以 alptugharun-ai-workbench-mcp 发布在 PyPI 上,可用 uvx 运行或用 pip 安装。需要一个支持 stdio 的 MCP 主机,README 说明其已在 Cursor 上验证,其他客户端可能不同。未声明任何账户、API 密钥、环境变量或请求头。
安装
在 SourceWeft 中
- 打开 控制台中的 AI Workbench MCP,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
AI Workbench MCP
[CI] [CodeQL] [OpenSSF Scorecard]
A tiny, read-only MCP server for reusable AI prompts and assistant blueprints.
[MCP read-only] [Python 3.10+] [Dependency-free runtime] [MIT]
AI Workbench MCP exposes a small local catalog over Model Context Protocol stdio. It is intentionally boring in the best way: no network calls, no shell execution, no account access, no file writes, no hidden provider request.
It gives an MCP host three tools:
Why this exists
A lot of AI repos jump straight from "here is a prompt" to "this is an agent." I wanted a smaller boundary that is easy to inspect.
The server keeps the useful parts local and makes its limits obvious:
- read-only tool contracts;
- explicit MCP trust hints;
- bounded input sizes;
- strict top-level schemas;
- no runtime dependencies outside the Python standard library;
- real stdio handshake tests;
- named tests for every public tool.
Quick start
Install the published alpha package:
Then point a stdio-capable MCP host at the server:
Launch command:
This repository documents the stdio server itself. For the host we have actually exercised, use the copy/paste Cursor setup and 3-tool verification guide. Other MCP clients can differ, so use their current documentation rather than assuming Cursor's configuration is portable.
Security model
Every public tool declares:
The implementation does not import HTTP clients, subprocess modules, filesystem-write helpers, browser libraries, or provider SDKs.
That does not mean "trust any MCP server." It means this repository keeps its own boundary narrow and testable.
Verify it yourself
CI runs the package and protocol tests on Linux and Windows.
Package / registry status
PyPI: alptugharun-ai-workbench-mcp==0.1.0a1 is published through GitHub OIDC Trusted Publishing. The release workflow also signs the wheel with keyless Sigstore.
A clean Windows virtual environment installed the exact PyPI version successfully, negotiated MCP protocol 2025-06-18, listed all three tools, completed successful render_prompt and get_assistant calls, and returned a bounded error for an unknown tool.
Official MCP Registry: io.github.alptugharun/ai-workbench-mcp is published and currently reports active in the production registry.
Real-host verification: a maintainer-run Cursor 3.20.21 session invoked list_prompts, render_prompt and get_assistant successfully against the published package. This is host evidence, not an independent third-party endorsement or a universal compatibility claim.
See REGISTRY-PUBLISHING.md and HOST-VERIFICATION.md.
Contributing
Small, reproducible improvements are welcome. The most useful contributions right now are:
- real MCP host verification;
- protocol edge-case tests;
- clearer failure messages;
- documentation corrections;
- narrowly scoped catalog improvements.
Please read CONTRIBUTING.md before opening a PR.
Origin
This project was extracted from AI Social Media Toolkit so the MCP server can evolve as a focused product instead of being buried inside a larger creator/AI repository.
Built by Alptuğ Harun.
License
MIT — see LICENSE.
来源:README.md,提交 4f97463
工具
0版本历史
1- v0.1.0a1最新Oct 3, 2026
