
AI Workbench MCP
io.github.alptugharunv0.1.0a1更新於 Oct 3, 2026
Read-only MCP server for reusable AI prompts and assistant blueprints.
概覽
一個唯讀的本機 MCP 伺服器,用來列出、渲染並回傳內建的 AI 提示詞範本與助理藍圖。
- 功能
- 它透過 stdio 提供三個唯讀工具:list_prompts 列出內建的提示詞範本與助理藍圖,render_prompt 以明確的字串變數填入內建範本,get_assistant 回傳一個適用於 ChatGPT、Claude、Gemini、Grok 或可攜式 Agent Skill 格式的助理藍圖。目錄是本機內建的;伺服器不發出網路請求、不執行 shell 指令,也不寫入檔案。
- 適用情境
- 當你希望助理從一個小型、可檢查的本機目錄取得可重複使用的提示詞或助理藍圖,而不是手動貼上時,適合加入。它適合偏好唯讀、不需要帳號或外部服務的窄工具介面的使用者。
- 執行需求
- 需要本機 Python 執行環境;此套件以 alptugharun-ai-workbench-mcp 發佈於 PyPI,可用 uvx 執行或以 pip 安裝。需要支援 stdio 的 MCP 主機,README 說明已在 Cursor 上驗證,其他用戶端可能不同。未宣告任何帳號、API 金鑰、環境變數或標頭。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 AI Workbench MCP,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
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.
來源:README.md,提交 4f97463
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1- v0.1.0a1最新Oct 3, 2026


