Dependency-free, read-only MCP server for reusable AI prompts and assistant blueprints.
- ✓Open-source license (MIT)
- ✓Actively maintained (<30d)
- ✓Clear description
- ✓Topics declared
- ✓Documented (README)
claude mcp add ai-workbench-mcp -- python -m ai-workbench-mcp{
"mcpServers": {
"ai-workbench-mcp": {
"command": "python",
"args": ["-m", "pip"]
}
}
}Resumen de MCP Servers
# AI Workbench MCP
[](https://github.com/alptugharun/ai-workbench-mcp/actions/workflows/ci.yml)
[](https://github.com/alptugharun/ai-workbench-mcp/actions/workflows/codeql.yml)
[](https://scorecard.dev/viewer/?uri=github.com/alptugharun/ai-workbench-mcp)
<!-- mcp-name: io.github.alptugharun/ai-workbench-mcp -->
[](README.md) [](README_TR.md)
<p align="center">
<strong>A tiny, read-only MCP server for reusable AI prompts and assistant blueprints.</strong>
</p>
<p align="center">
<img src="https://img.shields.io/badge/MCP-read--only-111827?style=for-the-badge" alt="MCP read-only">
<img src="https://img.shields.io/badge/Python-3.10%2B-3776AB?style=for-the-badge&logo=python&logoColor=white" alt="Python 3.10+">
<img src="https://img.shields.io/badge/runtime-dependency--free-16A34A?style=for-the-badge" alt="Dependency-free runtime">
<img src="https://img.shields.io/badge/license-MIT-2563EB?style=for-the-badge" alt="MIT">
</p>
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:
| Tool | Result |
| --- | --- |
| `list_prompts` | Lists the bundled prompt templates and assistant blueprints |
| `render_prompt` | Fills a bundled prompt template with explicit string variables |
| `get_assistant` | Returns one assistant blueprint for ChatGPT, Claude, Gemini, Grok, or portable Agent Skill format |
## 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:
```bash
python -m pip install "alptugharun-ai-workbench-mcp==0.1.0a1"
```
Then point a stdio-capable MCP host at the server:
Launch command:
```text
alptugharun-ai-workbench-mcp
```
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](CURSOR-SETUP.md). Other MCP clients can differ, so use their current documentation rather than assuming Cursor's configuration is portable.
## Security model
Every public tool declares:
```json
{
"readOnlyHint": true,
"destructiveHint": false,
"idempotentHint": true,
"openWorldHint": false
}
```
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
```bash
python -m unittest discover -s tests -v
python examples/smoke_client.py
```
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](REGISTRY-PUBLISHING.md) and [HOST-VERIFICATION.md](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](CONTRIBUTING.md) before opening a PR.
## Origin
This project was extracted from [AI Social Media Toolkit](https://github.com/alptugharun/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](LICENSE).
Lo que la gente pregunta sobre ai-workbench-mcp
¿Qué es alptugharun/ai-workbench-mcp?
+
alptugharun/ai-workbench-mcp es mcp servers para el ecosistema de Claude AI. Dependency-free, read-only MCP server for reusable AI prompts and assistant blueprints. Tiene 1 estrellas en GitHub y su última actualización registrada es del 2026-10-03.
¿Cómo se instala ai-workbench-mcp?
+
Puedes instalar ai-workbench-mcp clonando el repositorio (https://github.com/alptugharun/ai-workbench-mcp) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.
¿Es seguro usar alptugharun/ai-workbench-mcp?
+
Nuestro agente de seguridad ha analizado alptugharun/ai-workbench-mcp y le ha asignado un Trust Score de 95/100 (tier: Verified). Revisa el desglose completo de comprobaciones superadas y flags en esta página.
¿Quién mantiene alptugharun/ai-workbench-mcp?
+
alptugharun/ai-workbench-mcp es mantenido por alptugharun. La última actividad registrada en GitHub es del 2026-10-03, con 1 issues abiertos.
¿Hay alternativas a ai-workbench-mcp?
+
Sí. En ClaudeWave puedes explorar mcp servers similares en /categories/mcp, ordenados por popularidad o actividad reciente.
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