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ClaudeWave

Dependency-free, read-only MCP server for reusable AI prompts and assistant blueprints.

MCP ServersOfficial Registry1 stars0 forks● PythonMITUpdated today
ClaudeWave Trust Score
95/100
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Passed
  • ✓Open-source license (MIT)
  • ✓Actively maintained (<30d)
  • ✓Clear description
  • ✓Topics declared
  • ✓Documented (README)
Last scanned: 10/4/2026
Install in Claude Code / Claude Desktop
Method: pip / Python
Claude Code CLI
claude mcp add ai-workbench-mcp -- python -m ai-workbench-mcp
claude_desktop_config.json (Claude Desktop)
{
  "mcpServers": {
    "ai-workbench-mcp": {
      "command": "python",
      "args": ["-m", "pip"]
    }
  }
}
1. Run the command above in your terminal (Claude Code), or paste the JSON config into claude_desktop_config.json (Claude Desktop).
2. Replace any <placeholder> values with your API keys or paths.
3. Restart Claude. The MCP server and its tools appear automatically.
Use cases

MCP Servers overview

# AI Workbench MCP

[![CI](https://github.com/alptugharun/ai-workbench-mcp/actions/workflows/ci.yml/badge.svg)](https://github.com/alptugharun/ai-workbench-mcp/actions/workflows/ci.yml)
[![CodeQL](https://github.com/alptugharun/ai-workbench-mcp/actions/workflows/codeql.yml/badge.svg)](https://github.com/alptugharun/ai-workbench-mcp/actions/workflows/codeql.yml)
[![OpenSSF Scorecard](https://api.scorecard.dev/projects/github.com/alptugharun/ai-workbench-mcp/badge)](https://scorecard.dev/viewer/?uri=github.com/alptugharun/ai-workbench-mcp)

<!-- mcp-name: io.github.alptugharun/ai-workbench-mcp -->

[![English](https://img.shields.io/badge/English-0D1117?style=flat-square)](README.md) [![Türkçe](https://img.shields.io/badge/Türkçe-E30A17?style=flat-square)](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).
agent-toolsaimcpmodel-context-protocolpython

What people ask about ai-workbench-mcp

What is alptugharun/ai-workbench-mcp?

+

alptugharun/ai-workbench-mcp is mcp servers for the Claude AI ecosystem. Dependency-free, read-only MCP server for reusable AI prompts and assistant blueprints. It has 1 GitHub stars and its last recorded update is dated 2026-10-03.

How do I install ai-workbench-mcp?

+

You can install ai-workbench-mcp by cloning the repository (https://github.com/alptugharun/ai-workbench-mcp) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.

Is alptugharun/ai-workbench-mcp safe to use?

+

Our security agent has analyzed alptugharun/ai-workbench-mcp and assigned a Trust Score of 95/100 (tier: Verified). See the full breakdown of passed checks and flags on this page.

Who maintains alptugharun/ai-workbench-mcp?

+

alptugharun/ai-workbench-mcp is maintained by alptugharun. The last recorded GitHub activity is dated 2026-10-03, with 1 open issues.

Are there alternatives to ai-workbench-mcp?

+

Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.

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