MCP server for brutal, evidence-based screenplay analysis via retrieval over a reference database of real scripts.
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<div align="center"> # 🎬 slugline-mcp ### Brutal, evidence-based screenplay analysis — grounded in real produced scripts. **Mood, next-action suggestions, and "X meets Y" comparisons, backed by retrieval over ~2,200 real screenplays. One MCP server. Zero vibes-based feedback.** **Under the hood: a full Retrieval-Augmented Generation (RAG) pipeline — chunking, vector embeddings, semantic search, and local zero-shot classification — exposed entirely as Model Context Protocol (MCP) tools, with zero LLM calls from the server itself.** slugline-mcp doesn't write or judge your scene itself — it retrieves real produced scenes similar to yours (or matching a mood you're chasing) so *your own* connected Claude can ground its feedback in evidence instead of guessing. It's the *retrieval* half of RAG, full stop: parse, embed, index, and semantically search real screenplays, then hand that grounded evidence to Claude over MCP. [](https://pypi.org/project/slugline-mcp/) [](#-how-the-rag-pipeline-works) [](https://www.python.org/) [](https://modelcontextprotocol.io) [](LICENSE) [](https://github.com/NalluriTanavreddy/slugline-mcp/stargazers) ⭐ Star this repo if you find it useful. </div> --- > **Try it:** > > - 📦 **Install it** — `uvx slugline-mcp` (or `uv pip install slugline-mcp`), published on > [PyPI](https://pypi.org/project/slugline-mcp/) > - 🔌 **Add it to Claude Desktop** — see [`docs/claude_desktop.md`](docs/claude_desktop.md) for the config > - 🎬 **Ask about your scene**…
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