Scrivener MCP

Scrivener MCP

MCP server for Scrivener: connect your novels, screenplays, and manuscripts to Claude, ChatGPT, and any AI assistant, with document management, writing analysis, content enhancement, offline semantic search, and character/plot tracking.

Install · What You Can Do · All Tools · Guides · Contributing

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Scrivener MCP lets your AI assistant open, read, edit, analyze, and search your Scrivener projects directly. No exporting, no copy-pasting text back and forth. Tell it which project to open and start working.

You: Open my novel and analyze the pacing in Chapter 12.

Claude: Opens the .scriv project, reads Chapter 12, runs pacing analysis. The first half moves well, but the middle stalls — a three-page internal monologue starting at paragraph 14 kills the momentum you built in the confrontation scene. Consider cutting it to a paragraph and moving the backstory to Chapter 8.

Works with Claude Desktop, Claude Code, VS Code (Copilot/Continue), Cursor, and any MCP-compatible client. Scrivener 3 on macOS, Windows, and Linux. Listed on the official MCP Registry as io.github.writerslogic/scrivener-mcp.

Install

npm install -g scrivener-mcp

Restart Claude Desktop and it's ready. Other clients need one more step:

npx scrivener-setup

This finds Claude Code, Claude Desktop, and Cursor and configures them for you. To set up Claude Code by hand instead: claude mcp add -s user scrivener -- npx scrivener-mcp, then restart it (or run /mcp).

Other ways to install

Smithery

npx -y @smithery/cli install scrivener-mcp --client claude

npx, no install

npx scrivener-mcp

or add it to Claude Desktop's config directly:

{
  "mcpServers": {
    "scrivener": { "command": "npx", "args": ["scrivener-mcp"] }
  }
}

From GitHub

npm install -g writerslogic/scrivener-mcp              # latest main
npm install -g writerslogic/scrivener-mcp#v0.12.0       # a specific release

Homebrew (macOS)

brew install writerslogic/tap/scrivener-mcp

Docker

docker build -t scrivener-mcp https://github.com/writerslogic/scrivener-mcp.git
docker run -i --rm -v /path/to/your/projects:/projects scrivener-mcp

Any other MCP client: point it at npx scrivener-mcp as a stdio server.

Optional: AI-powered features

Document management, deterministic analysis, keyword search, and project memory work with no API key at all. Writing analysis, generation, enhancement, and semantic search need one — Anthropic, OpenAI, or OpenRouter. Set more than one and Claude handles chat by default; override with AI_PROVIDER=openai or AI_PROVIDER=openrouter (OpenRouter defaults to anthropic/claude-sonnet-4.6, change it with OPENROUTER_MODEL). If the active provider fails on an account-level error — bad key, no credit, an outage — the server retries on the next one you've configured. If your MCP client supports sampling, chat-based features can run through the client's own model instead, no separate key needed. Semantic indexing itself always runs locally through the Holographic Memory System; only semantic_search's query interpretation needs a provider.