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

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

Claude: Opens your .scriv project, reads Chapter 12, runs pacing analysis. The first half moves well with short, tense paragraphs. The middle section slows considerably -- the three-page internal monologue starting at paragraph 14 stalls the momentum you built in the confrontation scene. Consider cutting it to a single paragraph and moving the backstory to Chapter 8 where Elena is first introduced.

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

Pick the method that works for you. Most auto-configure Claude Desktop on install. Claude Code and other clients need one extra step -- see Claude Code below.

npm (recommended)

npm install -g scrivener-mcp

Restart Claude Desktop. Done.

Claude Code

Installing the npm package does not register the server with Claude Code -- the install-time auto-config only writes Claude Desktop's config. After installing, register the server:

npx scrivener-setup

This detects Claude Code (along with Claude Desktop and Cursor) and writes the config for you. To register it manually instead:

claude mcp add -s user scrivener -- npx scrivener-mcp

Then restart Claude Code (or run /mcp to reconnect) and Scrivener MCP appears in the server list. Drop -s user to scope it to the current project instead of all projects.

Smithery

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

npx (no install)

Use directly without installing globally:

npx scrivener-mcp

Or add to your Claude Desktop config manually:

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

GitHub

Install directly from the repo (latest main):

npm install -g writerslogic/scrivener-mcp

Or a specific release:

npm install -g writerslogic/scrivener-mcp#v0.5.1

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

Run the interactive setup to auto-detect and configure your client:

npx scrivener-setup

This detects Claude Desktop, Claude Code, and Cursor, and writes the config for you.

For other MCP clients, point them at npx scrivener-mcp as a stdio server.

Core features (document management, analysis, search) work without any API key. AI-powered enhancements work with an Anthropic (Claude), OpenAI, or OpenRouter key; when several are present, Claude handles chat and generation (set AI_PROVIDER=openai or AI_PROVIDER=openrouter to override). OpenRouter defaults to the anthropic/claude-sonnet-4.6 model; set OPENROUTER_MODEL to use any model in its catalog. If the active provider fails with an account-level error (invalid key, exhausted credit, outage), the server automatically retries the request on the next configured provider. When your MCP client supports the sampling capability, chat-based AI features can also run through the client's own model — with no API key at all. Semantic/embedding features need an OpenAI or OpenRouter key (embeddings run through OpenAI models either way). The server automatically discovers keys from common locations:

• ANTHROPIC_API_KEY / OPENAI_API_KEY / OPENROUTER_API_KEY environment variables
• ~/.env, ~/.scrivener-mcp/.env
• ~/.anthropic/key, ~/.openai/key, ~/.openrouter/key
• macOS Keychain (service names anthropic-api-key / openai-api-key / openrouter-api-key)

To store a key in the macOS Keychain:

security add-generic-password -s anthropic-api-key -a anthropic -w sk-ant-your-key-here

Or export it manually:

export ANTHROPIC_API_KEY="sk-ant-..."   # or OPENAI_API_KEY="sk-..."

This enables: content enhancement, semantic search, multi-agent analysis, character consistency checking, and intelligent compilation.

What You Can Do

First, open a project. The server acts on whatever .scriv project you point it at -- it has no link to the Scrivener app and can't see what you have open there. Start a conversation with "Open my Scrivener project at ~/Documents/My Novel.scriv" (or "Discover my Scrivener projects" if you don't know the path), then give your commands. On macOS you can also just say "Use the project I have open in Scrivener" -- it detects the open project and opens it (the first time, macOS asks you to allow controlling Scrivener). Do this once at the start of each conversation; the examples below all assume a project is open. If the same project is also open and unsaved in the Scrivener app, save or close it there first to avoid conflicting writes.

Manage Your Manuscript

Open any Scrivener project and work with it naturally. Read chapters, create new scenes, reorganize the binder, update synopses -- all through conversation.

You: Create a new scene called "The Reveal" after Chapter 5, and move the old epilogue to the trash.

Analyze Your Writing

Get detailed feedback on readability, pacing, style, dialogue quality, and emotional arc. Not generic advice -- analysis grounded in your actual prose.

You: Analyze Chapter 3. Is the pacing too slow?

Claude: Readability is good (Flesch-Kincaid grade 8.2), but pacing flags:

• 4 consecutive paragraphs of internal monologue (lines 45-78) with no action or dialogue
• The scene is 3,200 words with only 2 scene breaks -- your other chapters average 4
• Filter word density is 2x your manuscript average ("felt", "seemed", "noticed") Specific suggestions: ...

Enhance Your Prose

Apply targeted improvements: eliminate filter words, strengthen verbs, vary sentence structure, add sensory details, convert telling to showing, tighten dialogue, adjust pacing.

You: Eliminate the filter words in Chapter 7 and strengthen the verbs.

Track Characters and Plot

Store character profiles, plot threads, and style guides that persist with your project. The AI remembers your characters across sessions.

You: Save a character profile for Marcus: retired detective, cynical but fair, walks with a limp from an old injury, speaks in clipped sentences.

Later...

You: Check if Marcus is consistent across all chapters.

Claude: Found an inconsistency: Marcus walks "briskly" in Chapter 9 (line 34), but his limp is referenced in Chapters 2, 5, and 11. Also, his dialogue in Chapter 4 uses long flowing sentences, which contradicts the "clipped sentences" note in his profile.

Search by Meaning

Find passages by what they're about, not just keyword matching. "Find scenes where the protagonist feels isolated" works even if the word "isolated" never appears. Powered by the Holographic Memory System -- works offline, no API key needed.

You: Find all scenes where Elena and Marcus are alone together.

Track Relationships

Store and query relationships between characters, locations, themes, and plot threads. No Neo4j required -- relationships live in the semantic memory engine and persist with your project.

You: Who is connected to Marcus? What plot threads involve the lighthouse?

Compile and Export

Combine chapters into a single manuscript with configurable formatting, separators, and structure preservation. Export the result inline as Markdown, HTML, or JSON, or write a DOCX, EPUB, or PDF file to disk for submission, e-readers, or print.

All Tools

57 tools organized by workflow. To keep token usage low, tools load progressively -- project tools at startup, document and search tools when you open a project, and the rest on demand (your AI client activates them automatically, or calls them directly and the owning skill activates on the fly). Set SCRIVENER_MCP_EAGER_TOOLS=1 to load everything at once.

| Tool | What it does | |------|-------------| | open_project | Open a .scriv project (accepts .scriv folders or .scrivx files) and make it active | | discover_projects | Scan common locations for Scrivener projects when you don't know the path | | detect_open_project | Detect the project currently open in the Scrivener app (macOS) so you don't need a path | | get_structure | Browse the binder hierarchy (folders, documents, word counts) | | refresh_project | Reload from disk after external edits | | close_project | Close the active project and flush pending changes | | verify_project_integrity | Read-only scan for structural problems (missing/duplicate UUIDs, unreadable content) | | get_compile_settings | Read the project's compile formats and taxonomy -- labels/statuses (with colors), collections, section types | | get_manuscript_briefing | One "where am I?" snapshot: words vs. target (% to goal), document/status/label counts, longest/shortest documents | | list_snapshots | List Scrivener snapshots (title, date) for one document or the whole project | | read_snapshot | Read a snapshot's text as plain text, with word count | | compare_snapshot | Diff a snapshot against the current document (or another snapshot): paragraphs added/removed and net word change | | create_snapshot | Take a Scrivener-native snapshot of a document (restorable from Scrivener's own Snapshots browser) before editing |

| Tool | What it does | |------|-------------| | get_document_info | Metadata for one document (title, type, word count, synopsis, label, status) | | read_document | Read content; format: "formatted" for rich text, offset/limit to page long docs | | write_document | Replace a document's content (atomic, with pre-write backup) | | create_document | Create a new text document or folder | | update_document | Change title and/or metadata (synopsis, notes, label, status, custom fields) | | move_document | Reorganize within the binder | | delete_document | Move to trash (reversible) |

| Tool | What it does | |------|-------------| | search | Keyword/full-text search; field: "title" for titles, scope: "trash" for trash | | semantic_search | Find passages by meaning using embeddings, with similarity scores | | find_mentions | Locate every occurrence of a specific name or term, with context | | list_trash | List trashed documents | | restore_document | Restore a document from trash | | read_annotations | Read a document's comments and footnotes |

| Tool | What it does | |------|-------------| | analyze_document | AI writing analysis; focus with aspects (structure, style, pacing, themes...) | | check_consistency | Project-wide continuity check; scope for plot, characters, or timeline | | analyze_writing_style | Style-focused analysis | | check_plot_consistency | Plot-thread consistency check | | suggest_improvements | AI-generated improvement suggestions | | enhance_content | Suggest a specific improvement to a document | | generate_content | Generate new prose from a prompt and context | | set_writing_goal | Set a word-count goal (daily, weekly, or whole project) with an optional target date | | get_writing_goals | List goals with progress -- percent complete, words remaining, on-pace status | | set_writing_preferences | Set author preferences (tone, complexity, length, POV, style guide) that steer AI output | | get_writing_preferences | Show current preferences plus feedback insights and suggestions | | collect_feedback | Record a rating/comment on an AI operation to inform those insights |

Enhancement types: eliminate-filter-words, strengthen-verbs, vary-sentences, add-sensory-details, show-dont-tell, improve-flow, enhance-descriptions, strengthen-dialogue, fix-pacing, expand, condense, rewrite

| Tool | What it does | |------|-------------| | compile_documents | Combine documents; mode: "structured" compiles the Draft folder with the binder hierarchy as headings and honors "Include in Compile" (no AI), mode: "intelligent" for AI-optimized output | | export_project | Write the manuscript to disk -- Markdown, HTML, JSON inline, or DOCX, EPUB, PDF as a file | | get_statistics | Project-level word/document/character counts | | generate_marketing_materials | Draft synopsis, query letter, pitch, and related materials |

| Tool | What it does | |------|-------------| | remember | Store information that persists across sessions with the project | | recall | Retrieve previously stored memory |

Memory is stored within each .scriv project and travels with it.

| Tool | What it does | |------|-------------| | add_relationship | Store a relationship between characters, locations, themes, or plot threads | | find_relationships | Query entities related to a given character/theme/location | | discover_connections | Find co-occurring entities across the manuscript | | character_network | The character relationship network | | get_entity_references | Trace the reference graph in either direction: entities a document mentions (by documentId), or documents mentioning an entity (by entity) | | find_orphaned_entities | List registered characters/locations that no document actually mentions | | suggest_connections | Suggest entities a document may be missing, inferred from cross-document co-occurrence |

Works without Neo4j -- relationships live in the Holographic Memory System and are available immediately. The document cross-reference tools are fully deterministic (exact whole-word matching, no AI) and need no external services; Neo4j adds advanced graph analysis when connected.

| Tool | What it does | |------|-------------| | queue_document_analysis | Enqueue an async analysis of one document; returns a job id | | queue_project_analysis | Enqueue an async analysis of the whole project | | get_job_status | Poll progress/results for a queued job | | cancel_job | Cancel a queued or running job |

| Tool | What it does | |------|-------------| | list_skills | List the available tool groups and their tools | | use_skill | Activate a tool group (most are pre-activated by default) |

Guides

• Getting Started -- Installation, configuration, your first session
• MCP Client Setup -- Copy-paste config for Claude Desktop, Claude Code, Cursor, and VS Code
• Writing with AI -- Analysis workflows, enhancement strategies, memory management
• Troubleshooting -- Common issues and fixes
• Token Optimization -- How the server minimizes context window usage
• Architecture -- How the server works, module structure, data flow
• Scrivener Compatibility -- Supported Scrivener versions, platforms, and format coverage
• Scrivener File Format -- The reverse-engineered .scriv format, what we read vs. infer, and safe-modification guidance
• Contributing -- Development setup, code conventions, adding new tools

Requirements

• Node.js 18+
• Scrivener 3 project files (.scriv)
• macOS, Windows, or Linux
• Optional: Anthropic or OpenAI API key for AI-powered features (OpenAI required for semantic/embedding features)
• Optional: Neo4j for character relationship graphs

Development

git clone https://github.com/writerslogic/scrivener-mcp.git
cd scrivener-mcp
npm install
npm run dev          # Development mode with hot reload
npm run build        # Compile TypeScript
npm test             # Run tests
npm run typecheck    # Type checking only

Why This One?

Several Scrivener MCP servers exist. Here's how they compare:

| Feature | scrivener-mcp | jiayun | zaphodsdad | others | |---------|:-:|:-:|:-:|:-:| | Document read/write | 60+ tools | 29 tools | read-only | basic | | RTF / rich text support | yes | no | no | no | | Writing analysis | readability, pacing, style, emotion | basic metrics | no | no | | Content enhancement | 12 types (filter words, verbs, show-don't-tell…) | no | no | no | | Semantic search (offline) | vector + analogies + dream mode | no | no | no | | Character consistency check | yes | no | no | no | | Character / plot memory | persistent profiles, plot threads, style guide | no | no | no | | Relationship graphs | HMS triplets + optional Neo4j | no | no | no | | Multi-agent analysis | roundtable critique with specialised agents | no | no | no | | Story structure analysis | yes (requires Neo4j) | no | no | no | | Token optimisation | progressive skill loading, compact JSON | no | no | no | | Batch document operations | yes | partial | no | no | | Export / compilation | yes — multiple formats | basic | no | no | | Windows support | full path handling + .scrivx discovery | partial | no | no | | Install method | npm · Homebrew · Docker · Smithery | manual clone | manual clone | varies | | Published to npm | yes (npm i -g scrivener-mcp) | no | no | no | | License | AGPL-3.0 / commercial dual-license | MIT | — | varies | | Active development | weekly | stale | occasional | stale | | Community | ⭐ 35 · 14 forks · 9 issues | ⭐ ? | ⭐ 5 | minimal |

Contributing

We welcome contributions of all sizes. Check the issue tracker for good first issue labels, or see the contributing guide for development setup.

Areas where help is especially welcome:

• Test coverage (#18)
• Windows testing and path handling
• Scrivener 2 compatibility testing
• Documentation improvements (#25)

Security

Found a vulnerability? Please report it privately — see SECURITY.md.

License

AGPL-3.0 © WritersLogic, Inc.

Free for personal use and open-source projects. Commercial license available for proprietary integration. See COMMERCIAL_LICENSE.md for details.