writerslogic/scrivener-mcp

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πŸ“‡ 🏠 🍎 πŸͺŸ 🐧 - Connect Scrivener 3 writing projects to Claude and other AI assistants. 47 tools for document management, writing analysis, semantic search, character/plot memory, and content enhancement. Progressive skill loading, relationship engine with HMS triplets, and JS fallback for offline semantic search. npm i -g scrivener-mcp

Quick Install

One-Click IDE Configuration
claude_desktop_config.json
{
  "mcpServers": {
    "writerslogic-scrivener-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "writerslogic-scrivener-mcp"
      ]
    }
  }
}
Or

Using an AI coding agent (Claude Code, Cursor, etc.)? Copy a ready-made prompt that tells it to fetch the setup instructions and install this server for you.

Documentation Overview

Scrivener MCP Logo

Scrivener MCP

Connect your Scrivener projects to Claude, ChatGPT, and other AI assistants

npm version npm downloads build OpenSSF Scorecard license node version issues stars MseeP verified scrivener-mcp MCP server score

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


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
Setup for other MCP clients

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.

Optional: AI-powered features

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 β€” 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.

Project -- open, browse, manage
ToolWhat it does
open_projectOpen a .scriv project (accepts .scriv folders or .scrivx files) and make it active
discover_projectsScan common locations for Scrivener projects when you don't know the path
detect_open_projectDetect the project currently open in the Scrivener app (macOS) so you don't need a path
get_structureBrowse the binder hierarchy (folders, documents, word counts)
refresh_projectReload from disk after external edits
close_projectClose the active project and flush pending changes
verify_project_integrityRead-only scan for structural problems (missing/duplicate UUIDs, unreadable content)
get_compile_settingsRead the project's compile formats and taxonomy -- labels/statuses (with colors), collections, section types
get_manuscript_briefingOne "where am I?" snapshot: words vs. target (% to goal), document/status/label counts, longest/shortest documents
list_snapshotsList Scrivener snapshots (title, date) for one document or the whole project
read_snapshotRead a snapshot's text as plain text, with word count
compare_snapshotDiff a snapshot against the current document (or another snapshot): paragraphs added/removed and net word change
create_snapshotTake a Scrivener-native snapshot of a document (restorable from Scrivener's own Snapshots browser) before editing
Documents -- read, write, create, organize
ToolWhat it does
get_document_infoMetadata for one document (title, type, word count, synopsis, label, status)
read_documentRead content; format: "formatted" for rich text, offset/limit to page long docs
write_documentReplace a document's content (atomic, with pre-write backup)
create_documentCreate a new text document or folder
update_documentChange title and/or metadata (synopsis, notes, label, status, custom fields)
move_documentReorganize within the binder
delete_documentMove to trash (reversible)
Search -- find content, passages, and mentions
ToolWhat it does
searchKeyword/full-text search; field: "title" for titles, scope: "trash" for trash
semantic_searchFind passages by meaning using embeddings, with similarity scores
find_mentionsLocate every occurrence of a specific name or term, with context
list_trashList trashed documents
restore_documentRestore a document from trash
read_annotationsRead a document's comments and footnotes
Analysis -- quality, consistency, structure
ToolWhat it does
analyze_documentAI writing analysis; focus with aspects (structure, style, pacing, themes...)
check_consistencyProject-wide continuity check; scope for plot, characters, or timeline
analyze_writing_styleStyle-focused analysis
check_plot_consistencyPlot-thread consistency check
suggest_improvementsAI-generated improvement suggestions
enhance_contentSuggest a specific improvement to a document
generate_contentGenerate new prose from a prompt and context
set_writing_goalSet a word-count goal (daily, weekly, or whole project) with an optional target date
get_writing_goalsList goals with progress -- percent complete, words remaining, on-pace status
set_writing_preferencesSet author preferences (tone, complexity, length, POV, style guide) that steer AI output
get_writing_preferencesShow current preferences plus feedback insights and suggestions
collect_feedbackRecord 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

Compile & Export -- assemble and ship the manuscript
ToolWhat it does
compile_documentsCombine 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_projectWrite the manuscript to disk -- Markdown, HTML, JSON inline, or DOCX, EPUB, PDF as a file
get_statisticsProject-level word/document/character counts
generate_marketing_materialsDraft synopsis, query letter, pitch, and related materials
Memory -- persistent project knowledge
ToolWhat it does
rememberStore information that persists across sessions with the project
recallRetrieve previously stored memory

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

Relationships -- entity connections and story graph
ToolWhat it does
add_relationshipStore a relationship between characters, locations, themes, or plot threads
find_relationshipsQuery entities related to a given character/theme/location
discover_connectionsFind co-occurring entities across the manuscript
character_networkThe character relationship network
get_entity_referencesTrace the reference graph in either direction: entities a document mentions (by documentId), or documents mentioning an entity (by entity)
find_orphaned_entitiesList registered characters/locations that no document actually mentions
suggest_connectionsSuggest 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.

Background Jobs -- long-running analysis
ToolWhat it does
queue_document_analysisEnqueue an async analysis of one document; returns a job id
queue_project_analysisEnqueue an async analysis of the whole project
get_job_statusPoll progress/results for a queued job
cancel_jobCancel a queued or running job
Discovery -- explore capabilities
ToolWhat it does
list_skillsList the available tool groups and their tools
use_skillActivate a tool group (most are pre-activated by default)

Guides

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:

Featurescrivener-mcpjiayunzaphodsdadothers
Document read/write60+ tools29 toolsread-onlybasic
RTF / rich text supportyesnonono
Writing analysisreadability, pacing, style, emotionbasic metricsnono
Content enhancement12 types (filter words, verbs, show-don't-tell…)nonono
Semantic search (offline)vector + analogies + dream modenonono
Character consistency checkyesnonono
Character / plot memorypersistent profiles, plot threads, style guidenonono
Relationship graphsHMS triplets + optional Neo4jnonono
Multi-agent analysisroundtable critique with specialised agentsnonono
Story structure analysisyes (requires Neo4j)nonono
Token optimisationprogressive skill loading, compact JSONnonono
Batch document operationsyespartialnono
Export / compilationyes β€” multiple formatsbasicnono
Windows supportfull path handling + .scrivx discoverypartialnono
Install methodnpm Β· Homebrew Β· Docker Β· Smitherymanual clonemanual clonevaries
Published to npmyes (npm i -g scrivener-mcp)nonono
LicenseAGPL-3.0 / commercial dual-licenseMITβ€”varies
Active developmentweeklystaleoccasionalstale
Community⭐ 37 · 14 forks · 9 issues⭐ ?⭐ 5minimal

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 β€” see SECURITY.md.

License

AGPL-3.0 Β© WritersLogic, Inc.

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

scrivener-mcp MCP server

GitHub Β· npm Β· Issues Β· Changelog

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