Scrivener MCP

The definitive MCP server for Scrivener — connect your novels, screenplays, and manuscripts to Claude, ChatGPT, and any AI assistant. 53 tools: 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.

Keys are picked up automatically from:

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

security add-generic-password -s anthropic-api-key -a anthropic -w sk-ant-your-key-here   # Keychain
export ANTHROPIC_API_KEY="sk-ant-..."                                                      # or export it directly

What You Can Do

Open a project first. The server has no link to the Scrivener app itself and can't see what's open there — say "Open my Scrivener project at ~/Documents/My Novel.scriv", or "Discover my Scrivener projects" if you don't know the path. On macOS, "Use the project I have open in Scrivener" works too (the first time, macOS will ask permission to control Scrivener). Do this once per conversation. If the project is also open and unsaved in Scrivener itself, save or close it there first, or the two can write over each other.

Manage your manuscript. Read chapters, create scenes, reorganize the binder, update synopses — all through conversation. "Create a new scene called 'The Reveal' after Chapter 5, and move the old epilogue to the trash."

Analyze your writing. Readability, pacing, style, dialogue quality, emotional arc — grounded in your actual prose, not generic advice. Ask whether a chapter's pacing is off and get specifics: which paragraphs stall, how the scene compares to your other chapters, filter-word density against your own average.

Enhance your prose. Targeted edits: cut filter words, strengthen verbs, vary sentence structure, add sensory detail, turn telling into showing, tighten dialogue, fix pacing.

Track characters and plot. Character profiles, plot threads, and style guides persist with the project across sessions. Save a profile for a character once; a consistency check months later catches contradictions — dialogue that doesn't sound like them, a limp that disappears for a chapter.

Search by meaning. "Find scenes where the protagonist feels isolated" works even if that word never appears. Indexing and similarity scoring run locally through the Holographic Memory System; semantic_search also needs a configured AI provider to interpret the query and explain the results.

Track relationships. Query how characters, locations, themes, and plot threads connect. No Neo4j required — relationships live in the semantic memory engine and persist with the project; Neo4j adds deeper graph analysis if you have it.

Compile and export. Assemble chapters into one manuscript with your own formatting and structure preserved. Export inline as Markdown, HTML, or JSON, or write a DOCX, EPUB, or PDF to disk.

All Tools

57 tools organized by workflow. To keep token usage low, tools load progressively — project tools at startup, document and search tools once a project is open, the rest on demand. Set SCRIVENER_MCP_EAGER_TOOLS=1 to load everything up front.

Project -- open, browse, manage

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

Documents -- read, write, create, organize

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)

Search -- find content, passages, and mentions

Tool	What it does
search	Keyword/full-text search; field: "title" for titles, scope: "trash" for trash
semantic_search	Find passages by meaning using the local HMS index plus provider-backed query interpretation, 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

Analysis -- quality, consistency, structure

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

Compile & Export -- assemble and ship the manuscript

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

Memory -- persistent project knowledge

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.

Relationships -- entity connections and story graph

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.

Background Jobs -- long-running analysis

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

Discovery -- explore capabilities

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
• Fuzzing -- Jazzer.js target and OSS-Fuzz integration details
• Contributing -- Development setup, code conventions, adding new tools

Requirements

• Node.js 18+
• Scrivener 3 project files (.scriv)
• macOS, Windows, or Linux
• Optional: Anthropic, OpenAI, or OpenRouter API key for provider-backed AI features
• Optional: Neo4j for persistence and advanced graph queries; core relationship tools work without it

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?

A few Scrivener MCP servers exist. Feature claims below come from each project's own docs, published package, and advertised tools, last re-read on 2026-08-22; stars, forks, activity, and published version were refreshed 2026-09-15. "No" means undocumented — not necessarily impossible through the connected AI client.

Feature	scrivener-mcp	jiayun	TwelveTake	Scrivener Assistant	ricopicone	zaphodsdad
Public MCP tools	57	29	22	38	18	10
Manuscript access	read/write	read/write	read/write	read-only; writes sidecar data/metadata	read-only by default; opt-in content/notes/synopsis writes	read-only
RTF handling	formatted reads; fidelity-preserving span writes	reads/writes document content	reads/writes document content	converts RTF to text; manuscript read-only	RTF-to-text reads; snapshot-protected content writes	converts RTF to text; read-only
Built-in writing analysis	readability, pacing, style, emotion, AI critique	readability, style, sentiment	continuity comparison	agent-driven five-point review workflow	no dedicated analysis tool	no dedicated analysis tool
Content generation/enhancement	generation + 12 targeted enhancement types	no	no	brainstorm/draft agent workflow	no	no
Local semantic retrieval	HMS index and similarity search	no	no	no	no	no
Continuity/project memory	persistent memory + consistency checks	persistent notes + consistency checks	mention/description comparison	world bible, story state, characters, locations, review history	no persistent memory	no persistent memory
Relationship tooling	persistent relationships, networks, reference graph; optional Neo4j	no	no	human-editable relations data	no	no
Token optimization	progressive skill loading, compact output, paged reads	no documented equivalent	no documented equivalent	no documented equivalent	scoped binder/chapter reads	scoped overview/read tools
Export / compilation	Markdown, HTML, JSON, DOCX, EPUB, PDF	compile + whole-draft export	PDF	saves AI drafts; no manuscript export documented	no	no
Windows support	yes	yes (prebuilt binary)	yes	not documented	not documented	yes
Installation	npm, Homebrew, Docker, Smithery	Cargo or prebuilt binary	npm package (deprecated)	MCPB or source	source / uv	source / pip install -e
License	AGPL-3.0 / commercial dual-license	MIT	MIT	MIT	not declared	MIT
Repository/package status	weekly activity; npm 0.12.0	monthly activity	discontinued and unmaintained	occasional activity	occasional activity; no releases	occasional activity; no releases
Community	⭐ 54 · 18 forks	⭐ 7	source repository unavailable	⭐ 1	⭐ 0	⭐ 5 · 1 fork

Counts and feature claims can change. Follow the linked projects for their own latest documentation. The table is generated from docs/comparison.yml — edit claims there, not here.

The alternative that isn't an MCP server

Scrivener can also Sync to External Folder, writing each document out as RTF or plain text, which any generic file-access MCP server (like @modelcontextprotocol/server-filesystem) can then read and write.

It's free and works today. What you lose is everything tied to the actual project — binder hierarchy, metadata, labels and status, snapshots, compile settings, RTF formatting — and edits land in the sync folder rather than the project itself, so a bad edit gets reconciled by Scrivener on the next sync instead of caught before it happens. Fine for occasional read-only help with prose; not if you want the structure to survive the round trip.

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.

GitHub · npm · Issues · Changelog