scrivener-mcp

scrivener-mcp is an MCP server, listed under model apis. It reaches anthropic. It needs ANTHROPIC_API_KEY to authenticate. Its repository has 69 GitHub stars and is licensed under AGPL-3.0; we last read it on 2026-10-25.

Connects Scrivener projects to Claude, ChatGPT, and other AI assistants for document management, writing analysis, content enhancement, offline semantic search, and character/plot tracking.

Read from scrivener-mcp’s own README, close to verbatim -- not written by us, and not guessed.

npm install -g scrivener-mcp

40 tools documented in its README. An AI client calls these by name.

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

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

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

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

analyze_craft_local

Offline readability, grammar, syntax-tension, dialogue, and word-frequency report for one document (narrative-lens, no AI call)

check_continuity_local

Offline timeline and world-state continuity pass across the manuscript

Read from the README; names are kept only if the README contains them.

Ranked by services in common with scrivener-mcp, then by stars. Figures are from each repository when we last read it.

What does scrivener-mcp do?

Connects Scrivener projects to Claude, ChatGPT, and other AI assistants for document management, writing analysis, content enhancement, offline semantic search, and character/plot tracking.

How do I install scrivener-mcp?

Its own README gives this command: npm install -g scrivener-mcp. Run it where your MCP client can launch the server, and check the README for any settings it asks for.

What does scrivener-mcp connect to, and what does it need?

It reaches anthropic. The credentials we found in its source are ANTHROPIC_API_KEY.

Is scrivener-mcp official and is it maintained?

We found nothing naming it as a vendor’s official server. Its repository has 69 GitHub stars and its state in our directory is listed. Its last commit we recorded was on 2026-10-22.

What licence does scrivener-mcp use?

The repository declares the AGPL-3.0 licence.

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