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kitsu-mcp

MCP server (FastMCP + Gazu) for a Kitsu/Zou instance. Runs locally over stdio, or hosted over HTTP as a Le Chat / AI Studio connector where each person logs in with their own Kitsu account. Read-only by default; write tools are opt-in.

Install

You only need uv:

curl -LsSf https://astral.sh/uv/install.sh | sh

Then register the server with your agent, using your Kitsu login.

Mistral Vibe

vibe mcp add kitsu --transport stdio --command uvx --arg kitsu-mcp \
  --env KITSU_HOST=https://your-studio.cg-wire.com/api \
  --env KITSU_USER=you@example.com \
  --env KITSU_PASSWORD='your-password'

Claude Code

claude mcp add kitsu --scope user \
  -e KITSU_HOST=https://your-studio.cg-wire.com/api \
  -e KITSU_USER=you@example.com \
  -e KITSU_PASSWORD='your-password' \
  -- uvx kitsu-mcp

The password is stored in plain text in the agent's config file (e.g. ~/.vibe/config.toml).

Hosted connector (Le Chat, AI Studio)

Le Chat and AI Studio run in Mistral's cloud, so they need the server at a public HTTPS URL. One server serves everyone: each person adds their own private connector with their Kitsu login, and every call runs as them, with their Kitsu permissions.

Run it. Only KITSU_HOST is needed (no shared login). Deploy the image on a host that terminates HTTPS (Fly.io, Render, a reverse proxy) and confirm it with KITSU_BEHIND_TLS=true:

docker run -p 8000:8000 -e KITSU_HOST=https://your-studio.cg-wire.com/api -e KITSU_BEHIND_TLS=true \
  ghcr.io/estienneg/kitsu-mcp:latest

(or build it yourself with docker build -t kitsu-mcp .). Pin a version tag such as :0.2.0 in production.

To try it locally without a proxy, run KITSU_HOST=... kitsu-mcp --http, which listens on 127.0.0.1:8000.

The supported entry point is kitsu-mcp --http (--host / --port, or KITSU_HTTP_HOST / PORT): it applies the TLS check below, which fastmcp run would skip. The MCP endpoint is /mcp; /health answers for health checks. The image runs as an unprivileged user.

HTTPS is required. Callers send their Kitsu password with every request, so the server refuses to listen on anything but localhost unless the operator confirms TLS terminates in front of it (--behind-tls or KITSU_BEHIND_TLS=true; deliberately not set in the image). It never logs credentials and keeps them only in memory, under keys derived with a per-process secret. Only logins Kitsu accepted are kept, for an hour of inactivity. Repeated rejected logins for one account are slowed down (a Kitsu outage does not count), while a login Kitsu accepted in the last day is always let through, so guessing at someone's email cannot lock them out. Spraying many emails from one address is not throttled; fine at studio scale, otherwise rate-limit at the proxy. Listing the tools works without a login (it is metadata only); every tool call needs one.

Each user (AI Studio → Connectors → Add, or Le Chat → Connectors → Custom MCP connector):

  • URL: https://<your-server>/mcp, visibility Private
  • Authentication: Basic, with their Kitsu email and password. Where only a bearer token can be entered, use email:password as the token.

Differences from stdio: download_previews and download_video are hidden (they would write to the server's disk, not the user's); give people the url (Kitsu page) or download_url (original upload) instead, which open in their own Kitsu browser session. The video tools cache movies per user, and KITSU_VIDEO_CACHE_MB caps all users' movies together. Write tools follow KITSU_ALLOW_WRITE as over stdio. Kitsu accounts with two-factor authentication cannot log in this way.

Configuration

Variable Default
KITSU_HOST required Zou API URL, ending in /api
KITSU_USER / KITSU_PASSWORD required over stdio Kitsu login (over HTTP each caller sends their own)
KITSU_ALLOW_WRITE false Expose the write tools below
KITSU_CACHE_TTL 300 Seconds to cache projects, task types, statuses, people, departments, custom fields
KITSU_TIMEOUT 30 Per-request timeout (seconds)
KITSU_MAX_RETRIES 3 Attempts for reads failing with a server or network error
KITSU_VIDEO_CACHE_DIR system temp Where the video tools cache movies (kitsu-mcp-videos/)
KITSU_VIDEO_CACHE_MB 1024 Movie cache size; least recently used movies are deleted past it
KITSU_VIDEO_MAX_MB 500 Largest movie the video tools download
KITSU_OMITTED_STATUSES omit,na,n/a,omitted,cancelled,canceled Statuses meaning "dropped": left out of progress and open work
KITSU_DONE_STATUSES (none) Statuses meaning "finished", whatever Kitsu flags (e.g. cbb for "could be better")
KITSU_ON_HOLD_STATUSES stand by,standby,pause,paused,blocked,on hold Open but paused: never overdue
KITSU_REVIEW_STATUSES (none) Extra statuses meaning "waiting for review/approval"
KITSU_RETAKE_STATUSES (none) Extra statuses meaning "sent back for changes"
KITSU_DRY_RUN_LOG (none) JSONL file each write-tool dry run is appended to

Variables can also come from a .env file in the working directory.

Status roles

Kitsu's flags on a status (done, retake, feedback request, in progress) do not always say what a studio means: an OMIT status is often flagged done but means dropped, and a studio may flag a "could be better" (CBB) status as retake while meaning done-but-improvable (set KITSU_DONE_STATUSES=cbb for that). So every status gets exactly one role — omitted, done, on_hold, retake, waiting_review, wip or todo — and every count and filter uses it (progress, overdue, waiting for review, workload, search). A status listed in one of the KITSU_*_STATUSES settings above (names or short names, case-insensitive, checked in the order shown) takes that role; any other status gets it from Kitsu's flags, in the order done > retake > feedback request > in progress > to do.

list_task_statuses shows each status's role and where it comes from, and reports configured names that match no status. project_overview reports which statuses it counted as omitted and as done-but-improvable.

Development

cp .env.example .env   # fill in KITSU_USER / KITSU_PASSWORD
uv run kitsu-mcp       # reads .env from the current directory
uv run pytest          # tests run against an in-memory fake Kitsu, no credentials needed
uv run ruff check . && uv run ruff format --check . && uv run pyright

Layout (src/kitsu_mcp/): config.py settings, client.py HTTP client (login, re-login, retries, error mapping), lookups.py cached reference data and name resolution, models.py output schemas, formatters.py payload → model conversion, production.py project-wide task views, plans.py write plans (dry run), custom_fields.py custom field values and filters, tools/ one module per domain, resources.py, prompts.py, auth.py per-caller credentials, http.py HTTP mode (hidden local tools, /health, TLS guard), links.py Kitsu web links.

Release: bump version in pyproject.toml, merge, then tag it (git tag v0.2.0 && git push origin v0.2.0). The Release workflow checks the tag matches the version, runs the checks, then publishes the package to PyPI and the Docker image to ghcr.io/estienneg/kitsu-mcp (tags 0.2.0, 0.2 and latest). PyPI uses trusted publishing, so no token is stored: the kitsu-mcp project on PyPI has this repository as its publisher (workflow release.yml, environment pypi).

Tools

Project, task type, department, status and person arguments take names (case-insensitive) or IDs. departments filters (search_tasks, workload, project_overview) keep tasks whose task type belongs to one of the departments, so the three tools agree; people's own departments are not used (list_people shows them).

Area Tools
Meta whoami, kitsu_get (raw read of any Zou data/ route), refresh_cache
Projects list_projects, list_task_types, list_task_statuses, list_asset_types, project_overview
Assets list_assets (type, name and per-task-type status filters; detail="compact" or "full"), get_asset, get_casting (either way)
Shots list_episodes, list_sequences, list_shots, get_shot, get_casting
Custom fields list_custom_fields (a project's custom columns: type, choices, departments); values show up by display name in get_asset / get_shot (and detail="full" lists), and list_assets / list_shots filter on them with custom_field_filters
Tasks search_tasks (type, department, status, assignee, due dates, overdue, waiting feedback, group by assignee, ...), get_task, task_history, my_tasks
People list_people, get_person_tasks, workload
Previews recent_previews (latest uploads), get_preview (image or metadata, by entity or preview file), list_task_previews, download_previews, list_playlists, get_playlist
Video ([video] extra) get_video_info, get_video_contact_sheet, get_video_frames, compare_revisions, review_video, download_video
Write (opt-in) add_comment, set_task_status, assign_task, update_task_schedule, log_time, create_playlist, add_to_playlist (shots/assets with their latest preview)

Links: detail results carry a url to the Kitsu page (asset, shot, task, preview in the player, playlist), and preview metadata a download_url to the original upload. They open in a browser signed in to Kitsu, so movies are watched and downloaded there rather than passed through the server.

Dry run. Every write tool takes dry_run=True: it runs the same lookups and checks with reads only and returns the plan instead of writing: would (the action in one line), requests (method, path and payload, exactly what the real call sends), before/after for the fields that change (status, assignees, dates, estimate, time logged), and warnings (e.g. Kitsu may refuse a status your role cannot set). If a check fails (archived status, inactive person, start date after due date, over 24 h logged in a day), verdict is would_fail with the reason, and the real call refuses with the same reason. Invalid arguments (bad IDs, unknown names) are errors either way. Agents are told to dry-run first and show the user the plan.

Resources: kitsu://projects, kitsu://task-types, kitsu://task-statuses, kitsu://projects/{project}/overview, kitsu://tasks/{task_id}.

Prompts: project_status_report, review_queue, my_day, person_summary, review_shot.

Video

The video tools look inside movie previews. They need the optional video extra (PyAV, which bundles ffmpeg, and Pillow), so no system ffmpeg is required:

uvx --from 'kitsu-mcp[video]' kitsu-mcp      # or: pip install 'kitsu-mcp[video]'

Use that as the command when registering the server (e.g. -- uvx --from 'kitsu-mcp[video]' kitsu-mcp for Claude Code). Without the extra the tools are still listed but answer with an error saying how to install it (download_video works either way). get_preview says when a preview is a video.

  • Movies are fetched at Kitsu's low-resolution playback quality by default (quality="original" for the uploaded file) and cached per preview file and quality (see the KITSU_VIDEO_* settings).
  • Tools take a preview_file_id, or an entity_id (shot or asset) to use its current preview.
  • Frames are numbered from 1, like Kitsu's player. Frame arguments accept frame numbers (37), timecodes ("00:00:01:12", HH:MM:SS:FF), times ("1.5s") and percentages ("50%"). review_video finds the frames a task's comments point at: Kitsu's v3 00:00:01:12 (37) tags, timecodes, "frame 37", "2.5s", and frames with drawn annotations.
  • Limits: at most 16 frames per call, grids at most 1568 px on a side, single frames at most 1280 px. The agent only sees sampled still frames: no motion in between and no audio. Every image costs context, so start with get_video_contact_sheet and zoom in with get_video_frames.

License

MIT: see LICENSE. Free to use, modify and distribute, including commercially, provided the copyright notice is kept; no warranty.

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