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:passwordas 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 theKITSU_VIDEO_*settings). - Tools take a
preview_file_id, or anentity_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_videofinds the frames a task's comments point at: Kitsu'sv3 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_sheetand zoom in withget_video_frames.
License
MIT: see LICENSE. Free to use, modify and distribute, including commercially, provided the copyright notice is kept; no warranty.
Metadata
Release files for kitsu-mcp 0.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| kitsu_mcp-0.3.0.tar.gz | 71.2 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| kitsu_mcp-0.3.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 155.2 kB
Release files / kitsu_mcp-0.3.0.tar.gz
| Download URL | kitsu_mcp-0.3.0.tar.gz |
|---|---|
| Size | 71.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
475e7b42dcaca2c9735e61c222ba8c2ebba0263f07b956051592135dedcea5f0
|
|
BLAKE2b-256 checksum How to use checksums |
a5fe2ad19b1778905f6c4943770d5d89fee88011c68e04d20a20781652df7a13
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
uv/0.13.5 {"installer":{"name":"uv","version":"0.13.5","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}
|
Release files / kitsu_mcp-0.3.0-py3-none-any.whl
| Download URL | kitsu_mcp-0.3.0-py3-none-any.whl |
|---|---|
| Size | 84.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
a2e2f686bcaa51ba2fba6322984e82e8ae724e8064123d1935fd1c569c10e9c9
|
|
BLAKE2b-256 checksum How to use checksums |
db377e1f127fa6e311724566caa10eca0b5338dd66e519cb45fa93fcfc7036ab
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
uv/0.13.5 {"installer":{"name":"uv","version":"0.13.5","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}
|
Security for kitsu-mcp 0.3.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.