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Flask MCP Server

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Flask is listed as active in the registry but did not answer our last check. It exposes 17 tools. Last commit 8 Jul 2026.

Feedback layer for video. Reviewers talk through feedback; agents read it as structured comments.

Uptime history 51 days of history · worst day 0%
51 days agonow
3.3%
Uptime 24h
3 of 92 checks
17
Tools
read from the server
395 ms
Response time
average over 24h
0
Stars
last commit 8 Jul 2026

What changed 18

Every tool that appeared, vanished or quietly changed what it asks for. Recorded since 20 September 2026. No other catalogue keeps this.

20 Sep 10 tool descriptions were rewritten asset_status, contents, feedback_list and 7 more
20 Sep 8 tools changed the parameters they ask for asset_status, feedback_list, feedback_post and 5 more

What the code does

We read the source, 16 h ago · tools taken from the live server · rules 3dff92dd89df

Capabilities

What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.

Runs an external command cli.js:27
  return spawnSync(probe, [cmd], { stdio: "ignore" }).status === 0;

Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.

This code can reach further than it looks

We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.

Three servers free · no card

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 1 min ago.

run in your terminal
claude mcp add flask --transport http https://api.flask.do/api/mcp/mcp
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "flask": {
      "url": "https://api.flask.do/api/mcp/mcp"
    }
  }
}
~/.codex/config.toml
[mcp_servers.flask]
url = "https://api.flask.do/api/mcp/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "flask": {
      "url": "https://api.flask.do/api/mcp/mcp"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "flask": {
      "url": "https://api.flask.do/api/mcp/mcp"
    }
  }
}

Available tools 17

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

feedback
feedback_get
Get a single feedback item with its full reply thread. Returns the item's text body (for recordings: the AI-organized feedback), tags (by name), author, video timestamp, the recording's full verbatim transcript, visual_references (the pointing phrases - "this", "over here" - with the recording time each was spoken; feed them to get_frame to see what was being pointed at), visual attachments (images / has_drawing - render them with get_annotated_frames), and all nested replies.
feedback_list
List top-level feedback on an asset (pass the asset id for its current version, or a version id for that exact version). Returns each item's text body, tags (by name), author, timestamp, and reply_count. Recording items are ONE comment per recording: the text body is the AI-organized feedback, and the recording object adds the full verbatim transcript plus visual_references (the pointing phrases with the recording time each was spoken). Items with visual attachments carry images (attached image files) and/or has_drawing: true (a drawing made on the asset) - call get_annotated_frames to see them. Use feedback_get to read full reply threads.
feedback_post
Create a feedback comment on an asset, as the connected user. Pass an asset id (the comment lands on its current version) or a version id (that exact version). PREFER passing timestamp (seconds into the video) whenever the source material has one - e.g. when importing feedback from an email like 'at 0:42 the logo is wrong', convert 0:42 to 42. Without timestamp the comment is a general (non-anchored) note. tags applies the team's EXISTING tags by name (see the tags tool); statuses are tags too. Use reply_to to reply in an existing thread. Cannot attach recordings, drawings, or images.
feedback_stats
Aggregate feedback statistics across many assets in ONE call - counts per asset and per version (v1, v2, ...), split by type (text/recording), tag, and author, with first/last feedback timestamps. Scope to a folder (folder_id), one asset (asset_id - an asset id or any of its version ids; the whole asset is reported, version by version), or the whole team; narrow the time window with from/to. Each item carries container_id (the asset) and its versions. Use this for trend questions like 'are v1 notes going down across this client's recent videos' or 'what tags dominate this folder' instead of calling feedback_list per asset. For reading the feedback text itself across assets, use recent_activity.
feedback_update
Edit an existing feedback item. content (replaces the text) and timestamp (video time in seconds) can only be changed on the connected user's OWN comments. add_tags / remove_tags apply the team's existing tags by NAME and work on ANY feedback item you can comment on (labels and statuses are collaborative - e.g. add the 'Done' tag to mark feedback resolved). Provide at least one of content, timestamp, add_tags, remove_tags.
upload
upload_file_complete
Finalize a local file upload started with upload_file_start. Call this only AFTER the curl PUT has finished successfully. Verifies the file landed in storage and starts video processing. Safe to retry.
upload_file_start
Start uploading a LOCAL video file from the user's machine into Flask. Creates the asset immediately (container_id + shareable url, live before any bytes move) with the file as its version (asset_id / version_id), or a new version of an existing asset with version_of, and returns a presigned upload URL. After calling this, upload the file bytes with the curl command from next_step, then call upload_file_complete. folder_id is OPTIONAL: omit it to upload to the team's top level (root). Max file size 5GB. Free to use for up to 100 MCP uploads; beyond that the user needs a plan at https://flask.do/plan. You still need edit access on the folder if one is given.
upload_video
Upload a video from a public URL (a direct video file link or a Google Drive share link) into Flask. Flask downloads it, stores it, and starts processing. Creates a new asset (container_id + url) with the file as its first version (asset_id / version_id), or a new version of an existing asset with version_of. Share the returned asset URL while processing; poll asset_status(version_id) until status is "ready" before reporting processing complete. folder_id is OPTIONAL: omit it to upload to the team's top level (root). Free to use for up to 100 MCP uploads; beyond that the user needs a plan at https://flask.do/plan. You still need edit access on the folder if one is given. For a LOCAL file on disk, use upload_file_start instead.
annotated
get_annotated_frames
Supplementary visuals for a feedback item. For recording items: the media under review with the reviewer's drawing rendered in, plus their shared SCREEN when they demonstrated something (e.g. a Photoshop/Figma mockup); webcam frames are NOT included, and the transcript is returned marked [FRAME N]. Also works for text comments that carry visuals: a standalone drawing (has_drawing: true) is rendered onto the frame it was drawn over, and attached images (images array) are returned as frames. If a visual reference is still unclear, call get_frame to drill into a specific moment (at) or spoken word/phrase (word). Returns up to 12 images.
asset
asset_status
Check the processing status of a video. Pass the version id an upload returned (asset_id), or an asset id (resolves to its current version). Returns progress percentage for videos being processed, confirms it is ready, or reports no_versions for an asset that has no media yet.
contents
contents
Browse contents. Without folder_id: lists what's at the team's top level (root) — both folders and assets that live directly at root. With folder_id: opens that folder and returns its child folders and assets. Each asset item carries asset_id (the asset), version_id (its current version), version_count, its media fields, url (always the newest version) and version_url.
frame
get_frame
Drill into a recording for MORE visual detail: get the exact frame at a specific time (at) or when a specific word/phrase was spoken (word). Use when get_annotated_frames did not show what a reference ('this','here','that') means, or to see a moment the transcript mentions. Returns the asset frame at that moment (plus the active shared screen, if any) and a transcript snippet around it.
permission
permission_get
See who has access to a folder or an asset and their permission levels (full_access, comment, view, none). Returns the connected user's effective access, the creator, plus link and team-member default access levels. Pass folder_id for a folder, or asset_id for an asset (an asset id or any of its version ids - permissions live on the asset, versions inherit them).
recent
recent_activity
Get the latest comments across your team, newest first. Returns a mix of text and recording comments with author, timestamp, and a link to jump into the conversation. Each item has a `type` field ("text" or "recording") plus the asset it belongs to (container_id / container_title), the version it was left on (asset_id = version id, version number), so you can read feedback across many videos in one call. Scope with folder_id to read one client's/project's feedback, narrow the window with since/until, and page with offset. For counts and trends use feedback_stats instead.
search
search
Search across your team's folders, assets, and feedback by text. Always returns all three categories together.
tags
tags
List the team's tags and show the share of each tag (plus an 'untagged' bucket) across a scope. Scope defaults to the whole team; pass folder_id to narrow to one folder (its whole subtree), or asset_id to narrow to one asset (an asset id counts feedback across ALL its versions; a version id widens to its asset). Shares are count_with_tag / total_elements and do NOT sum to 100% because elements can carry multiple tags.
wait
wait_for_feedback
Wait for NEW feedback on an asset. Blocks up to timeout_seconds (default 45) and returns as soon as feedback newer than `since` arrives, or times out with an empty list. To listen continuously, call it again with the returned next_since. Use this after uploading a video for review instead of repeatedly calling feedback_list.

Endpoints

URLTransportStateLatencyChecked
https://api.flask.do/api/mcp/mcp streamable-http answering 166 ms 1 min ago

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Flask — questions

Answers built from our own checks of this server.

What can Flask do?
It exposes 17 tools, read directly from the server on our last check. Among them: asset_status, contents, feedback_get, feedback_list, feedback_post, feedback_stats and 11 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
What is Flask mostly used for?
Its tools cluster around feedback and upload. That is what this server is built to work with — the grouping comes from the actual tool names, not from a category we assigned.
Is Flask working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 3 of 92 checks got a reply (3.3%), average response time 395 ms. The bar chart above shows every period we have measured.
The registry lists Flask as active — why does it not respond?
The official MCP registry stores what the author submitted; it does not verify that the server still runs. We check the endpoint ourselves, and this one does not answer. Catalogues that copy the registry without checking will show it as working.
How do I connect Flask?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does Flask need an API key?
No. Flask completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 17 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is Flask?
It answers our handshake in 395 ms on average, which is faster than 41% of all working MCP servers we measure. The comparison comes from our own checks across the whole registry, every 15 minutes.
Is Flask open source?
Yes — it is published under the MIT licence, written in JavaScript, 0 stars on GitHub and 1 open issue. The source link is on this page, so you can read exactly what it does with your data before you connect it.