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Feedback layer for video. Reviewers talk through feedback; agents read it as structured comments.
About
Feedback layer for video. Reviewers talk through feedback; agents read it as structured comments.
Remote endpoints: streamable-http: https://api.flask.do/api/mcp/mcp
Security Report
10.0
Low Risk10.0Low RiskValid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.
Endpoint verified · Requires authentication · 1 issue found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
How to Connect
Remote Plugin
No local installation needed. Your AI client connects to the remote endpoint directly.
Add this to your MCP configuration to connect:
{
"mcpServers": {
"io-github-enritarta-flask": {
"url": "https://api.flask.do/api/mcp/mcp"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
Flask plugin for Claude Code
Flask is the feedback layer for video, built for the agentic loop: your agent uploads a render and shares the link instantly. The reviewer doesn't type - they hit record and talk through the video (voice, camera, screen, drawing on frames), and Flask turns the recording into structured, timestamped comments with transcripts. The agent reads that feedback and iterates, pushing each revision as a new version of the same asset. Typed comments work too - recordings are the advantage, not a requirement.
This plugin connects the Flask MCP server and teaches the agent the full review loop.
Install
/plugin marketplace add enritarta/flask-plugin
/plugin install flask@flask
Then authenticate once: /mcp -> flask -> complete the browser sign-in.
No plugin manager? Connect the MCP server directly:
claude mcp add --transport http flask https://api.flask.do/api/mcp/mcp
What the agent can do
| Tool | What it does |
|---|---|
contents, search, recent_activity | Browse folders/assets, search, latest team feedback |
feedback_list, feedback_get | Read feedback with tags, timestamps, recording transcripts (transcript: "full" for whole recording) |
wait_for_feedback | Long-poll - returns new feedback the moment it's left |
upload_file_start / upload_file_complete | Upload a local video (5GB max) via presigned URL; share link available the instant the upload starts |
upload_video | Import from a public URL or Google Drive link |
version_of (param on uploads) | Upload as a new version of an existing asset - one stable link for the whole iteration |
asset_status, tags, permission_get | Processing status, tag distribution, folder access |
The server is read-only except for uploads - it can never edit or delete anything.
The loop in practice
agent renders video -> upload_file_start -> user gets flask.do link instantly
user records feedback on the video -> wait_for_feedback returns it (transcribed)
agent implements changes -> uploads v2 with version_of -> same link shows v2
Docs and support
- Server documentation: https://flask.do/mcp
- Support: hello@flask.do
This repo is kept in sync with the MCP server. Tool list and behavior described here mirror https://flask.do/mcp, which is the source of truth.
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