Is Flask Plugin free?

Yes, Flask Plugin is free to use.

How do I install Flask Plugin?

Flask Plugin is a remote plugin. You do not need to install anything locally. Add the server URL to your AI app's MCP configuration and you are ready to go.

Is Flask Plugin safe to use?

Yes. Flask Plugin passed MCP Marketplace's automated security scan with a score of 10/10 (low risk). Every server on MCP Marketplace is security-scanned before it's listed; see the full security report on this page for the findings and permissions.

What AI apps work with Flask Plugin?

Flask Plugin uses the Model Context Protocol (MCP) and works with any MCP-compatible AI app, including Claude, ChatGPT / Codex, Gemini, Copilot, Cursor, and more.

Back to Browse

Flask Plugin MCP Server

by Enritarta

Developer ToolsLow Risk10.0MCP RegistryRemote

Free

Server data from the Official MCP Registry

Feedback layer for agentic video: upload renders for human review, read transcribed feedback.

About

Feedback layer for agentic video: upload renders for human review, read transcribed feedback.

Remote endpoints: streamable-http: https://api.flask.do/api/mcp/mcp

Security Report

10.0

Low Risk10.0Low Risk

Valid 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.

file_system

Check that this permission is expected for this type of plugin.

Shell Command Execution

Runs commands on your machine. Be cautious — only use if you trust this plugin.

HTTP Network Access

Connects to external APIs or services over the internet.

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 GitHub

From 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

One command connects the Flask MCP server (Claude Code, Cursor) and installs the review-loop skill for any agent that reads skills:

npx flask-feedback

Prefer to wire things yourself? Per-client instructions below.

Claude Code

/plugin marketplace add tryflask/skills
/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

Cursor, Codex, and other agents

Install the review-loop skill (works across skills-compatible clients):

npx skills add tryflask/skills

Then connect the MCP server:

Cursor:
claude.ai / Claude Desktop: Settings -> Connectors -> add https://api.flask.do/api/mcp/mcp
Any MCP client: Streamable HTTP at https://api.flask.do/api/mcp/mcp (OAuth sign-in opens in the browser on first use)

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
`get_annotated_frames`	Returns the video frames a recording pointed at / drew on, as images with the drawing rendered in, plus the transcript marked `[FRAME N]` - resolves "this"/"here"/drawn-circle references to actual pixels
`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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Flask Plugin MCP Server

About

Security Report

Findings (1)

Permissions Required

How to Connect

Documentation

Flask plugin for Claude Code

Install

Claude Code

Cursor, Codex, and other agents

What the agent can do

The loop in practice

Docs and support

Reviews

No reviews yet

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