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Media Context MCP

Analyzes local or linked video, audio, and images for frames, transcripts, and on-screen text.

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Install Media Context MCP

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "media-context-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "media-context-mcp"
      ]
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Automated check passed— started and listed 2 tools correctly (4d ago).

Overview

media-context-mcp MCP server analyzes local media files and HTTP(S) links for AI assistants. It exposes tools for sampled video frames, scene detection, filmstrips, audio transcription, image analysis, and OCR, with processing performed on the local machine. Use it when an agent needs context from video, audio, screenshots, or supported media links without uploading files. Install the server with npx and run its setup command to install local helper dependencies.

Use cases

  • Summarize a local video from sampled keyframes
  • Transcribe meetings, podcasts, or voice notes
  • Read error messages from screenshots and screen recordings
  • Locate brief interface glitches with dense video sampling

Key features

  • Video keyframes, scenes, stills, and filmstrips
  • Local audio and video transcription
  • On-screen text extraction with OCR
  • Local files and supported HTTP(S) links
  • Cropping, time windows, and sampling controls
  • Local dependency and capability checks

Tools2

What Media Context MCP lets your agent do. Expand a tool for its parameters.

Verified live~1.3k tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked Today

Recent health check succeeded.

4/4 checks healthy over the last 44d

What it can do

From the 2 tools this server returned when we ran it.

Makes network requests · 1Read-only tools · 2
Network at startup3 connections
Files written at startupNone
Install scriptsNone
npm provenanceSigned build
Package age116 days
Maintainers1

Observed 2026-10-18 in an isolated sandbox. A description of reach, not a security audit.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 6d ago via OSV.dev · media-context-mcp (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars2Stargazers on the source repository.
npm downloads252Package downloads in the last 30 days.
Last commit20d agoMost recent push to the default branch.
Availability100%Our rolling endpoint + install checks that succeeded.
Install checkPassedOur sandbox started it and listed its tools.
Tools exposed2Callable tools this server registers over MCP.
Directory activity3 viewsConfig copies, upvotes, and views on AllMCPs.

How Media Context MCP works

What media-context-mcp MCP server does

The media-context-mcp MCP server turns video, audio, and image sources into context that an AI assistant can use. Sources can be local file paths or HTTP(S) URLs. For video, it can return sampled frames, full-size stills, scene-change frames, or dense filmstrips. Audio can be converted to a transcript, and images or video frames can be processed for text displayed on screen.

The server also removes temporary data after each tool call. Supported link sources include YouTube, Vimeo, and more than 1,000 other sites, according to the project documentation.

How it works

The primary analyze_media tool detects whether the source is audio, video, or an image. Video analysis defaults to sheet mode, which places sampled frames into one or two contact sheets. frames returns individual stills, scenes focuses on scene changes, and filmstrip samples densely for brief interface glitches or other short-lived events.

Analysis can be narrowed to a time range or a cropped region. Options also control image format, frame count, frame scale, grid size, scene sensitivity, and sampling rate. Transcription can be enabled for video and audio, with Whisper model choices from tiny through large. OCR can extract visible text and accepts language and page-segmentation settings.

Setup and configuration

Install the MCP package in a compatible client with the command npx -y media-context-mcp. The README provides configurations for Claude Desktop, Claude Code, Cursor, VS Code, Windsurf, Cline, Roo Code, Gemini CLI, Zed, Codex CLI, and JetBrains AI Assistant. Claude Code can also install it as a plugin, and project-scoped configuration is supported there.

After adding the server, run npx media-context-mcp setup for the core helpers. Add --audio to enable transcription support. The setup process uses the operating system package manager, and the server discovers the installed helpers automatically. Run check_media_deps to inspect available capabilities; setup --uninstall removes the helpers.

Tools and capabilities

The media-context-mcp MCP server exposes two documented tools:

  • analyze_media accepts a local path or URL and returns model-readable media context. It supports cropping, time windows, language selection, sampling controls, transcription, and OCR.
  • check_media_deps reports which local media capabilities are ready.

Useful workflows include summarizing a video from keyframes, reading an error from a screenshot, transcribing a meeting recording, explaining a screen recording from scene changes, or locating a brief visual defect with filmstrip sampling.

Limitations and notes

Transcription depends on the optional audio setup and a locally available Whisper model. OCR language support depends on the language codes and local helper availability. More detailed modes and parameters may increase processing time or the amount of visual context returned.

Read the full README View source on GitHub

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Frequently Asked Questions about Media Context MCP

media-context-mcp is an MCP server that connects AI assistants to local video, audio, and image files, plus supported HTTP(S) links. Its main tools are analyze_media for frames, transcripts, OCR, and media context, and check_media_deps for reporting available local capabilities. Processing runs on the user’s machine.

Install it with `npx -y media-context-mcp` in your MCP client configuration. Then run `npx media-context-mcp setup` for core helpers, or add `--audio` to enable transcription. The README includes client-specific configuration examples and a dependency check command.

Yes, media-context-mcp works with Cursor through its MCP configuration file.

Yes, it can transcribe audio and video locally when audio support is installed. Run `npx media-context-mcp setup --audio`, then enable transcription through `analyze_media`; the tool supports Whisper model choices including `tiny`, `base`, `small`, `medium`, and `large`.

Yes, it can extract on-screen text with OCR. Enable the `ocr` option in `analyze_media`, and optionally provide language codes such as `eng+deu`, page-segmentation settings, a crop, or a time range to focus the extraction.

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