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media context mcp

media context mcp

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@vishalguptax2TypeScriptApache-2.0Updated 2mo ago

Local MCP server to analyze video, audio & images: frames, transcripts, on-screen text.

media-context-mcp — local media analysis for AI assistants

npm version npm downloads license node

Give your AI assistant eyes and ears.
Analyze any video, audio, or image — locally, right inside your editor.

Install  ·  Capabilities  ·  Modes  ·  Examples  ·  Tools  ·  Options  ·  Docs


LLMs read text and glance at a single image — but they can't watch a video or listen to audio. media-context-mcp closes that gap. Hand it a file or a link and it returns clean, model-ready context — keyframes, a transcript, or the text on screen — entirely on your machine. Nothing is uploaded.

A 10-second clip turned into one contact sheet of keyframes

A 10-second clip becomes one tidy contact sheet your model reads in order — not hundreds of stills.


🚀 Install

Two steps — add the server, then install the local helpers it uses.

1 · Add the server to your client

# Claude Code
claude mcp add media-context -- npx -y media-context-mcp

The launch command is always npx -y media-context-mcp. Pick your client:

Claude Desktop

Settings → Developer → Edit Config (claude_desktop_config.json):

{
  "mcpServers": {
    "media-context": { "command": "npx", "args": ["-y", "media-context-mcp"] }
  }
}
Cursor

~/.cursor/mcp.json (global) or .cursor/mcp.json (per-project):

{
  "mcpServers": {
    "media-context": { "command": "npx", "args": ["-y", "media-context-mcp"] }
  }
}
VS Code (GitHub Copilot, agent mode)

.vscode/mcp.json — VS Code uses the servers key:

{
  "servers": {
    "media-context": { "command": "npx", "args": ["-y", "media-context-mcp"] }
  }
}
Windsurf

~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "media-context": { "command": "npx", "args": ["-y", "media-context-mcp"] }
  }
}
Cline / Roo Code

cline_mcp_settings.json (the extension's MCP settings):

{
  "mcpServers": {
    "media-context": { "command": "npx", "args": ["-y", "media-context-mcp"] }
  }
}
Kiro

.kiro/settings/mcp.json (project) or ~/.kiro/settings/mcp.json (user):

{
  "mcpServers": {
    "media-context": { "command": "npx", "args": ["-y", "media-context-mcp"] }
  }
}
Gemini CLI

~/.gemini/settings.json:

{
  "mcpServers": {
    "media-context": { "command": "npx", "args": ["-y", "media-context-mcp"] }
  }
}
Zed

settings.json — Zed uses context_servers:

{
  "context_servers": {
    "media-context": { "command": { "path": "npx", "args": ["-y", "media-context-mcp"] } }
  }
}
Codex CLI

~/.codex/config.toml:

[mcp_servers.media-context]
command = "npx"
args = ["-y", "media-context-mcp"]
JetBrains AI Assistant

Settings → Tools → AI Assistant → Model Context Protocol → Add, then use command npx with args -y media-context-mcp.

Tip: in Claude Code you can install it as a plugin instead — run /plugin marketplace add vishalguptax/media-context-mcp, then /plugin install media-context. To share with a team, install per-project: --scope project (writes .mcp.json) or commit a .cursor/mcp.json in the repo.

2 · Install the local helpers

One command sets up everything the server uses, via your OS package manager:

npx media-context-mcp setup          # core: keyframes, links, on-screen text
npx media-context-mcp setup --audio  # also enable transcription

The server finds the helpers automatically afterward — no extra configuration. Run check_media_deps to see what's ready, and setup --uninstall to remove them. (Install by hand →)

3 · Ask

“Summarize demo.mp4.”

✨ Capabilities

VideoKeyframe overview, full-size stills, scene detection, or a dense filmstrip that catches split-second glitches
AudioSpeech turned into text — clips, voice notes, meetings, podcasts
ImagesThe picture, plus the exact text shown on screen
AnywhereLocal files or links — YouTube, Vimeo, and 1000+ sites
PrivateRuns on your machine. No API keys, no uploads
EfficientA long clip becomes a couple of images, not hundreds

🎞️ Modes

analyze_media auto-detects audio and images. For video, choose how frames are sampled:

ModeBest for
sheet (default)A cheap overview — frames tiled into one or two contact sheets
framesDetail on specific moments — individual full-size stills
scenesSlide decks & static screencasts — only scene-change frames
filmstripCatching a sub-second UI glitch — a dense, near-native-rate strip

💬 Examples

Just ask in plain language — the assistant picks the right options.

You askWhat you get
“Summarize demo.mp4.”A quick overview from sampled keyframes
“What error does bug.mp4 show at the end?”The exact on-screen text, read back
“Walk me through the UI flow in onboarding.mov.”Step-by-step from scene-change frames
“Transcribe standup.m4a and list action items.”A local transcript
“Summarize https://youtu.be/… with the transcript.”Fetched and transcribed
“Read the error in this screenshot crash.png.”The picture plus its exact text
“Find where the slider in ui.mp4 flickers ~0:06.”The exact frame of a sub-second glitch

🧰 Tools

ToolWhat it does
analyze_mediaTurn a video, audio, or image — file or URL — into model-readable context. Auto-detects the type and supports cropping, time windows, language, and sampling rate.
check_media_depsReport which capabilities are ready on this machine.

Every call runs locally and cleans up after itself.

⚙️ Options

Your assistant fills these in for you, but you can steer it (“use filmstrip mode”, “crop to the toolbar”).

Full analyze_media parameters
ParamDefaultDescription
sourceLocal file path (video/audio/image) or http(s) URL
contextA note framing the analysis; echoed atop the summary
detailhigh = readable stills for screen recordings; low = cheap overview
modesheetsheet · frames · scenes · filmstrip
formatwebpwebp (smallest) · jpeg · png (crisp text)
maxFrames30Upper bound on sampled frames
grid5Tiles per row/column for contact-sheet modes
scale320Per-frame width in px — lower = fewer tokens
sceneThreshold0.4Scene-change sensitivity (scenes mode)
fpsautoExplicit sampling rate; pair high with filmstrip
crop{x,y,width,height} (pixels, or 0–1 fractions) to zoom a region
stripRows18Tiles per image in filmstrip mode
startSec / endSecRestrict to a time window
transcriptfalseAlso produce a transcript (video)
whisperModelsmalltiny · base · small · medium · large
ocrfalseExtract on-screen text
ocrLangengLanguage code(s), e.g. eng+deu
ocrPsm3Page-segmentation: 3 auto · 6 block · 11 sparse
detectJumpsfalseTrack an on-screen number and report jump-back glitches with timestamps
maxDurationSec3600Reject URL downloads longer than this
maxFileSizeMb500Abort a URL download past this size

Worked recipes for each are in the usage guide.

❓ FAQ

Can an LLM watch a video? Not directly — models take images and text, not video. This server turns the video into frames and a transcript it can read.

Does anything get uploaded? No. Everything runs on your machine; no keys, no cloud.

Which clients work? Any MCP client — Claude Code, Claude Desktop, Cursor, VS Code, Windsurf, Cline, Kiro, Gemini CLI, JetBrains, Zed, Codex.

Does it handle YouTube and other links? Yes.

How much does it cost? It's free and open source.

📋 Requirements

Node.js 18+, on Windows, macOS, or Linux. The one-time npx media-context-mcp setup installs everything else.

🛠️ Development

npm install
npm run build
npm test

Issues and PRs welcome — see the usage guide for the architecture.

📄 License

Apache-2.0 © Vishal Gupta