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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.

🚀 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:

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

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

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

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

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

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

~/.codeium/windsurf/mcp_config.json:

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

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

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

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

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

~/.gemini/settings.json:

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

settings.json — Zed uses context_servers:

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

~/.codex/config.toml:

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

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.”

Related MCP server: local-agent-senses

✨ Capabilities

Video

Keyframe overview, full-size stills, scene detection, or a dense filmstrip that catches split-second glitches

Audio

Speech turned into text — clips, voice notes, meetings, podcasts

Images

The picture, plus the exact text shown on screen

Anywhere

Local files or links — YouTube, Vimeo, and 1000+ sites

Private

Runs on your machine. No API keys, no uploads

Efficient

A long clip becomes a couple of images, not hundreds

🎞️ Modes

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

Mode

Best for

sheet (default)

A cheap overview — frames tiled into one or two contact sheets

frames

Detail on specific moments — individual full-size stills

scenes

Slide decks & static screencasts — only scene-change frames

filmstrip

Catching a sub-second UI glitch — a dense, near-native-rate strip

💬 Examples

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

You ask

What 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

Tool

What it does

analyze_media

Turn 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_deps

Report 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”).

Param

Default

Description

source

—

Local file path (video/audio/image) or http(s) URL

context

—

A note framing the analysis; echoed atop the summary

detail

—

high = readable stills for screen recordings; low = cheap overview

mode

sheet

sheet · frames · scenes · filmstrip

format

webp

webp (smallest) · jpeg · png (crisp text)

maxFrames

30

Upper bound on sampled frames

grid

5

Tiles per row/column for contact-sheet modes

scale

320

Per-frame width in px — lower = fewer tokens

sceneThreshold

0.4

Scene-change sensitivity (scenes mode)

fps

auto

Explicit sampling rate; pair high with filmstrip

crop

—

{x,y,width,height} (pixels, or 0–1 fractions) to zoom a region

stripRows

18

Tiles per image in filmstrip mode

startSec / endSec

—

Restrict to a time window

transcript

false

Also produce a transcript (video)

whisperModel

small

tiny · base · small · medium · large

ocr

false

Extract on-screen text

ocrLang

eng

Language code(s), e.g. eng+deu

ocrPsm

3

Page-segmentation: 3 auto · 6 block · 11 sparse

detectJumps

false

Track an on-screen number and report jump-back glitches with timestamps

maxDurationSec

3600

Reject URL downloads longer than this

maxFileSizeMb

500

Abort 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

Available Tools

2 tools
analyze_mediaAnalyze a video, audio, or image file or URLA

Turn a local media file or URL (video, audio, or image) into compact context a model can read — fully local, no paid APIs. Video: montage frames (mode 'sheet', cheapest default), individual stills ('frames'), or scene changes ('scenes'); add transcript and/or ocr. Audio: speech transcript. Image: the picture plus optional OCR. For app/screen recordings use detail:'high' + ocr:true. To catch a transient UI glitch (a flicker/jump lasting <1s), use mode:'filmstrip' with a narrow startSec/endSec window, a high fps (10–15), and a crop around the affected control — it stacks dense frames so you can spot a frame whose value disagrees with the visual. Use the cheap default for everything else. Pass context to frame the analysis.

Inputs: source (required), context, detail, mode, +19 more.

check_media_depsCheck media tool dependenciesA

Report which external binaries (ffmpeg, ffprobe, yt-dlp, whisper, tesseract) are available. Call this first if analyze_media fails with a missing-binary error.

Inputs: no named parameters.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A4.7/5.0

    Scored across 2 tools

    Disambiguation5/5

    The two tools have completely distinct purposes: analyze_media handles media content analysis, while check_media_deps checks for required external binaries. There is no overlap or ambiguity.

    Naming Consistency5/5

    Both tool names follow a consistent verb_noun pattern using snake_case (analyze_media, check_media_deps), making them predictable and easy to understand.

    Tool Count4/5

    With only two tools, the set is minimal but appropriate for a focused utility server. The main tool is comprehensive, and the second tool provides essential support. A slightly larger set might allow more granular operations, but the current count is not problematic.

    Completeness5/5

    The analyze_media tool covers video, audio, and image analysis comprehensively with multiple modes and options. The check_media_deps tool fills the essential dependency-checking role. No obvious gaps are present for the server's stated purpose.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

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