video-research-mcp

Ask questions across recordings and documents, then inspect the source frames, transcripts and clips behind the answer. The server exposes 120 MCP tools for video, audio and image operations, document analysis, web and academic research, and saved knowledge. Agent workflows connect those tools into a research or production task.

Use it in Codex, Claude Code, or any client that supports stdio Model Context Protocol. Gemini handles the main analysis and research routes; local tools inspect and transform source files. Optional providers and runtimes extend that core.

Open the interactive user guide (Dutch): from your problem to an approach. Search the function map or choose a task to see its tools, prerequisites and steps. The English user documentation also covers setup problems and examples. Describe your problem in your MCP client in ordinary language to begin.

Release · npm · PyPI · Source

Release candidate: 0.8.0-rc.6 (PyPI 0.8.0rc6). The links above identify the exact packages and immutable source tag. Check the release notes and each route's prerequisites before installing. The npm prerelease channel is next. Local-model qualification is outside this API-first release. Stable 0.7.1 predates the native Codex plugin and expanded media surface.

From source material to a useful result

Work	Tools to start with	What to inspect
Question a recording	video_analyze, video_create_session, video_continue_session	Source timestamps, the answer and supporting material
Analyze a long recording in stages	media_info, video_analyze_windows, job_status	Requested intervals, dry-run plan, execution limits and retained outcomes
Prepare audio or transcripts	audio_transcribe, audio_clip_export, audio_dsp_analyze	Caption or model provenance, source timing and exported audio
Inspect images or export media	image_read, image_crop, image_ocr, video_frame, video_clip_export	Source bytes, selected region or interval, output files and manifests
Compare documents or investigate a topic	content_analyze, research_document, research_plan, research_web	Citations, contradictions, missing evidence and job status
Generate images or short video	Separate explainer image and video APIs	Pinned sources, a current operator quote, explicit operations and saved decoded files; provider quality remains unqualified
Search previous work	knowledge_ingest, knowledge_search, knowledge_ask	Stored records and retrieval provenance; requires Weaviate

For example, ask your client:

Compare ~/recordings/design-review.mp4 with ~/docs/requirements.pdf.
Identify decisions that change a requirement. Cite recording timestamps and
relevant document pages, distinguish explicit decisions from interpretation,
and flag anything the sources do not establish.

Workflows combine tools; individual MCP calls return their own results. Source hashes identify bytes, and export manifests retain how an artifact was produced. Model timestamps, citations and interpretations still need checking against the original material. Sampling a recording does not establish complete coverage.

Install

You need Python 3.11+, uv with uvx on your client's PATH, and a Gemini API key for Gemini requests. Plugin installation also needs Node.js 22+ and npm. Install FFmpeg/FFprobe for local media inspection, frame extraction and clip exports. Other operations may need an optional dependency or configured backend.

By default, the server reads process environment variables first, then ~/.config/video-research-mcp/.env, then defaults. Project installations can select a separate credential file. Add your key to the shared file for the routes below, keeping any existing settings:

GEMINI_API_KEY=your-gemini-api-key

Keep the file private (chmod 600 ~/.config/video-research-mcp/.env). Codex plugin servers receive a filtered environment, so this file is the reliable credential route there. Provider analysis sends source material to the configured service and can incur usage charges. A selected analysis interval does not necessarily limit the uploaded file.

Codex: native plugin

The plugin supplies 26 skills and the version-pinned research server. Historical RC3 observation: on 2026-10-06, the selected Codex 0.160.1 RC3 installation and fresh-session restart loaded the research tools and packaged skills. This is historical RC3 evidence. Follow the verification steps below for the version you install. The native route does not run the Claude workflow installer.

For a new installation, save this catalog as ~/.local/share/video-research-mcp/.agents/plugins/marketplace.json, creating its parent directories if needed:

{
  "name": "video-research",
  "interface": { "displayName": "Video Research" },
  "plugins": [
    {
      "name": "video-research",
      "source": {
        "source": "npm",
        "package": "video-research-mcp",
        "version": "0.8.0-rc.6"
      },
      "policy": { "installation": "AVAILABLE", "authentication": "ON_INSTALL" },
      "category": "Productivity"
    }
  ]
}

codex plugin marketplace add ~/.local/share/video-research-mcp
codex plugin add video-research@video-research
codex plugin list --json

Start a fresh Codex session. Check that video-research@video-research is enabled, its source is npm at 0.8.0-rc.6, and the server's tools are available.

For an existing installation, use the native plugin and migration guide. Back up local plugin edits before reinstalling: Codex replaces its managed cache. A manual mcp_servers.video-research entry can hide the plugin server. In the historical RC1 check on Codex 0.160.0, this also occurred when the entry was disabled; the guide describes the specific configuration to remove.

Claude Code: workflow installer

npx video-research-mcp@0.8.0-rc.6 --global

This installs slash commands, skills and agents into ~/.claude/, registers the research server in ~/.claude.json, and creates a credential template if needed. Set the key, restart Claude Code and inspect /mcp. Use /gr:advisor to select a workflow, or /gr:video, /gr:research and /gr:analyze to start directly.

Use --local for project scope and set the key in ./.config/video-research-mcp/.env; this replaces the shared credential-file route. Use --global --check to inspect the global installation. Updates preserve modified workflow files and custom configuration. See installer options and recovery for scope, checkpoints and rollback.

Other MCP clients: server only

Use your client's stdio registration format. A typical JSON entry is:

{
  "mcpServers": {
    "video-research": {
      "command": "uvx",
      "args": ["video-research-mcp==0.8.0-rc.6"]
    }
  }
}

This connects the same tools; agent workflows are installed separately. Python package filenames use the normalized spelling 0.8.0rc6.

Verify your first connection

Ask the client to call infra_configure with no arguments. It returns the running configuration without making an analysis request. Then try a tool on material you can inspect yourself. A successful connection verifies setup; checking the returned evidence verifies the particular result.

Configure only what the task needs

Setting or addition	Use it for
GEMINI_MODEL, GEMINI_FLASH_MODEL	Select supported primary and auxiliary models
YOUTUBE_API_KEY	YouTube metadata, comments and playlists; otherwise uses the Gemini key
GEMINI_SESSION_DB	Persist video sessions in SQLite; unset means in-memory sessions
WEAVIATE_URL, WEAVIATE_API_KEY	Store and retrieve research across sessions
MLFLOW_TRACKING_URI and the tracing extra	Trace tool execution; GEMINI_TRACING_ENABLED=false disables optional tracing
LOCAL_FILE_ACCESS_ROOT	Restrict supported local-file operations to a directory

Research works without Weaviate. When storage is configured, write-through errors are non-fatal; verify the stored record when persistence matters. The knowledge-store guide covers embeddings, collections and optional query dependencies. For a manually configured server, retain the version pin when adding extras, for example uvx 'video-research-mcp[tracing,agents]==0.8.0-rc.6'. The full runtime configuration lives in ServerConfig.

Image edits, OCR, speech inference, Blender, FreeCAD and local model services have additional runtime or backend requirements. Installing the plugin does not install those runtimes, model weights or provider accounts. Inspect the relevant skill and its prerequisites before using an optional integration.

For video production, the separate explainer companion exposes 39 tools, including direct HTTP image and text/frame-video generation and an optional external CLI/rendering pipeline; the scene-agent companion exposes two tools for scene-code generation. Neither is required for research. Production skills also provide workflows for narration, image generation, clip generation and assembly.

Generate an image or a short video

Connect the explainer companion separately. Its RC4 candidate (0.2.2rc4 on PyPI) adds direct HTTP routes for text-to-image, image editing, image translation and video from text, a first frame, or first plus last frames. These routes need the companion's generation extra, an existing project with pinned script/scene files, explicit regional DashScope configuration and current pinned price/access and quote declarations. Video output checks also need FFmpeg/ffprobe. They run without the upstream video_explainer CLI.

Follow the image lifecycle or video lifecycle. Obtain actual human authority for source submission and spending before setting spend_authorized=true; that field records an input acknowledgement and does not authenticate anyone or impose a provider billing cap. Keep the returned job ID. Use explainer_image_generation_finalize for captured synchronous images, explainer_image_generation_poll for translation and explicit image recovery, or explainer_generation_poll for video, each with a bounded authorized operation. Core job_status rejects both generated-media job kinds.

Saved hashes and complete decode checks qualify the selected file bytes. Live provider access, image identity/style fidelity, creative quality and full security review remain open. S2V/HappyHorse successor modes are optional and await separate source acceptance; the disabled raw Qwen process integration is a separate route. Stock search, local ASR intake timing and the retained renderer timing failure remain limits.

Inspect and extend

• Tool implementations: exact parameters and behavior. Your client's discovered MCP schemas describe the running version.
• Windowed video analysis: dry-run budgets, continuation, upload limits and retained partial results.
• Contributing: source setup and checks.
• Security policy: local access, provider boundaries and reporting.
• Changelog: changes in this candidate.

The selected RC3 native check covered the installed baseline and restart, with 124 cache files. Fresh npm network acquisition versus reuse of the same-version cache remains unknown. Earlier RC1 native and RC2 archive/installer checks remain historical results. Tool discovery does not qualify every optional runtime; live-provider quality and complete comparative acceptance remain open.

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Created by Fausto Albers · Wonder Why. Built with Google Gemini, FastMCP and Pydantic, with optional knowledge and tracing integrations. Project code is MIT licensed; third-party notices cover bundled components with their own terms.