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Gemini Media Analysis

MCP Video Recognition Server provides tools for image, audio, and video analysis using Google's Gemini AI. Built with TypeScript and the MCP SDK, it offers three main tools: image recognition for describing visual content, audio recognition for transcription and analysis, and video recognition for understanding video content. The server supports both stdio and SSE transport methods, includes file caching to improve performance, and handles the complexities of waiting for video processing to complete. It's particularly useful for applications requiring media content analysis, automated descriptions, or accessibility features without requiring direct integration with Google's APIs.

Cognium trust score

91%

Tier

Verified

Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.

Scan details: Circle-IR · 2026-09-28 · Appeal

View full trust & usage report →

Metadata

Version: 1.0.0
Skill type: atomic
Execution layer: mcp-remote
Category: media
Source: PulseMCP
Repository: github.com/mario-andreschak/mcp_video_recognition
Author type: human
Last scanned: 2026-09-28
Updated: 2026-09-28

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MCP

Resolve Gemini Media Analysis from your agent

Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.

One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.

claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp

Swap --scope user for --scope project to commit it to .mcp.json.

Your client Same endpoint everywhere; only the config key differs. The full list is in the descriptor.

Claude Desktop · Settings → Connectors → Add custom connector

https://api.skillsregistry.net/mcp

Paste the URL as the connector endpoint. No authentication.

ChatGPT · Settings → Connectors → Create (developer mode) → MCP server URL

https://api.skillsregistry.net/mcp

Authentication: none. Works in chat and deep research — the server exposes the connector search and fetch tools.

Codex CLI · ~/.codex/config.toml

[mcp_servers.skillsregistry]
url = "https://api.skillsregistry.net/mcp"