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Summary
This guide connects AI clients to VideoVector tools for media retrieval, prompt execution, workflow inspection, and playground validation.
Use the published package names
Use these package and environment identifiers when installing or configuring the MCP server:
- package:
@videosearch/mcp-server - command:
videosearch-mcp - environment variables:
VIDEOSEARCH_*
Install and run in stdio mode
npm install -g @videosearch/mcp-server
VIDEOSEARCH_API_KEY=sk_live_... videosearch-mcp
Use generated config when available
If your application uses the public MCP helper endpoints, use:
GET /api/v2/mcp/statusGET /api/v2/mcp/configGET /api/v2/mcp/toolsPOST /api/v2/mcp/playground
Those helpers are useful for setup, inspection, and client testing before a full deployment.
Choose the correct transport
- Use stdio for local agent environments such as Claude Desktop or Cursor.
- Use HTTP when the MCP server needs a network addressable endpoint, readiness probes, host/origin controls, or session controls.
For platform-specific configuration details, continue to the dedicated Claude Desktop, Cursor, or Custom / HTTP transport pages.
Related documentation
The VideoVector MCP docs show how AI clients can browse indexes, run prompts, search media evidence, inspect workflow resources, and validate available tools.
Claude Desktop uses the stdio transport. The public helper endpoint `/mcp/config` generates the same `mcpServers` JSON shape documented here.
Custom clients can use the same stdio server config as Claude Desktop and Cursor or connect to a remote HTTP deployment when the MCP server must be network addressable.