data-ai MCP Server
MCP server for searching and retrieving Claude Agent Skills using vector search
Discovered via unknown and last synced 3mo ago.
1. Install the package
uvx claude-skills-mcp
2. Add to claude_desktop_config.json
{
"mcpServers": {
"claude-skills-mcp": {
"command": "npx",
"args": [
"claude-skills-mcp"
]
}
}
}Config file location: ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) / %APPDATA%\Claude\claude_desktop_config.json (Windows)
AI engineers and product developers building Claude-powered agents who need quick access to pre-built skills and capabilities. Platform architects designing multi-agent systems benefit from discovering reusable skill components via semantic search. DevOps and ML engineers integrating Claude agents into production pipelines can leverage this to standardize skill discovery across teams.
Search vector embeddings to find existing Claude Agent Skills matching your agent's requirements without manually browsing documentation. Accelerates development by identifying compatible capabilities already proven in production.
Index your organization's custom Claude Skills into the MCP server, enabling team-wide discovery and preventing duplicate skill development. Maintains consistency across multiple agent projects.
Rapidly assemble agent prototypes by querying for skills semantically similar to natural language requirements. Test capability combinations before committing to full implementation.
Embed this MCP server into your agent initialization pipeline to auto-recommend skills based on agent purpose and configured tools. Reduces manual skill selection overhead.
The MCP server uses vector embeddings for semantic search over Claude Agent Skills. Exact embedding model and indexing backend details depend on your deployment configuration. Check the server documentation for supported embedding providers.
Requirements vary by deployment. The server implements MCP protocol standard communication, but vector search indexing may depend on external embedding services. Verify infrastructure dependencies in your setup documentation.
Data freshness and skill ingestion pipelines depend on your MCP server instance configuration. Most deployments support adding custom skills through explicit indexing or API ingestion. Consult your server administrator about skill management workflows.
This is an MCP server that works within the Model Context Protocol ecosystem. Integration with your Claude API setup depends on your client's MCP support. Ensure your Claude client (like Claude Code) has MCP capabilities enabled.