[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"cc-detail-mcp-servers-rippermercs-tensorfeed":3},{"id":4,"slug":5,"type":6,"title":7,"summary":8,"description_md":9,"install_command":10,"install_method":10,"source_url":11,"source_type":12,"github_repo":13,"github_stars":14,"github_last_commit_at":15,"language":16,"tags":17,"use_cases":24,"status":25,"submitted_by_ip":10,"approved_at":26,"view_count":27,"copy_count":27,"created_at":28,"updated_at":28,"quality_score":29,"discovered_via":30},"e1fa380a-affa-43d3-b8ec-eedab707b959","rippermercs-tensorfeed","mcp_server","TensorFeed MCP Server","An MCP server for TensorFeed.ai data and AI ecosystem intelligence.","TensorFeed.ai provides real-time AI ecosystem intelligence, including news, provider status, model pricing, benchmarks, and agent directory data.\n\nThe README says the fastest way to use it with Claude Desktop, Claude Code, Cursor, Cline, Continue, Zed, Goose, and other stdio MCP clients is the official MCP server. The actual MCP server lives in a separate repository, `RipperMercs\u002Ftensorfeed-mcp`, and this repo links to it as the dedicated surface.\n\nThe README includes a Claude Desktop MCP config example using `npx -y @tensorfeed\u002Fmcp-server`. It also notes that the server has 22 tools, with free and paid capabilities, and that the package is published on npm as `@tensorfeed\u002Fmcp-server`.\n\nThis repository itself is the main TensorFeed product and API hub, with docs, endpoints, SDKs, and dataset links, but the Claude Code-relevant resource here is the MCP integration.",null,"https:\u002F\u002Fgithub.com\u002FRipperMercs\u002Ftensorfeed","github","RipperMercs\u002Ftensorfeed",2,"2026-07-16T19:05:46+00:00","en",[18,19,20,21,22,23],"mcp","claude-code","ai-data","api","news","pricing",[],"approved","2026-07-17T04:00:34.398+00:00",0,"2026-07-17T04:00:34.418531+00:00",7,"awesome-list"]