[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"tool-related-zh-datalayer-jupyter-mcp-server":3},{"items":4,"total":96,"page":97,"pageSize":98},[5,30,46,63,80],{"slug":6,"name":7,"categorySlug":8,"summary":9,"description":10,"categoryName":11,"sourceUrl":12,"homepageUrl":-1,"downloadUrl":13,"cliCommand":-1,"primaryLanguage":-1,"license":-1,"stars":14,"forks":15,"trendScore":16,"qualityScore":16,"supportedClients":17,"clients":20,"tags":27,"installCommand":-1,"configSnippet":-1,"useCases":28,"updatedAt":29},"datalayer-jupyter-mcp-server","datalayer\u002Fjupyter-mcp-server","data-science-ml","🪐 🔧 Model Context Protocol (MCP) Server for Jupyter.","You must configure MCP_TOKEN in your MCP client setup. For setup details, see: https:\u002F\u002Fjupyter-mcp-server.datalayer.tech\u002Fproviders\u002Fjupyter-streamable-http-standalone\u002F#3-configure-your-mcp-client pycrdt is now supported, so installing datalayer_pycrdt is no longer required.\n\nWe're actively developing support for and deployments. If you're using or planning to use Jupyter MCP Server with these platforms, we'd love to hear from you! - 🏢 : Share your deployment setup and requirements - 🌐 : Help us understand your use cases and workflows Join the conversation in our Community page - your feedback will help us prioritize features and ensure these integrations work seamlessly for your needs.\n\n- ⚡ Instantly view notebook changes as they happen. - 🔁 Automatically adjusts when a cell run fails thanks to cell output feedback. - 🧠 Understands the entire notebook context for more relevant interactions. - 📊 Support different output types, including images, plots, and text.","数据科学与机器学习","https:\u002F\u002Fgithub.com\u002Fdatalayer\u002Fjupyter-mcp-server","https:\u002F\u002Fgithub.com\u002Fdatalayer\u002Fjupyter-mcp-server\u002Farchive\u002FHEAD.zip",1198,0,95,[18,19],"claude-desktop","cursor",[21,24],{"slug":18,"name":22,"summary":23,"count":15},"Claude Desktop","支持本地 MCP 配置的桌面客户端。",{"slug":19,"name":25,"summary":26,"count":15},"Cursor","常与开发类 MCP Server 搭配使用的 AI 代码编辑器。",[8],[],"2026-08-30T08:26:56.552824",{"slug":31,"name":32,"categorySlug":8,"summary":33,"description":34,"categoryName":11,"sourceUrl":35,"homepageUrl":-1,"downloadUrl":36,"cliCommand":-1,"primaryLanguage":-1,"license":-1,"stars":37,"forks":15,"trendScore":38,"qualityScore":38,"supportedClients":39,"clients":40,"tags":43,"installCommand":-1,"configSnippet":-1,"useCases":44,"updatedAt":45},"formulahendry-mcp-server-spec-driven-development","formulahendry\u002Fmcp-server-spec-driven-development","Spec-Driven Development MCP Server, not just Vibe Coding","Model Context Protocol (MCP) server that facilitates spec-driven development workflows by providing structured prompts for generating requirements, design documents, and code following a systematic approach.\n\nThis MCP server enables developers to follow a structured spec-driven development approach by providing prompts that guide you through:\n\n1. - Create detailed requirements documents using the EARS (Easy Approach to Requirements Syntax) format 2. - Generate design documents based on requirements 3. - Generate implementation code based on design documents\n\n- : Follows a clear progression from → → - : Uses industry-standard EARS format for requirements documentation - : Integrates seamlessly with MCP-compatible tools and environments\n\nInstall the MCP server in VS Code using below buttons:\n\nAlternatively, you can add configuration in mcp.json:\n\nInstall the MCP server in Cursor using below button:\n\nAlternatively, you can add configuration in mcp.json:","https:\u002F\u002Fgithub.com\u002Fformulahendry\u002Fmcp-server-spec-driven-development","https:\u002F\u002Fgithub.com\u002Fformulahendry\u002Fmcp-server-spec-driven-development\u002Farchive\u002FHEAD.zip",432,92,[18,19],[41,42],{"slug":18,"name":22,"summary":23,"count":15},{"slug":19,"name":25,"summary":26,"count":15},[8],[],"2026-09-11T01:35:05.922458",{"slug":47,"name":48,"categorySlug":8,"summary":49,"description":49,"categoryName":11,"sourceUrl":50,"homepageUrl":-1,"downloadUrl":51,"cliCommand":52,"primaryLanguage":-1,"license":-1,"stars":53,"forks":15,"trendScore":54,"qualityScore":54,"supportedClients":55,"clients":56,"tags":59,"installCommand":52,"configSnippet":60,"useCases":61,"updatedAt":62},"finite-sample-rmcp","finite-sample\u002Frmcp","- A Model Context Protocol (MCP) server with across 11 categories and from systematic CRAN task views.","https:\u002F\u002Fgithub.com\u002Ffinite-sample\u002Frmcp","https:\u002F\u002Fgithub.com\u002Ffinite-sample\u002Frmcp\u002Farchive\u002FHEAD.zip","docker run -e RMCP_HTTP_HOST=0.0.0.0 -e RMCP_HTTP_PORT=8000 rmcp:latest",206,91,[18,19],[57,58],{"slug":18,"name":22,"summary":23,"count":15},{"slug":19,"name":25,"summary":26,"count":15},[8],"{\n  \"mcpServers\": {\n    \"rmcp\": {\n      \"command\": \"rmcp\",\n      \"args\": [\"start\"]\n    }\n  }\n}",[],"2026-07-23T01:51:34.868769",{"slug":64,"name":65,"categorySlug":8,"summary":66,"description":66,"categoryName":11,"sourceUrl":67,"homepageUrl":-1,"downloadUrl":68,"cliCommand":69,"primaryLanguage":-1,"license":-1,"stars":70,"forks":15,"trendScore":71,"qualityScore":71,"supportedClients":72,"clients":73,"tags":76,"installCommand":69,"configSnippet":77,"useCases":78,"updatedAt":79},"geeksfino-kb-mcp-server","geeksfino\u002Fkb-mcp-server","A Model Context Protocol (MCP) server implementation powered by txtai, providing semantic search, knowledge graph capabilities, and AI-driven text processing through a standardized interface.","https:\u002F\u002Fgithub.com\u002Fgeeksfino\u002Fkb-mcp-server","https:\u002F\u002Fgithub.com\u002Fgeeksfino\u002Fkb-mcp-server\u002Farchive\u002FHEAD.zip","uvx kb-mcp-server@0.2.6 --embeddings \u002Fpath\u002Fto\u002Fknowledge_base --host localhost --port 8000",71,90,[18,19],[74,75],{"slug":18,"name":22,"summary":23,"count":15},{"slug":19,"name":25,"summary":26,"count":15},[8],"{\n  \"mcpServers\": {\n    \"kb-server\": {\n      \"command\": \"\u002Fyour\u002Fhome\u002Fproject\u002F.venv\u002Fbin\u002Fkb-mcp-server\",\n      \"args\": [\n        \"--embeddings\", \n        \"\u002Fpath\u002Fto\u002Fknowledge_base.tar.gz\"\n      ],\n      \"cwd\": \"\u002Fpath\u002Fto\u002Fworking\u002Fdirectory\"\n    }\n  }\n}",[],"2026-08-11T05:12:36.356991",{"slug":81,"name":82,"categorySlug":8,"summary":83,"description":83,"categoryName":11,"sourceUrl":84,"homepageUrl":-1,"downloadUrl":85,"cliCommand":86,"primaryLanguage":-1,"license":-1,"stars":87,"forks":15,"trendScore":71,"qualityScore":71,"supportedClients":88,"clients":89,"tags":92,"installCommand":86,"configSnippet":93,"useCases":94,"updatedAt":95},"mrdgbot-lanhu-mcp","mrdgbot\u002Flanhu-mcp","mcp-lanhu 是蓝湖的 MCP 服务器，装上之后 都能直接连接蓝湖。AI 可以读取设计稿、提取 HTML\u002FCSS、解析 PRD、下载切图，全程不用离开编辑器。","https:\u002F\u002Fgithub.com\u002Fmrdgbot\u002Flanhu-mcp","https:\u002F\u002Fgithub.com\u002Fmrdgbot\u002Flanhu-mcp\u002Farchive\u002FHEAD.zip","npx -y mcp-lanhu",104,[18,19],[90,91],{"slug":18,"name":22,"summary":23,"count":15},{"slug":19,"name":25,"summary":26,"count":15},[8],"{\n  \"mcpServers\": {\n    \"lanhu\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"mcp-lanhu\"],\n      \"env\": { \"LANHU_COOKIE\": \"your_cookie_here\" }\n    }\n  }\n}",[],"2026-08-13T02:47:55.678988",18,1,5]