io.github.u00dxk2由 GitHub 帳號 u00dxk2 發布v2.0.0更新於 Oct 25, 2026
Independent directory of agentic AI tools — search, compare & recommend via MCP. Read-only.
發布方自己的服務：agentic.no
一個唯讀的遠端 MCP 伺服器，介接獨立的代理式 AI 工具目錄，讓助理搜尋、瀏覽、比較工具並取得推薦。
Web executable，透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。
把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式，或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南，先向你展示發布者、端點和登入方式，經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。
閱讀 https://sourceweft.com/mcp/io.github.u00dxk2%2Fagentic-directory/install.md，並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前，先告訴我它的發布者、端點和登入方式，等我確認。不要把 API 金鑰寫進命令或我會提交的檔案；問我金鑰應從哪裡取得。把它新增到你客戶端的 mcpServers 設定中。
{
"mcpServers": {
"agentic-ai-directory": {
"type": "http",
"url": "https://agentic.ai/mcp"
}
}
}該儲存庫沒有 README。
Search for agentic AI tools by keyword query with optional filters. Use this for keyword-based search. For natural language queries like 'something that automates email', use semantic_search instead. For browsing all tools in a category, use get_category instead.
limitquery必填cohortcategoryminScoremcpSupportopenSourceautonomyLeveldeploymentModelSearch for AI tools using natural language with AI-powered semantic matching. Best for conceptual queries like 'something that automates my email workflow'. Supports structured filters to narrow results (e.g., openSource + deploymentModel). For exact name/keyword searches, use search_listings instead. For comparing specific tools, use compare_listings.
limitquery必填cohortcategoryminScoremcpSupportopenSourceautonomyLeveldeploymentModelGet full details for one specific AI tool by its slug — includes features, pricing, agenticness scores, and structured attributes. Use this when you know the exact tool slug. To find a slug, use search_listings first. For comparing two tools, use compare_listings. Note: null on boolean fields means 'unknown', false means 'confirmed no'.
slug必填Compare exactly two AI tools side-by-side. Returns structured field matrix and 'Choose A if... Choose B if...' verdict. Use this when a user wants to decide between two specific tools. For finding tools first, use search_listings or semantic_search.
slug1必填slug2必填Get the full agenticness evaluation breakdown: 9 dimensions (action capability, autonomy, planning, adaptation, state continuity, reliability, interoperability, safety, operator sovereignty) scored 0-4 each (max 36, Agenticness rubric v3.1) with evidence-based reasoning. Use this for deep analysis of one tool's AI agent capabilities. For a quick score, get_listing includes the overall score. For comparing scores, use compare_listings.
slug必填Get all categories with descriptions and listing counts. Use this to discover what categories exist before filtering. To get listings IN a category, use get_category with the slug. Categories are split into PEOPLE (individual use) and TEAMS (team/enterprise) cohorts.
無需輸入參數。
Get all published listings in one specific category, sorted by agenticness score. Use this to browse a category. To see all categories first, use list_categories. To search across ALL categories, use search_listings or semantic_search.
slug必填Get all tags grouped by type (pricing, platform, capability, deployment, model, autonomy, use-case). Use this to discover available filter values. Tags can be used as filters in search_listings. This does NOT return listings — use search_listings or get_category for that.
無需輸入參數。
Get the most recently added AI tool listings, sorted by creation date. Use this to see what's new. For finding specific tools, use search_listings. For browsing by category, use get_category.
limitGet AI-powered tool recommendations for a specific need. This is the recommended starting point — describe what you're looking for in natural language and get curated, ranked results with explanations. Handles search, filtering, scoring, and ranking in one call. Use this instead of chaining search_listings + get_listing + compare_listings. Examples: - "best coding agent for a small startup on a budget" - "open source alternative to Cursor for VS Code" - "autonomous customer support agent with MCP support" - "self-hosted data analysis tool for enterprise"
question必填constraints已滿足適用檢查項的 75%
該評分衡量此收錄條目的完整程度，依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價，也不表示伺服器安全或目前可用：可連通性是帶日期的檢查結果，評分也不包含安裝量或使用者評價。
請宣告包含 README 的 GitHub 儲存庫，或在 OAuth 受保護資源後設資料中提供 resource_documentation。
請在儲存庫或註冊中心條目中宣告授權條款。
no.agentic官方發布者
一個遠端 MCP 端點，協助助理依模型尋找 AI 推論的 GPU 賣家，並依價格由低到高排序，透過 x402 按次付費。
academy.ase官方發布者
使用編碼代理建立軟體的實踐，每項實踐都附帶一個可在你的程式碼庫中檢查的測試。AI 翻譯
space.hf.hoyant-su-agentic-rl官方發布者
讓助理依監督方式、critic 與任務設定篩選代理強化學習方法，並取得來源連結與 BibTeX。
由 GitHub 帳號 tlq5l 發布
本機 stdio MCP 伺服器，讓只能讀文字與圖片的助理檢查影片檔：聯絡表、轉錄、剪接點、響度與影音同步檢查。
由 GitHub 帳號 kinnister 發布
唯讀、不執行任何操作的 MCP 伺服器，向助理提供 agentic-os 的治理、SDLC 與品質工程方法論。