Agentic.ai Directory

Independent directory of agentic AI tools — search, compare & recommend via MCP. Read-only.

我該用這個嗎

品質與安全性

A
說明品質
98%
結構描述完整度
85%
命名品質
94%
汙染風險
100%
權限相符程度
100%
協定合規性
100%

根據工具定義與協定合規性的自動化分析。

上下文成本

~1,925Token(工具定義)
~1.4 KB典型回應大小
中等的注意力影響(128k 上下文的 1.50%)

這是每次將伺服器的工具載入模型上下文時所消耗的約略 token 數量。數量越高,可用於其他工作的注意力就越少。

安裝

一鍵安裝

將以下內容加入你的 `claude_desktop_config.json` 檔案:

{
  "mcpServers": {
    "agentic-directory": {
      "url": "https://agentic.ai/mcp"
    }
  }
}

遠端端點

https://agentic.ai/mcpstreamable-http

它能做什麼

工具清單

工具(10)

🟢 唯讀🟡 寫入🔴 刪除⚪ 未知
🟢search_listings(query, category, cohort, openSource, mcpSupport, ...)

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.

輸入結構描述

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Search query (e.g. 'code review', 'open source coding agent')"
    },
    "category": {
      "type": "string",
      "description": "Filter by category slug (e.g. 'coding-agents', 'general-purpose-agents')"
    },
    "cohort": {
      "type": "string",
      "enum": [
        "PEOPLE",
        "TEAMS"
      ],
      "description": "Filter by cohort: PEOPLE (individual tools) or TEAMS (team/enterprise tools)"
    },
    "openSource": {
      "type": "boolean",
      "description": "Filter to open-source tools only"
    },
    "mcpSupport": {
      "type": "boolean",
      "description": "Filter to tools with MCP (Model Context Protocol) support"
    },
    "deploymentModel": {
      "type": "string",
      "enum": [
        "CLOUD",
        "SELF_HOSTED",
        "HYBRID",
        "ON_DEVICE"
      ],
      "description": "Filter by deployment model"
    },
    "autonomyLevel": {
      "type": "string",
      "enum": [
        "COPILOT",
        "SEMI_AUTONOMOUS",
        "FULLY_AUTONOMOUS"
      ],
      "description": "Filter by autonomy level"
    },
    "minScore": {
      "type": "number",
      "minimum": 0,
      "maximum": 36,
      "default": 1,
      "description": "Minimum agenticness score (default 1 to exclude unscored/junk entries, set to 0 to include all)"
    },
    "limit": {
      "type": "number",
      "minimum": 1,
      "maximum": 50,
      "default": 10,
      "description": "Max results to return"
    }
  },
  "required": [
    "query"
  ],
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢semantic_search(query, category, cohort, openSource, deploymentModel, ...)

Search 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.

輸入結構描述

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Natural language search query"
    },
    "category": {
      "type": "string",
      "description": "Filter by category slug"
    },
    "cohort": {
      "type": "string",
      "enum": [
        "PEOPLE",
        "TEAMS"
      ],
      "description": "Filter by cohort"
    },
    "openSource": {
      "type": "boolean",
      "description": "Filter by open source status (true/false)"
    },
    "deploymentModel": {
      "type": "string",
      "enum": [
        "CLOUD",
        "ON_DEVICE",
        "SELF_HOSTED",
        "HYBRID"
      ],
      "description": "Filter by deployment model"
    },
    "mcpSupport": {
      "type": "boolean",
      "description": "Filter by MCP (Model Context Protocol) support"
    },
    "autonomyLevel": {
      "type": "string",
      "enum": [
        "ASSISTED",
        "SEMI_AUTONOMOUS",
        "FULLY_AUTONOMOUS"
      ],
      "description": "Filter by autonomy level"
    },
    "minScore": {
      "type": "number",
      "minimum": 0,
      "maximum": 36,
      "description": "Minimum agenticness score (0-36)"
    },
    "limit": {
      "type": "number",
      "minimum": 1,
      "maximum": 20,
      "default": 5,
      "description": "Max results to return"
    }
  },
  "required": [
    "query"
  ],
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢get_listing(slug)

Get 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'.

輸入結構描述

{
  "type": "object",
  "properties": {
    "slug": {
      "type": "string",
      "description": "The listing slug (e.g. 'cursor', 'claude-code', 'openclaw')"
    }
  },
  "required": [
    "slug"
  ],
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢compare_listings(slug1, slug2)

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.

輸入結構描述

{
  "type": "object",
  "properties": {
    "slug1": {
      "type": "string",
      "description": "First tool's slug (e.g. 'cursor')"
    },
    "slug2": {
      "type": "string",
      "description": "Second tool's slug (e.g. 'claude-code')"
    }
  },
  "required": [
    "slug1",
    "slug2"
  ],
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢get_agenticness_details(slug)

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.

輸入結構描述

{
  "type": "object",
  "properties": {
    "slug": {
      "type": "string",
      "description": "The listing slug"
    }
  },
  "required": [
    "slug"
  ],
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢list_categories

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.

輸入結構描述

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢get_category(slug)

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.

輸入結構描述

{
  "type": "object",
  "properties": {
    "slug": {
      "type": "string",
      "description": "The category slug (e.g. 'coding-agents', 'general-purpose-agents')"
    }
  },
  "required": [
    "slug"
  ],
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢list_tags

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.

輸入結構描述

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢list_recent(limit)

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.

輸入結構描述

{
  "type": "object",
  "properties": {
    "limit": {
      "type": "number",
      "minimum": 1,
      "maximum": 50,
      "default": 10,
      "description": "Number of listings to return"
    }
  },
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢recommend_tools(question, constraints)

Get 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"

輸入結構描述

{
  "type": "object",
  "properties": {
    "question": {
      "type": "string",
      "description": "Natural language description of what you need. Be specific about your use case, team size, budget, deployment preferences, etc."
    },
    "constraints": {
      "type": "object",
      "properties": {
        "category": {
          "type": "string",
          "description": "Category slug to filter by (e.g. 'coding-agents', 'customer-support')"
        },
        "openSource": {
          "type": "boolean",
          "description": "Require open source tools"
        },
        "selfHosted": {
          "type": "boolean",
          "description": "Require self-hosted/on-premise deployment"
        },
        "mcpSupport": {
          "type": "boolean",
          "description": "Require MCP (Model Context Protocol) support"
        },
        "maxResults": {
          "type": "number",
          "minimum": 1,
          "maximum": 10,
          "default": 5,
          "description": "Number of recommendations to return"
        },
        "minRelevanceScore": {
          "type": "integer",
          "minimum": 0,
          "maximum": 100,
          "description": "Drop recommendations whose relevanceScore (0-100) is below this floor. Use to suppress weak matches."
        }
      },
      "additionalProperties": false,
      "description": "Optional structured constraints to narrow results"
    }
  },
  "required": [
    "question"
  ],
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}

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