mcp server
Agentic.ai Directory
Independent directory of agentic AI tools — search, compare & recommend via MCP. Read-only.
Description as published by the maintainer. Source
- version 2.0.0
- active
- retrieval
active — Registry entry last updated 2026-06-29. Dashed tags are derived by ZBS Index from the published description, not stated by the maintainer.
What this server can do
10 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.
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. Required: slug1, slug2.
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. Required: slug.
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. Required: slug.
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'. Required: slug.
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.
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.
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.
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" Required: question.
search_listings(limit, query, cohort, category, minScore, mcpSupport, openSource, autonomyLevel, deploymentModel)- 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. Required: query.
semantic_search(limit, query, cohort, category, minScore, mcpSupport, openSource, autonomyLevel, 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. Required: query.
Last successful function declaration observed on . Source: https://agentic.ai/mcp. We list what the server declared; we do not call any of these functions.
Endpoint status observed on . Source: https://agentic.ai/mcp.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| Latest published version | 2.0.0 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2026-06-29 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| First listed in the MCP Registry | 2026-06-29 | Date this server was first published to the official MCP Registry. Not a usage or quality measure. | point in time | Model Context Protocol | |
| mcp tools declared | 10 tools | Number of functions the server itself declared when asked to list them. This is what the server offers an agent, not a measure of how well any of them work. | as of probe | agentic.ai | |
| mcp endpoint status | ok | The server listed 10 functions when asked. | as of probe | agentic.ai |
Where to get it
Also from u00dxk2
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Agentic News
— repository gone
AI-powered news intelligence — 21 tools for personalized monitoring, briefings, and semantic search
This record as data
Every field on this page, with its source and observation date, is in the catalog JSON. Fetch the whole kind at once instead of parsing this HTML.
GET /api/v1/entries/mcp_server.json