# Agentic.ai Directory (remote · agentic.ai)

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

- Trust score: 70/100 (medium)
- Change this week: +4
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-03

## Components

- remote · `agentic.ai`: 70/100 (this document), [markdown](https://verifymcp.io/servers/u00dxk2-agentic-directory/agentic.md), [page](https://verifymcp.io/servers/u00dxk2-agentic-directory/agentic)

## Channel facts

- Endpoint: `https://agentic.ai/mcp`
- Transports: `streamable-http`
- Auth: `none`
- Version: `2.0.0`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-03.

- **Endpoint Security**: 63/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - Authorisation not fully verified: no authorisation is required to call this server, and 10 tool(s) never declared a destructiveHint. The MCP spec treats an absent hint as destructive by default, so we cannot call this surface safe.
  - HTTPS is enforced; there's no plaintext access path.
  - The HSTS (Strict-Transport-Security) header is present.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 79/100
  - AI-judged instruction clarity (excellent).
  - Context-footprint check failed: tool/resource definitions use about 1171 tokens (~117/item across 10 items; 10 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 27/100
  - Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### Claude

```bash
claude mcp add --transport http u00dxk2-agentic-directory https://agentic.ai/mcp
```

### Codex

```toml
[mcp_servers.u00dxk2-agentic-directory]
url = "https://agentic.ai/mcp"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "u00dxk2-agentic-directory": {
      "type": "remote",
      "url": "https://agentic.ai/mcp",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add u00dxk2-agentic-directory --url https://agentic.ai/mcp --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  u00dxk2-agentic-directory:
    url: "https://agentic.ai/mcp"
```

### Other

```json
{
  "mcpServers": {
    "u00dxk2-agentic-directory": {
      "type": "http",
      "url": "https://agentic.ai/mcp"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-08-03 (score 70, +1)

No change was recorded against any check on this day. Stability & Change Management went from 23 to 27. That category is still filling its 30-day observation window: 7 days of observed history at the previous scan, 8 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-31 (score 69, +1)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-30 (score 68, 0)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-29 (score 68, +1)

No change was recorded against any check on this day. Stability & Change Management went from 7 to 10. That category is still filling its 30-day observation window: 2 days of observed history at the previous scan, 3 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-28 (score 67, +1)

No change was recorded against any check on this day. Stability & Change Management went from 3 to 7. That category is still filling its 30-day observation window: 1 days of observed history at the previous scan, 2 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-27 (score 66, 0)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-26 (score 66)

First indexed and scored.

## MCP tools (10)

### `search_listings` (~232 tokens)

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.

Input parameters:

- `autonomyLevel` (string): Filter by autonomy level
- `category` (string): Filter by category slug (e.g. 'coding-agents', 'general-purpose-agents')
- `cohort` (string): Filter by cohort: PEOPLE (individual tools) or TEAMS (team/enterprise tools)
- `deploymentModel` (string): Filter by deployment model
- `limit` (number): Max results to return
- `mcpSupport` (boolean): Filter to tools with MCP (Model Context Protocol) support
- `minScore` (number): Minimum agenticness score (default 1 to exclude unscored/junk entries, set to 0 to include all)
- `openSource` (boolean): Filter to open-source tools only
- `query` (string, required): Search query (e.g. 'code review', 'open source coding agent')

### `semantic_search` (~193 tokens)

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.

Input parameters:

- `autonomyLevel` (string): Filter by autonomy level
- `category` (string): Filter by category slug
- `cohort` (string): Filter by cohort
- `deploymentModel` (string): Filter by deployment model
- `limit` (number): Max results to return
- `mcpSupport` (boolean): Filter by MCP (Model Context Protocol) support
- `minScore` (number): Minimum agenticness score (0-36)
- `openSource` (boolean): Filter by open source status (true/false)
- `query` (string, required): Natural language search query

### `get_listing` (~107 tokens)

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'.

Input parameters:

- `slug` (string, required): The listing slug (e.g. 'cursor', 'claude-code', 'openclaw')

### `compare_listings` (~98 tokens)

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.

Input parameters:

- `slug1` (string, required): First tool's slug (e.g. 'cursor')
- `slug2` (string, required): Second tool's slug (e.g. 'claude-code')

### `get_agenticness_details` (~114 tokens)

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.

Input parameters:

- `slug` (string, required): The listing slug

### `list_categories` (~60 tokens)

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.

### `get_category` (~79 tokens)

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.

Input parameters:

- `slug` (string, required): The category slug (e.g. 'coding-agents', 'general-purpose-agents')

### `list_tags` (~65 tokens)

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.

### `list_recent` (~60 tokens)

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.

Input parameters:

- `limit` (number): Number of listings to return

### `recommend_tools` (~163 tokens)

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"

Input parameters:

- `constraints` (object): Optional structured constraints to narrow results
- `question` (string, required): Natural language description of what you need. Be specific about your use case, team size, budget, deployment preferences, etc.

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/u00dxk2-agentic-directory/agentic#diagnostics

## Score history

- 2026-08-03: 70
- 2026-08-02: 69
- 2026-08-01: 69
- 2026-07-31: 69
- 2026-07-30: 68
- 2026-07-29: 68
- 2026-07-28: 67
- 2026-07-27: 66
- 2026-07-26: 66

## Links

- Remote endpoint: https://agentic.ai/mcp
- Repository: https://github.com/u00dxk2/agentic-directory
- Website: https://agentic.ai/developers
- Changelog RSS feed: https://verifymcp.io/servers/u00dxk2-agentic-directory/agentic/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/u00dxk2-agentic-directory/agentic/changelog.json
- HTML version of this page: https://verifymcp.io/servers/u00dxk2-agentic-directory/agentic