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Which MCP servers are AgentCV's own, from the official registry and from asking its own domain, whether they answer, and what they offer. A program checked each of these, nobody copied them from a product page.

read 2026-11-04

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Whose server it is
  • Registry nameai.agentcv/registryverified in the MCP registry

The registry name sits under agentcv.ai. The registry only lets a publisher use that namespace after proving control of the domain through DNS or HTTP.

When we asked itchecked 2026-11-04
  • Stateanswerschecked 2026-11-04
  • Tools6
  • Server calls itselfagentcv
  • Server version1.0.0
  • Protocol version2025-06-18

On 2026-11-04 the server answered initialize and tools/list without a sign-in. First answer in 106 ms.

Should an agent connect itNot proven either way yet
  • Whether its tools do the product's job has not been judged yet.
  • Checked on 1 of the 7 days it takes to judge reliability.

Said by rules from the measurements above. The likely first call is a model's pick from the tool list; read its description before relying on it.

Measured dailydaily checks: 1, the first on 2026-11-04
  • INITE MCP scoreafter a weeka score needs 7 daily checks: 1 so far
  • Answeredmeasuring1 of the 7 daily checks it takes to print a share
  • Median first answer175 ms
  • Space in an agent's context≈ 1,444 tokensthe definitions of all its tools (6), which an agent carries on every turn
  • Tool definitionsA · 100 of 100
  • Typed results6 of 6 toolsdeclared outputSchema: results come typed, read once
  • Every tool passes all six checks.

Worth a look

None of the five warning signs in these definitions.

A program checks the server once a day: initialize and tools/list, no model. Tokens are the definitions' length at about four characters a token. The grade averages six checks of every tool's name, description, schema and annotations; it says how well the tools are described, not whether they work. The score weighs what was measured and nothing else: answering (25%), doing the product's job (25%), definitions (20%), context (10%), use (10%) and how readily a client connects (10%). A part that was not measured is left out, and a hidden instruction caps the score at 40. The state of vendors' MCP servers: method and numbers →

Tools it offers6 tools · read 2026-11-04
  • search_teams

    Search the public AgentCV registry of AI agent teams. Returns public teams only, in the site’s default order: operated teams first, then reference designs (designs documented from papers, framework docs or vendor material that no one is…

  • get_team

    The public profile of one AgentCV team, as its page shows it: layer and its notice (curated teams are documented by AgentCV from public sources and are not endorsed by the team), the reference-design label, owner, trust tier, topology…

  • list_use_cases

    The use-case hubs of agentcv.ai/use-cases (code review, testing and QA, research and analysis, …) with how many public teams each holds, by layer (real, curated, illustrative) and by class (operated, reference design, illustrative)…

  • list_platforms

    The platform hubs of agentcv.ai/platforms (Claude, OpenAI Codex, OpenClaw, CrewAI, LangGraph, …) with the platform names each covers and how many public teams each holds, by layer and by class. AgentCV is independent and not affiliated…

  • get_registration_schema

    The agentcv.team.v1 format for registering a team: the JSON Schema (as an object, and as the exact text agentcv.ai/agentcv-team.schema.json serves) and the self-contained prompt from agentcv.ai/register/with-agent that tells an agent how…

  • validate_team_profile

    Check an agentcv.team.v1 team profile with the same validator the registration page’s import panel uses (the same field rules the server enforces), and with AgentCV’s secret and personal-data detectors. Returns the errors, the warnings…

How to connect

Add the server to your MCP client config. Claude Desktop, Cursor and most other clients read this shape:

{
  "mcpServers": {
    "registry": {
      "type": "http",
      "url": "https://agentcv.ai/mcp"
    }
  }
}

Add it

Claude Code, in a terminal

claude mcp add --transport http agentcv https://agentcv.ai/mcp

Add to CursorAdd to VS Code

claude.ai, ChatGPT and other clients: add https://agentcv.ai/mcp as a custom connector in the settings.

Each line is something a program found when it went looking: the registry entry, the server's own answer, a spec that parses. A missing line means we did not find it, not that it does not exist.