INDIVIDUAL MCP TOOL

validate_ai_output

The merge gate for AI-written CODE: returns a binary approve/reject verdict with veto power — e.

verificate.ainone authenticationAvailability not checked

LIVE ENDPOINT

https://mcp.verificate.ai/mcp

No auth detected

Connect to this endpoint to inspect the live schema for validate_ai_output and invoke it with your own arguments.

{}

Inferred read-only · medium confidence · heuristic, not a guarantee.

No write-capable action terms were found; this is not proof that invocation has no side effects.

CONNECT WITH APPROVAL

Review this server and its permissions before adding it. Secret placeholders must be set locally.

Codex

~/.codex/config.toml

[mcp_servers.verificate-mcp-http]
url = "https://mcp.verificate.ai/mcp"
enabled = true

Claude Code

.mcp.json

{
  "mcpServers": {
    "verificate-mcp-http": {
      "type": "http",
      "url": "https://mcp.verificate.ai/mcp"
    }
  }
}

Claude Desktop

Settings → Connectors → Add custom connector

Name: verificate-mcp-http
Remote MCP URL: https://mcp.verificate.ai/mcp

Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.

Cursor

.cursor/mcp.json

{
  "mcpServers": {
    "verificate-mcp-http": {
      "url": "https://mcp.verificate.ai/mcp"
    }
  }
}

Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code

{
  "servers": {
    "verificate-mcp-http": {
      "type": "http",
      "url": "https://mcp.verificate.ai/mcp"
    }
  }
}

Generic MCP

Client-specific MCP configuration

{
  "name": "verificate-mcp-http",
  "transport": "streamable-http",
  "url": "https://mcp.verificate.ai/mcp"
}

MCP Inspector

Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.

validate_plan — The gate for PLANS, designs and specs — run BEFORE any code is written, the cheapest place to catch a bad design.
analyze_code — Advisory deep-dive on existing code — scores and findings, deliberately NO pass/fail verdict, so it never blocks an agent.
generate_code — Generate code and gate it in one step: an LLM writes the implementation, then the same protection engine as validate_ai_output vets it — retrying generation when the gate rejects.