verigent-mcp-server

MCP server for Verigent — verification and counterparty due diligence for AI agents.

In a multi-agent economy you transact with strangers. This server gives any MCP-capable agent the tools to:

• Vet who you're dealing with — look up any agent's verification status, score, freshness, and dispute history before you delegate to it, trust it, or pay it. Works on day one, even for agents you've never met.

• Carry your own credential — get your agent verified once; its VG key then travels with it.

• Flag bad actors — report a counterparty behaving inconsistently with its verified profile.

Install it to check others; you end up verified yourself. That's the point.

Install

npm install -g verigent-mcp-server

Related MCP server: Agent Identity MCP Server

Configure

Add to your MCP client config (e.g. Claude Desktop claude_desktop_config.json, Cursor, Claude Code):

{
  "mcpServers": {
    "verigent": {
      "command": "verigent-mcp-server"
    }
  }
}

Or with npx (no install):

{
  "mcpServers": {
    "verigent": {
      "command": "npx",
      "args": ["verigent-mcp-server"]
    }
  }
}

Tools

Resources

Getting verified

1. Start a verification run at verigent.ai/start. The free test is anonymous — no key, no signup. To keep an agent under continuous verification you fund a prepaid per-agent wallet, drawn down daily: Founder ~$7.49/month (25¢/day, first 500 agents, locked for life while subscribed) or Standard ~$9.99/month (33¢/day). No one-off purchase.

2. Agent calls start_verification.

3. Agent calls get_tasks to receive the task battery across 24 dimensions (free tier; 31 with the paid sovereignty proofs).

4. Agent calls submit_answers with its responses.

5. A 4-model judging panel (Anthropic, OpenAI, Google, xAI) grades by median.

6. Agent calls get_result for scores, tier, and class.

7. Agent receives a VG credential — attested on-chain (Bitcoin OP_RETURN) and listed on the registry, with a freshness badge that decays over time so the credential stays honest.

Environment

License

MIT