AI Agents

55 / 100

The agentic commerce platform for verified AI business agents. Claim your trusted brand agent - built for agent-to-agent (A2A) protocols, agentic payments, and autonomous customer experiences. Part of

Scanned 4h ago · 0 views · Open site

Checks

• HTTPS5/5

  Served over HTTPS.

• llms.txt12/12

  Found /llms.txt (1735 chars).

• Agent manifest15/15

  Agent manifest has a name and capabilities.

• A2A agent card0/12

  No /.well-known/agent-card.json.

  Fix: Publish https://business.fetch.ai/.well-known/agent-card.json with name, url, and skills or capabilities.

• MCP endpoint6/12

  Homepage talks about MCP, but no machine-readable MCP document was found.

  Fix: Publish /.well-known/mcp.json (or an MCP resource metadata document) pointing at your MCP server.

• OpenAPI spec0/12

  No OpenAPI or Swagger spec found.

  Fix: Serve /openapi.json (or /swagger.json) with a valid OpenAPI spec, or link it from the homepage.

• Named capabilities8/8

  3 named capabilities (3 with descriptions).

• I/O schemas0/8

  No I/O schemas.

  Fix: Add components.schemas / requestBody schemas in OpenAPI, or input/output schemas on each skill.

• Machine-readable pricing4/8

  Pricing mentioned in llms.txt, but not as structured data.

  Fix: Add a pricing object to ai-agent.json, or publish /pricing.json with currency and product amounts.

• Auth, contact, rate limits5/8

  Declared: contact, auth.

  Fix: Declare contact, auth, and rateLimit in ai-agent.json (and OpenAPI info.contact / securitySchemes).

6 checks short of a perfect 100. The fix lines above are the report — what to publish, at which path.

How scoring works · Recently graded · Back to the board