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83 / 100

Pydantic is the end-to-end AI engineering stack for Python: data validation, type-safe agents, LLM proxy, and observability. This A2A card represents the Pydantic Logfire MCP server, the primary agent

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Checks

• HTTPS5/5

  Served over HTTPS.

• llms.txt12/12

  Found /llms.txt (15427 chars).

• Agent manifest5/15

  JSON exists at the agent manifest path, but it is missing required fields.

  Fix: Publish https://pydantic.dev/.well-known/ai-agent.json with name, description, capabilities, contact, auth, and pricing.

• A2A agent card12/12

  A2A agent card with skills or capabilities.

• MCP endpoint12/12

  Discoverable MCP metadata or endpoint.

• OpenAPI spec12/12

  Valid OpenAPI/Swagger document.

• Named capabilities8/8

  7 named capabilities (7 with descriptions).

• I/O schemas8/8

  Found 10 schema signals.

• 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).

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

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