# Share a PydanticAI Agent's Output — Typed Result, Real URL Canonical: https://commareports.com/agents/share-pydantic-ai-output Published: 2026-09-14 > PydanticAI gives you a validated output type. Make the report a URL in that type: add an @agent.tool that publishes, or attach Comma's MCP server. # Share what a PydanticAI agent produced PydanticAI's whole argument is that an agent's output should be a validated object rather than a hopeful string. That argument extends one step further than most people take it: if the deliverable is a report, the validated object should contain the report's *address*, not the report. ## A tool, from a function signature ```python from pydantic_ai import Agent, ModelRetry import httpx, os agent = Agent("claude-sonnet-5", output_type=Analysis) @agent.tool_plain def publish_report(title: str, html: str) -> str: """Publish an HTML report and return its shareable URL.""" if ".") r = httpx.post( "https://commareports.com/api/v1/reports", headers={"Authorization": f"Bearer {os.environ['COMMA_API_TOKEN']}"}, json={"title": title, "html": html}, ) r.raise_for_status() return r.json()["url"] ``` The `ModelRetry` is the part worth copying. A model that hands you a fragment instead of a document gets told why and tries again — far better than publishing a page that renders as three orphaned `
`s and finding out from the reader. ## Put the URL in the type ```python from pydantic import BaseModel, HttpUrl class Analysis(BaseModel): headline: str confidence: float report_url: HttpUrl ``` Now "did this run actually produce something shareable?" is answered by validation rather than by inspection. An agent that skipped the tool cannot satisfy the type, and the failure happens in your process instead of in someone's inbox. It is also the cheap version. The document lives at the URL; your program handles a short object — the argument in [context budgeting for AI reports](/agents/context-budgeting-ai-reports). ## Or attach the MCP server ```python from pydantic_ai.mcp import MCPServerStreamableHTTP comma = MCPServerStreamableHTTP( "https://commareports.com/api/mcp", headers={"Authorization": f"Bearer {os.environ['COMMA_API_TOKEN']}"}, ) agent = Agent("claude-sonnet-5", toolsets=[comma], output_type=Analysis) ``` Publishing, updating and comment reading all arrive at once, from the same endpoint your editor uses — see [MCP setup](/mcp). ## Worth knowing - **Dependencies carry the token.** If you use `deps_type`, put the API token there rather than reading the environment inside the tool — it makes the agent testable without a live token. - **One report id per recurring job.** Store it and update, so a nightly agent keeps one address and one comment history. - **`reports:write`, plus `comments:read` for revisions** — see [scoped tokens for AI agents](/agents/scoped-tokens-for-ai-agents). - **5 MB per report body.** ## Try it Free — unlimited reports, commenters and revisions. **[Read the API reference →](/docs/api)** ### Related - [Where should my agent post?](/agents/where-should-my-agent-post) · [Let an agent respond to comments](/agents/let-an-agent-respond-to-comments) - [Share OpenAI Agents SDK output](/agents/share-openai-agents-sdk-output) · [Share a LlamaIndex workflow's output](/agents/share-llamaindex-output) - [The API](/docs/api) · [MCP setup](/mcp)