Write regression tests that catch recurring bugs in FastMCP changes using pytest. Covers reproducing failures before a fix, testing requests without a network server, and checking outgoing requests while replacing external services with test substitutes.
Write regression tests for FastMCP changes using its pytest fixtures, in-memory clients, and protocol boundaries.
Review the instructions the agent will receive before you install.
Read nearby tests, the testing guide, and the repository's validation requirements first. Extend the owning test module when it remains readable; use a focused module when the existing one is already too large.
For a bug fix, run the regression against unchanged code and confirm it fails for the reported reason, then run it with the fix. An import error or broken fixture is not a reproduced bug. To run a PR's test against main, copy it into a main worktree: pythonpath in pyproject shadows PYTHONPATH. Include supported adjacent behavior that the same branch could change, especially omitted defaults and explicit overrides.
asyncio_mode = "auto" is configured globally.Client(server) for real MCP dispatch without a network server. Use HTTP transport only when network behavior is the subject.mode="legacy" only when the handshake era is the subject.httpx2.MockTransport and assert its bytes, headers, or decoded parameters.tmp_path for files.True from 1: check the resulting type when type preservation matters.inline_snapshot conventions for complex schema assertions. Inspect generated snapshots rather than accepting them blindly.Run focused tests during development, then the full commands required by AGENTS.md before committing. If a failure appears unrelated, reproduce it on the unchanged base; do not call it pre-existing from the test name alone.
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Write and revise FastMCP documentation pages with consistent structure, clear explanations, and runnable code examples. Covers accessibility, link and Python checks, and the publishing steps needed to confirm changes reach the live site.
Discover MCP servers and inspect their available tools from the command line, then invoke operations with typed arguments or JSON. Use local files, remote endpoints, or configured server names, and return structured output for scripts.
Build, extend, or review Python FastMCP servers using documentation for the installed version. Design operations that agents can discover and use, then check input definitions, results, error handling, and representative agent workflows.
Take a selected FastMCP bug from a reproducible failure to a focused fix. Check compatibility, run required validation, prepare a pull request, and follow automated checks and review feedback after publication.
Prepare and publish FastMCP releases, from reviewing changes and crediting contributors to updating changelogs, creating release tags, checking Python package publication on PyPI, and confirming that the documentation site reflects the release.
Evaluate an incoming FastMCP issue and its linked pull requests. Check whether the reported behavior is a supported bug, assess the proposed contribution, and recommend assigning the contributor, declining, or seeking a specific maintainer decision.