mcp-python-conventions-taudelta

MCP server code conventions

The Python inside a stdio-transport MCP server. Split out of python-conventions-taudelta on 2026-08-31, which keeps the general design defaults — this skill owns only what is different because the code is an MCP server, and those differences are not stylistic: two of the three are protocol correctness.

Not about shipping. Entry points, uv tool install, claude mcp add and scope selection belong to mcp-server-shipping; this is what the code does once it runs.

MCP-stdio logging discipline

Scope: stdio-transport MCP servers only (the *-polite-mcp family) — not applicable to a repo that has no MCP server of its own.

• Snippet: references/snippets/mcp-tool-boundary.py
• Default: never a bare print() in server package code. Route all logging through the stdlib logging module, explicitly configured to write to stderr at startup (or defer to FastMCP's own configure_logging(), which already defaults there).
• Why: the MCP stdio spec is unambiguous — a server MUST NOT write anything to stdout that isn't a valid MCP message; a single stray print() or a dependency's stdout-bound log handler corrupts the JSON-RPC stream. stderr is the sanctioned outlet for everything, logs included.
• Don't: trust that "no print() in my code" is sufficient — a dependency that logs to stdout on its own initiative isn't caught by explicit stderr configuration of your own logging. The robust check is exercising the real stdio transport end-to-end, not code review alone.
• Model default: overrides — sharply, not a style nudge. This is protocol-specific knowledge a model has no general-Python reason to know; without it, a model reaches for print() debugging exactly as it would in any other script, silently breaking the server.

Error handling at the MCP tool boundary

Scope: stdio-transport MCP servers only, same as above.

• Snippet: references/snippets/mcp-tool-boundary.py
• Default: at the point an internal exception is about to cross back to the client, decide deliberately what's safe to expose — either re-raise as fastmcp.exceptions.ToolError with an explicit, hand-written message, or let a plain exception raise (FastMCP's default already surfaces it, unmasked, to the client). Never assume str(exc) of an arbitrarily caught exception is safe by default, especially inside a broad per-item except Exception (a legitimate pattern for isolating one bad item in a batch call — just don't let its caught exception's message reach the client unreviewed).
• Why: FastMCP's default (mask_error_details=False) already includes full exception detail in the client-facing response — this isn't an opt-in risk, it's the out-of-the-box behavior. The same shape as this skill's SecretStr caveat: a broad safety switch doesn't sanitize text you deliberately choose to expose.
• Don't: flip mask_error_details=True project-wide as a blanket fix — it suppresses legitimately useful validation detail (a bad argument, a batch-size violation) that plain raise ValueError(...) call sites rely on being visible to the calling agent. Prefer the finer-grained per-message ToolError choice.
• Model default: overrides. A model doesn't know ToolError exists or that FastMCP unmasks exceptions by default unless told — without this, it either leaves exceptions to propagate as-is (today's actual state in this family) or reaches for a blanket masking flag, both worse than the deliberate per-boundary choice.

MCP tool docstrings

Scope: any function decorated as an MCP tool (@mcp.tool() in this family). A genuinely distinct concern from general docstring style — no general docstring-content rule exists elsewhere in this skill to extend.

• Default: write the docstring to Anthropic's tool-definition bar, not PEP 257's — what the tool does and how it differs from its nearest sibling by name, when to use/not use it, where each non-obvious parameter's value comes from, response shape/size caveats, at least 3–4 sentences, more for a complex tool. See references/rationale.md §11 for the concrete template and this family's own strongest real examples.
• Why: the docstring becomes the wire-level Tool.description an LLM client reads at inference time to decide whether/how to call the tool — a weak one causes wrong-tool-picked, wrong-arguments, or never-invoked failures, a correctness cost paid by every future call, not a comprehension-speed one the way a weak human-facing docstring is.
• Escalate to: Annotated[x, Field(description=...)] for per-parameter descriptions once free-form prose isn't enough (so the JSON-Schema inputSchema itself carries them); annotations= (readOnlyHint/destructiveHint/etc.) on any tool with real side effects, since clients use it to decide when to skip or require confirmation prompts.
• Model default: overrides. A model's default docstring instinct is PEP 257's — a concise one-line summary — which is actively worse here; the entire point of this section is that the bar for an LLM-facing description is different from, not a stricter version of, ordinary docstring style.

Full rationale

See references/rationale.md — the sources for the stdout constraint, the error-taxonomy reasoning, and the docstring-as-contract argument.

Starter snippet

references/snippets/mcp-tool-boundary.py is a runnable sketch of the tool-boundary error handling described here.

Editing this skill

This file is copied into ~/.agents/skills/mcp-python-conventions-taudelta at install time, never symlinked, so editing the deployed copy is local drift — the exact thing this skill exists to prevent, and it reaches no other machine. Edit the source in the repo this was installed from, push, and re-run skills add <that source> --global --skill mcp-python-conventions-taudelta to refresh every project's copy. If you installed it from someone else's repo rather than your own fork, the source is theirs: open an issue or a pull request there instead.