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ayhammouda

python-docs-mcp-server

search_docs

Read-onlyIdempotent

Search Python documentation by symbol, example, or concept. Filter by version and limit results for focused answers.

Instructions

Search Python documentation. Use kind='symbol' for API lookups (asyncio.TaskGroup), kind='example' for code samples, kind='auto' otherwise. When version is omitted, searches across all versions. Pass the version from each hit's version field to get_docs for consistent results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query - Python symbol (asyncio.TaskGroup) or concept (parse json)
versionNoPython version (e.g. '3.13'). Defaults to latest.
kindNoSearch type. Use 'symbol' for API lookups, 'example' for code samples, 'auto' otherwise.auto
max_resultsNoMaximum number of results to return.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
hitsNoSearch result hits
noteNoInformational note (e.g., limited search mode)
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate read-only, non-destructive, idempotent behavior. The description adds valuable context about cross-version searching and the relationship with get_docs. No contradictions; it complements the annotations well.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four sentences, no redundant information, front-loaded with purpose. Every sentence earns its place, covering purpose, kind usage, version behavior, and downstream workflow. Highly efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (4 parameters, output schema present), the description fully covers how to search effectively and how to integrate with get_docs. The return values are presumably documented in the output schema, so no omission here.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema has 100% coverage with descriptive parameter descriptions. The description adds moderate value by reiterating kind usage and providing version guidance, but it largely overlaps with schema descriptions. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Search Python documentation' as the core function. It distinguishes from sibling tools like get_docs and list_versions by explaining the search behavior and how results feed into get_docs, making the tool's purpose unique and actionable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use each kind argument ('symbol', 'example', 'auto'), explains version omission behavior, and advises on using get_docs for consistent results. This clearly differentiates usage contexts and workflow integration.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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