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kmaneesh

BioPython MCP Server

by kmaneesh

clear_entrez_cache

Clear cached Entrez results to update stale data and reduce disk usage. Specify a database (e.g., 'pubmed') or leave empty to clear all caches.

Instructions

Clear cached Entrez results.

The caching system stores Entrez query results to reduce API calls and improve response times. Use this tool to clear stale cache data.

Args: database: Database name to clear (empty string clears all databases)

Returns: Dictionary containing: - success: Whether operation succeeded - cleared: Number of cache files removed - database: Database cleared (or "all" if empty string) - cache_location: Path to cache directory

Examples: >>> clear_entrez_cache() # Clear all caches >>> clear_entrez_cache("pubmed") # Clear only PubMed cache >>> clear_entrez_cache("gene") # Clear only Gene cache

Notes: - Caching is optional and controlled via use_cache parameter - Default TTL: 1 hour for searches, 7 days for fetches - Cache stored in ~/.biopython-mcp/cache/ - Cached data includes search results and summaries

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
databaseNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

No annotations are provided, but the description fully discloses behavior: it clears cache, returns a dictionary with success/cleared count/database cleared/cache location, and notes on caching optionality, TTL, and storage.

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

Conciseness4/5

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

The description is well-structured with sections (Args, Returns, Examples, Notes) and front-loaded purpose. While slightly lengthy, each section provides value; minor conciseness improvements possible.

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?

The description covers all necessary aspects: purpose, parameters, return values (despite output schema presence), examples, and behavioral notes. No gaps remain for a simple one-parameter tool.

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

Parameters5/5

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

The single parameter 'database' is explained: 'Database name to clear (empty string clears all databases)'. Examples illustrate usage. This adds significant meaning beyond the schema's default type.

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 'Clear cached Entrez results' and explains the caching system. It uniquely identifies the tool's purpose among siblings, none of which deal with cache clearing.

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

Usage Guidelines4/5

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

The description advises using the tool to clear stale cache data and provides notes on caching behavior, but lacks explicit when-to-use vs. alternatives. However, no alternatives exist for cache clearing.

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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