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ZengZichao

SwissBioPics MCP Server

by ZengZichao

search_locations

Search SwissBioPics for subcellular locations and cell types using advanced query syntax to find precise biological matches.

Instructions

Search SwissBioPics for subcellular locations and cell types.

The query supports advanced syntax:

  • spindle body or spindle AND body — both terms must be present (AND)

  • SL-0073 OR chromatophore — either term (OR)

  • "golgi stack" — exact phrase

  • endosome -peroxisome — exclude a term (NOT)

  • bact* — wildcard prefix

  • rhoptri~ — fuzzy search (allows ~2 typos)

  • Parentheses: lumen AND (SL0158 OR wall)

Args: query: Search query string using the syntax described above.

Returns: A formatted summary of matching cell types and their locations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden. It implies a read-only search and notes the return is 'a formatted summary of matching cell types and their locations', but says nothing about auth requirements, result limits, pagination, or error behavior on malformed syntax.

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?

Front-loads the purpose, then itemizes syntax with aligned examples and a short Returns note; every line is scannable and earns its place. The syntax block is long but justified by the 0%-coverage parameter, so it is efficient rather than padded.

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

Completeness4/5

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

An output schema exists, so not explaining return values in detail is acceptable, and the description does mention the summary shape. Combined with exhaustive query-syntax documentation, the agent has enough to invoke correctly; only the missing sibling routing keeps it from a 5.

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?

Schema coverage is 0% (the schema says only 'Query'), so the description must compensate and does so thoroughly: it documents AND/OR/NOT, exact phrases, wildcard prefix, fuzzy matching, and parentheses, each with a concrete example. This is far beyond what the bare string parameter conveys.

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

Purpose4/5

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

States a specific verb and resource ('Search SwissBioPics for subcellular locations and cell types'), so the agent knows exactly what corpus is queried. It does not name a sibling to differentiate from, which matters given seven closely related tools (get_subcellular_locations, get_search_suggestions), so it falls short of a 5.

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

Usage Guidelines2/5

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

No when-to-use or when-not-to-use guidance is given despite seven siblings that overlap heavily (e.g., get_search_suggestions for autocomplete, get_subcellular_locations for browsing). The examples teach query syntax, not tool selection, so the agent must infer the routing itself.

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