taxonomy_search"NCBI taxonomy ID for [organism]" / "taxid for [species]" / "look up [Latin name] in NCBI taxonomy" — search NCBI Taxonomy via UniProt's mirror. Returns taxonomic IDs you can use as organism_id filters in search (9606 = human, 10090 = mouse, 7227 = D. melanogaster, etc).
| Name | Required | Description | Default |
|---|---|---|---|
| size | No | ||
| query | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| facets | No | Search facets | |
| results | No | Array of taxonomy entries |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds context about the data source (UniProt mirror) and return value (taxonomic IDs). No contradictions. It does not describe additional behavioral traits like caching or rate limits, but with annotations the burden is lower.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, using only two sentences and including practical examples. It is front-loaded with example queries and gets straight to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has only two parameters and an output schema exists, the description covers the core purpose and usage context. However, the lack of parameter explanation (especially 'size') leaves a gap. It is complete enough for a simple lookup tool but could mention that 'size' controls the number of results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has two parameters: query (required) and size (optional), but the schema itself has no descriptions (0% coverage). The description provides examples of queries but does not explicitly explain the 'size' parameter or its effect. The examples in the schema are not part of the description text, so parameter semantics are inadequately covered.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches NCBI Taxonomy via UniProt's mirror to retrieve taxonomic IDs for given species names. It provides examples and explains the output's purpose in conjunction with the sibling tool 'search'. This distinguishes it from other search tools by its specific role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains that returned IDs can be used as organism_id filters in the 'search' tool, providing a clear use case. However, it does not explicitly mention when not to use this tool or discuss alternatives among the sibling tools, so some guidance is implied but not exhaustive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.