get_entityOne entity (gene/protein, complex, drug, disease, process...) with its linked studies as short cards (first studies_limit) and every pathway relation it takes part in as a one-line claim. Accepts an id, a name or a synonym.
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Alias of entity. | |
| entity | No | e.g. "mTORC1", "Rheb", "rapamycin" | |
| studies_limit | No | Maximum 50; a larger value is capped at 50. |
Changes observed during successful MCP inspections.
Input schema / properties / idAdded value: +{
+ "description": "Alias of entity.",
+ "type": "string"
+}Input schema / properties / studies_limit / descriptionAdded value: +"Maximum 50; a larger value is capped at 50."Input schema / properties / studies_limit / maximumPrevious value: -50New value: +9007199254740991Input schema / requiredRemoved value: -[
- "entity"
-]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, so the safety profile is covered. The description usefully adds the shape of the payload (linked studies as short cards, pathway relations as one-line claims) and the studies_limit truncation, but says nothing about ambiguity or error behavior when a name matches multiple entities.
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?
Two sentences, front-loaded with the resource and its scope, with the accepted-key note placed last. Dense but every clause carries information; no filler.
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?
With no output schema, the description does the necessary work of describing the returned payload, which is its main strength. It leaves open what happens with zero arguments (nothing is required) and how ambiguous names are resolved, gaps an agent would hit in practice.
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?
Schema description coverage is 100%, so all three parameters are documented in the schema (including the 50-study cap). The description adds only the clarification that id/name/synonym are interchangeable lookup keys, which is modest value over the schema's own 'Alias of entity' note.
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?
States a specific verb+resource ('One entity') and enumerates the entity types it covers (gene/protein, complex, drug, disease, process), which clearly separates it from the plural search_entities. It stops short of explicitly naming the sibling it is the singular counterpart of, so an agent must infer the split.
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 clause 'Accepts an id, a name or a synonym' implies you call this when you already have a concrete identifier, versus using search_entities to discover one. There is no explicit when-to-use/when-not statement and no guidance on which of the two identifiers to prefer.
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.