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Oliver's mTOR Atlas

Oliver's mTOR Atlas

by open-mtor-atlas
OverviewSchemaSourceRelated ServersDiscussionsAdmin

Get one entity

get_entity
Read-onlyIdempotent

Retrieve any mTOR research entity by name, ID, or synonym, along with its linked studies and every pathway relation.

Instructions

One 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.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "entity": "<entity>"
    },
    "name": "get_entity"
  }
}

Input Schema

NameRequiredDescriptionDefault
entityYese.g. "mTORC1", "Rheb", "rapamycin"
studies_limitNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.2

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds genuine return-behavior context beyond that: studies come back as short cards truncated to the first studies_limit, and pathway relations as one-line claims. It does not mention pagination beyond the limit or error behavior for unresolved names.

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?

Two tight sentences with no filler; the core resource is front-loaded and the return shape follows. The parenthetical entity-type list is slightly bulky but earns its place by telling the agent what counts as an entity.

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?

With no output schema, the description carries the burden of describing returns and does so adequately (short cards for studies, one-line claims for pathways). The only gap is what happens when the name is ambiguous or unmatched, which an agent resolving identifiers would want to know.

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

Parameters4/5

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

Schema coverage is 50%: the entity param has example values but studies_limit has only default/min/max and no prose. The description compensates by clarifying that studies_limit caps which studies are returned ('first studies_limit') and by stating that entity accepts an id, a name, or a synonym, which the schema does not say.

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 resource (one entity) and enumerates the entity kinds it covers (gene/protein, complex, drug, disease, process), plus what comes back: linked studies and pathway relations. It is clearly distinguishable from search_entities by the singular scope, though it never names the sibling explicitly.

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?

The description notes that the tool accepts an id, a name, or a synonym, which hints at input flexibility, but it gives no when-to-use versus when-not guidance and never points to search_entities or find_relations as alternatives. An agent must infer the retrieval-vs-search split on its own.

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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