entitySingle node by curie (e.g. "MONDO:0007947").
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Node curie identifier | |
| name | No | Entity name | |
| xrefs | No | Cross-reference identifiers | |
| category | No | Biolink category | |
| description | No | Entity description | |
| provided_by | No | Data sources providing this entity |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "id": "MONDO:0007947"
+ },
+ {
+ "id": "HP:0000118"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "description": "Single entity node details from Monarch Initiative",
+ "properties": {
+ "category": {
+ "description": "Biolink category",
+ "type": "string"
+ },
+ "description": {
+ "description": "Entity description",
+ "type": "string"
+ },
+ "id": {
+ "description": "Node curie identifier",
+ "type": "string"
+ },
+ "name": {
+ "description": "Entity name",
+ "type": "string"
+ },
+ "provided_by": {
+ "description": "Data sources providing this entity",
+ "items": {
+ "type": "string"
+ },
+ "type": "array"
+ },
+ "xrefs": {
+ "description": "Cross-reference identifiers",
+ "items": {
+ "type": "string"
+ },
+ "type": "array"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, indicating a safe, non-mutating, repeatable lookup. The description adds no behavioral context beyond the input format, so it does not contradict annotations but also does not enhance transparency beyond what annotations provide.
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 one short sentence fragment, extremely concise with no wasted words. It is front-loaded with the core purpose. However, it is so terse that it omits usage guidance and context, so it loses a point for under-specification.
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's simplicity (one parameter, output schema present, annotations present), the description covers the basic lookup purpose. However, it does not address when to use this over siblings like 'search' or 'entity_profile', and lacks any mention of return behavior. The output schema covers return values, but the missing usage guidance makes it only minimally complete.
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 0%, so the description must compensate. It does by explicitly stating that 'id' is a CURIE and providing an example. This adds meaning beyond the bare schema property type 'string', although the schema examples also illustrate the format. The description clarifies the expected identifier scheme, which is valuable.
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 states the tool returns a single node identified by a CURIE, e.g., 'MONDO:0007947'. This specifies the resource type (node) and the input format (CURIE), which is more specific than the title alone. However, it lacks an explicit verb like 'retrieve' or 'fetch', and does not clearly differentiate from sibling tools such as 'entity_profile' or 'resolve_entity'.
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 gives no explicit guidance on when to use this tool versus alternatives. It only implies usage for looking up a single node by CURIE. No exclusions, prerequisites, or alternative tools are mentioned, leaving the agent without clear selection criteria.
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.
Most tools have clear, distinct purposes, especially within the same domain (e.g., Polymarket betting tools each serve a specific function). However, the multiple data-querying tools (ask_pipeworx, ask_pipeworx_grounded, deep_research) could cause confusion despite detailed descriptions.
Many tools follow a verb_noun snake_case pattern (e.g., bet_research, compare_entities), but there are exceptions like ai_visibility_check, forget, and suggest_questions. The mix of imperative verbs and descriptive phrases creates inconsistency.
With 35 tools, the server feels overloaded. While each domain (biomedical, financial, betting) is covered extensively, the sheer number of tools likely overwhelms agents, and many tools could be merged or split into separate servers.
The tool set is comprehensive for its declared purpose, covering biomedical queries, company data, betting analysis, memory management, and more. Minor gaps exist (e.g., no tool to delete a bet, no write operations for biomedical data), but the breadth is impressive.