evipedia-mcp

get_metadata

Retrieve an evidence review's structured medical metadata as JSON: review dates, typed intervention names, and ordered citations with PubMed IDs. Use it for review freshness or PMID references.

Instructions

Get a review's structured medical metadata as JSON: review dates (datePublished/dateModified/lastReviewed — a freshness signal absent from the Markdown), the intervention as a typed about entity with alternate names, and an ordered citation list of primary sources (each with a PubMed pmid when available). Use when you need the review's freshness, machine-readable references/PMIDs, or drug classification rather than prose.

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": {
      "slug": "<slug>"
    },
    "name": "get_metadata"
  }
}

Input Schema

Name	Required	Description	Default
`slug`	Yes	Review slug, e.g. 'rapamycin' (a full evipedia.ai URL is also accepted)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.26Jul 31, 2026

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses the output format (JSON), the structured nature of the returned metadata, and caveats such as 'pmid when available' and 'freshness signal absent from the Markdown'. It does not mention error behavior or permissions, but for a non-mutating getter this is reasonably transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two well-organized sentences. The first opens with the verb+resource and lists the key return elements; the second gives direct use cases. Every clause adds value, with no filler or redundancy.

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

Completeness5/5

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

Given the tool's simplicity (one required parameter) and lack of output schema, the description fully compensates by enumerating the returned fields (dates, about entity, citations) and explaining when to use the tool. The schema handles the parameter semantics, and the description provides sufficient context for correct invocation.

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

Parameters3/5

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

Schema description coverage is 100% for the single parameter, including an example and note that a full URL is accepted. The tool description adds no additional parameter details beyond the schema, so the baseline score of 3 is appropriate.

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

Purpose5/5

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

The description clearly states the verb 'Get' and the resource 'a review's structured medical metadata as JSON', then enumerates the specific contents (dates, about entity, citations). It distinguishes itself from siblings by emphasizing 'rather than prose' and the freshness signal 'absent from the Markdown', making the tool's unique role clear.

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

Usage Guidelines4/5

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

The description explicitly says when to use this tool: 'Use when you need the review's freshness, machine-readable references/PMIDs, or drug classification rather than prose.' It provides clear use cases and an implied exclusion of prose needs, but does not explicitly name an alternative tool like get_review, so it falls just short of a perfect score.

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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