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pubmed-search-mcp

by u9401066
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Python
Remote

get_citation_metrics

Read-onlyIdempotent

Fetch field-normalized citation metrics from NIH iCite for PubMed articles. Sort and filter results by citation count, RCR, percentile, or citations per year to assess research impact.

Instructions

Get citation metrics from NIH iCite for articles.

Returns field-normalized citation data including:

  • citation_count: Total number of citations

  • relative_citation_ratio (RCR): Field-normalized metric (1.0 = average)

  • nih_percentile: Percentile ranking (0-100)

  • citations_per_year: Citation velocity

  • apt: Approximate Potential to Translate (clinical relevance 0-1)

Can sort and filter results by citation metrics.

Args: pmids: PubMed IDs - accepts multiple formats: - "12345678,87654321" (comma-separated) - ["12345678", "87654321"] (list) - "PMID:12345678" (with prefix) - "last" to use PMIDs from the last search Batches are fail-closed and limited to 1,000 unique PMIDs. sort_by: Metric to sort by: - "citation_count": Raw citation count (default) - "relative_citation_ratio": Field-normalized (recommended) - "nih_percentile": Percentile ranking - "citations_per_year": Citation velocity min_citations: Filter out articles with fewer citations min_rcr: Filter out articles with RCR below threshold (e.g., 1.0 = average) min_percentile: Filter out articles below percentile (e.g., 50 = top half)

Returns: Articles with citation metrics, sorted and filtered as requested. iCite transport or response failures return an explicit retryable error and are never rendered as an empty/unindexed result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pmidsYes
min_rcrNo
sort_byNocitation_count
min_citationsNo
output_formatNomarkdown
min_percentileNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed7 schema fields changedv0.7.2
    • addedInput schema / additionalProperties
      Added value: +false
    • changedInput schema / properties / min_citations / anyOf
      Previous value: -[
-  {
-    "type": "integer"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "maximum": 2000000000,
+    "minimum": 0,
+    "type": "integer"
+  },
+  {
+    "type": "null"
+  }
+]
    • changedInput schema / properties / min_percentile / anyOf
      Previous value: -[
-  {
-    "type": "number"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "maximum": 100,
+    "minimum": 0,
+    "type": "number"
+  },
+  {
+    "type": "null"
+  }
+]
    • changedInput schema / properties / min_rcr / anyOf
      Previous value: -[
-  {
-    "type": "number"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "maximum": 1000000,
+    "minimum": 0,
+    "type": "number"
+  },
+  {
+    "type": "null"
+  }
+]
    • changedInput schema / properties / pmids / anyOf
      Previous value: -[
-  {
-    "type": "string"
-  },
-  {
-    "items": {},
-    "type": "array"
-  },
-  {
-    "type": "integer"
-  }
-]New value: +[
+  {
+    "maxLength": 100000,
+    "minLength": 1,
+    "type": "string"
+  },
+  {
+    "items": {
+      "maxLength": 512,
+      "minLength": 1,
+      "type": "string"
+    },
+    "maxItems": 1000,
+    "minItems": 1,
+    "type": "array"
+  }
+]
    • addedInput schema / properties / sort_by / enum
      Added value: +[
+  "citation_count",
+  "relative_citation_ratio",
+  "nih_percentile",
+  "citations_per_year"
+]
    • changedOutput schema / (root)
      Previous value: -{
-  "properties": {
-    "result": {
-      "title": "Result",
-      "type": "string"
-    }
-  },
-  "required": [
-    "result"
-  ],
-  "title": "get_citation_metricsOutput",
-  "type": "object"
-}New value: +null
  2. First observedv0.5.16

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and openWorld, so the safety profile is covered. The description adds genuine behavioral context beyond that: fail-closed batching capped at 1,000 unique PMIDs, and the guarantee that iCite transport/response failures surface as retryable errors rather than empty results.

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?

Front-loads purpose, then return fields, then args, then return behavior—logical and scannable. There is mild redundancy in listing the return fields once in the intro and again under 'Returns', but every section still earns its place.

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 compensates by enumerating returned fields and explaining failure semantics, which is what an agent needs to call and interpret the tool. The only real gap is the undocumented output_format parameter.

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 description coverage is 0%, so the description carries the full burden, and it does so well for five of six parameters: accepted PMID formats, meaningful sort_by options with a recommended value, and threshold semantics for min_citations/min_rcr/min_percentile. It omits output_format (markdown/json/toon), leaving one enum undocumented.

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?

States a specific verb and resource ('Get citation metrics from NIH iCite for articles'), names the upstream source, and enumerates exactly which metrics are returned. An agent can distinguish this from siblings like find_citing_articles or fetch_article_details without opening the schema.

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

Usage Guidelines3/5

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

Provides useful in-tool guidance such as accepting 'last' to reuse PMIDs from the preceding search, which implicitly ties it to the search workflow. However, it never states when to prefer this tool over siblings such as find_citing_articles or fetch_article_details, so usage is implied rather than directed.

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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