PubMed MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'search_pubmed' has a clearly defined and distinct purpose for searching PubMed articles.
Naming Consistency5/5Since there is only one tool, naming consistency is inherently perfect. The tool name 'search_pubmed' follows a clear verb_noun pattern that would be appropriate if more tools were added.
Tool Count2/5A single tool for a PubMed server is too minimal for the apparent scope. While search is a core function, a complete PubMed interface would typically include tools for fetching article details, citations, related articles, or filtering by metadata. One tool feels thin and incomplete.
Completeness2/5The tool surface is severely incomplete for a PubMed domain. It only provides search functionality, missing essential operations like retrieving specific articles by PMID, fetching citations, accessing related articles, or filtering by date/journal. This will cause significant agent failures when trying to perform comprehensive PubMed tasks.
Average 4.2/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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- No stable releases found
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- No high-severity vulnerability alerts
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It effectively describes the search behavior, field logic, and return format, though it lacks details on rate limits, authentication needs, or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (Parameters, Field logic, Returns) and avoids redundancy. It could be slightly more concise by integrating some details, but overall it's efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 5-parameter search tool with no annotations or output schema, the description is quite complete—covering parameters, logic, and return values. Minor gaps include lack of error handling or performance details, but it's largely sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does 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 thoroughly explains all 5 parameters, including their purposes, defaults, and interactions (e.g., field logic for title/abstract/keywords), adding significant value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Search PubMed') and resource ('article JSON objects'), with no siblings to distinguish from. It provides a complete picture of what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for searching PubMed articles but provides no explicit guidance on when to use this tool versus alternatives, prerequisites, or error conditions. With no sibling tools, this is less critical but still a gap.
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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