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BioLit MCP

BioLit MCP

by sanikacentric
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

get_abstracts

Read-onlyIdempotent

Fetch PubMed abstracts and metadata by PMID to read papers before citing and verify citations; non-existent IDs are returned as not found.

Instructions

Fetch abstracts and metadata for PMIDs. PMIDs that do not exist are returned in not_found. Use this to read papers before citing them and to verify citations.

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": {
      "pmids": "<pmids>"
    },
    "name": "get_abstracts"
  }
}

Input Schema

NameRequiredDescriptionDefault
pmidsYesUp to 20 PubMed IDs, e.g. ['12345678']

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, openWorld), so the bar is lower. The description still adds real behavioral value: it discloses that non-existent PMIDs are surfaced in a not_found field rather than failing, which matters because no output schema is provided.

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?

Two compact sentences with zero filler; the core action and the key error behavior are front-loaded before the usage hint.

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?

For a single-parameter read tool with full annotation coverage, the definition is nearly sufficient, and it partially compensates for the missing output schema by describing not_found. It does not sketch the shape of the returned abstract/metadata fields, leaving one small gap.

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?

Only one parameter, and the schema already documents it fully at 100% coverage including the 20-ID cap and an example. The description adds no syntax or format detail beyond the schema, so baseline 3 applies.

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 verb (fetch) and resource (abstracts and metadata) keyed by a named identifier type (PMIDs), which cleanly separates it from search_pubmed. It does not explicitly name the sibling it complements, so it stops short of a 5.

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?

Gives concrete usage context — read papers before citing them and verify citations — which tells the agent when this tool is appropriate rather than search. No explicit 'when not to use' or named alternative, so not a 5.

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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