Skip to main content
Glama
enesjakozh
AIAnytime

pubmed-mcp-server

by AIAnytime
OverviewSchemaSourceRelated ServersScoreDiscussionsAdmin
Python
Hybrid

PubMed MCP Server

This repository contains an MCP server that searches PubMed for article abstracts using BioPython's Entrez module. It leverages the FastMCP framework to provide asynchronous search capabilities for PubMed.

Features

  • Search PubMed: Query for articles based on a search term.

  • Retrieve Abstracts: Fetch abstracts of articles returned from PubMed.

  • Asynchronous Operation: Uses asynchronous execution (via asyncio.to_thread) to avoid blocking the server.

Related MCP server: PubMed MCP Server

Prerequisites

  • Python 3.8 or higher

  • mcp[cli]

  • BioPython

Setup

  1. Clone the Repository:

    git clone https://github.com/AIAnytime/MCP-Servers
cd pubmed-mcp-server

  2. Install Dependencies:

    You can install the required packages using uv:

    uv add -r requirements.txt

  3. Configure Entrez Email:

    Ensure you have set a valid email address in the code (in main.py):

    Entrez.email = "give an email address"

Running the Server

Start the PubMed MCP server by running:

uv run main.py

This command starts the server using the uv command-line tool (as specified in your configuration).

Configuring the MCP Client

To configure your MCP client to connect to the PubMed MCP server, create or update your config.json file as follows:

{
  "mcpServers": {
    "pubmed": {
      "command": "C:/Users/aiany/.local/bin/uv",
      "args": [
        "--directory",
        "C:/Users/aiany/OneDrive/Desktop/YT Video/pubmed-mcp-server",
        "run",
        "main.py"
      ]
    }
  }
}

Explanation of the Configuration

  • command:
    The full path to the command-line tool used to run the MCP server (in this case, uv).

  • args:

    • --directory: Specifies the working directory where the server is located.

    • "C:/Users/aiany/OneDrive/Desktop/YT Video/pubmed-mcp-server": The path to the server's root directory.

    • "run" and "main.py": The command and entry point to start the PubMed MCP server.

Usage

Once the server is running and your MCP client is configured, you can use the provided tool:

  • Tool: search_pubmed

  • Parameters:

    • query: The search term for PubMed (default is "endocarditis").

    • max_results: Maximum number of articles to retrieve (default is 10).

Example Usage:

search_pubmed(query="endocarditis", max_results=10)

This will return a string with the abstracts of the articles separated by newlines.

License

This project is licensed under the MIT License.

You can adjust paths and details as needed for your specific setup.

Available Tools

1 tool
search_pubmedB
Search PubMed for articles matching the query.

Args:
    query: The search term for PubMed.
    max_results: Maximum number of articles to retrieve.

Returns:
    A string containing the abstracts of found articles, separated by two newlines.
ParametersJSON Schema
NameRequiredDescriptionDefault
max_resultsNo
queryNoendocarditis

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool 'searches' and 'retrieves' articles, implying a read-only operation, but doesn't clarify if it's safe, requires authentication, has rate limits, or details the search behavior (e.g., relevance ranking, filters). The return format is described, but key behavioral traits like error handling or performance are omitted.

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 well-structured and front-loaded with the core purpose, followed by clear sections for Args and Returns. Every sentence adds value: the first states the purpose, and the others explain parameters and output. There's no redundancy or unnecessary information, making it highly efficient.

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

Completeness3/5

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

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is minimally adequate. It covers the purpose, parameters, and return format, but lacks behavioral context like error handling, search constraints, or performance details. Without annotations or output schema, more completeness would be beneficial, but it meets basic requirements.

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?

The description adds basic meaning for both parameters: 'query' is described as 'the search term for PubMed,' and 'max_results' as 'maximum number of articles to retrieve.' This compensates for the 0% schema description coverage by providing semantic context. However, it lacks details on query syntax, result limits, or default behaviors, keeping it at a baseline level.

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?

The description clearly states the tool's purpose: 'Search PubMed for articles matching the query.' This specifies the verb ('search'), resource ('PubMed articles'), and scope ('matching the query'). It's not a tautology and is unambiguous. However, with no sibling tools mentioned, there's no explicit differentiation from alternatives, preventing a perfect score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It lacks context about prerequisites, limitations, or scenarios where it's most appropriate. While it implies usage for searching PubMed articles, there's no explicit when/when-not advice or mention of other tools, leaving the agent with minimal usage direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev1.0.0
    • First observedsearch_pubmed
Install Server
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

B3.2/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of confusion or overlap between tools. The tool 'search_pubmed' has a clear, singular purpose of searching PubMed for articles, making disambiguation trivial.

Naming Consistency5/5

Since there is only one tool, naming consistency is inherently perfect. The tool name 'search_pubmed' follows a clear verb_noun pattern, and there are no other tools to compare it against for inconsistency.

Tool Count2/5

A single tool for a PubMed server is too few for the apparent scope. PubMed typically involves operations like fetching article details, filtering by date or author, or retrieving citations, which are missing. This minimal set limits functionality and feels incomplete for the domain.

Completeness2/5

The tool set is severely incomplete for a PubMed server. While 'search_pubmed' covers basic searching, there are obvious gaps such as retrieving full article metadata, accessing citations, filtering results, or managing user queries. This will likely cause agent failures when more complex tasks are required.

Maintenance

ActivityActive
ResponsivenessResponsive

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Connectors

Related MCP Servers

  • PubMed MCP Server

    emi-dm
    F
    license
    A
    quality
    D
    maintenance
    Enables searching and retrieving detailed information from PubMed articles using the NCBI Entrez API. Supports configurable search parameters including title/abstract filtering and keyword expansion to find relevant scientific publications.
    1
    -

  • PubMed MCP Server

    openpharma-org
    A
    license
    B
    quality
    D
    maintenance
    Enables AI assistants to search and retrieve biomedical research articles from PubMed's database of over 35 million citations, including metadata, abstracts, MeSH terms, and full-text PDFs when available.
    1
    1
    MIT

  • PubMed MCP Server

    aeghnnsw
    F
    license
    Not graded
    quality
    C
    maintenance
    Enables searching PubMed's biomedical literature database and retrieving article metadata, abstracts, and full content through the E-utilities API. Supports advanced queries, batch operations, and multiple output formats with automatic rate limiting.
    1
    -

Appeared in Searches