mcp-pubmed-evidence

MCP server for reliable PubMed literature retrieval, BibTeX export, and evidence table generation for biomedical research agents.

This project exposes PubMed as structured MCP tools so AI assistants can retrieve biomedical literature with source URLs, PMID/DOI metadata, article types, and citation-ready outputs instead of relying on model memory.

Status

Early development. The first version focuses on PubMed metadata retrieval and citation provenance.

Related MCP server: PubMed MCP Server

Features

• Search PubMed with optional year and publication type filters

• Search ClinicalTrials.gov by query, condition, intervention, status, and result limit

• Fetch normalized metadata for a PubMed article by PMID

• Export PubMed records as BibTeX entries

• Build compact evidence tables for agent workflows

• Return structured PubMed fields such as PMID, title, authors, journal, year, DOI, abstract, article types, and PubMed URL

• Return structured trial fields such as NCT ID, condition, intervention, phase, status, enrollment, outcomes, locations, sponsors, and linked publication references

Why MCP for Biomedical Evidence

Biomedical research agents need reliable access to current, source-backed evidence. A plain chatbot can answer from model memory, but it may miss recent papers, blur study types, or provide weak citations. This MCP server gives agents a controlled tool layer for PubMed retrieval, ClinicalTrials.gov trial registry retrieval, structured metadata, citation export, and evidence-table generation.

The goal is not to make medical decisions. The goal is to help agents retrieve and organize biomedical literature with provenance, stable schemas, and clear source URLs.

Safety scope

This server is intended for biomedical research support, literature discovery, citation management, and evidence organization. It is not intended for diagnosis, treatment recommendations, or medical advice.

Installation

git clone https://github.com/Tianyu-Qu/mcp-pubmed-evidence.git
cd mcp-pubmed-evidence
python -m venv .venv
.\.venv\Scripts\Activate.ps1
pip install -e .[dev]

For macOS/Linux, activate the virtual environment with:

source .venv/bin/activate

MCP Configuration

This server uses MCP stdio transport and can be used by any MCP-compatible client.

Generic stdio configuration:

{
  "command": "python",
  "args": ["-m", "mcp_pubmed_evidence.server"],
  "env": {
    "PYTHONPATH": "/path/to/mcp-pubmed-evidence/src"
  }
}

Claude Desktop example:

{
  "mcpServers": {
    "pubmed-evidence": {
      "command": "python",
      "args": ["-m", "mcp_pubmed_evidence.server"],
      "env": {
        "PYTHONPATH": "/path/to/mcp-pubmed-evidence/src"
      }
    }
  }
}

Replace /path/to/mcp-pubmed-evidence/src with the absolute path to your local src directory. On Windows, it may look like C:\\path\\to\\mcp-pubmed-evidence\\src.

If you install the project into the same Python environment used by your MCP client, you can omit PYTHONPATH.

If your network requires a proxy, add HTTP_PROXY and HTTPS_PROXY to env:

"HTTP_PROXY": "http://127.0.0.1:7890",
"HTTPS_PROXY": "http://127.0.0.1:7890"

Local Demo

You can test PubMed retrieval without an MCP client:

python examples/search_pubmed.py "Alzheimer disease machine learning" --max-results 3

With a year filter:

python examples/search_pubmed.py "Alzheimer disease machine learning" --max-results 5 --year-from 2022 --year-to 2026

Search ClinicalTrials.gov without an MCP client:

python examples/search_trials.py --condition "Alzheimer disease" --intervention "GLP-1" --max-results 5

Example outputs are available in examples/sample_search_output.json and examples/sample_trial_output.json.

You can also verify the MCP stdio server locally by listing its tools:

python examples/mcp_list_tools.py

Expected tools:

search_pubmed
get_pubmed_article
export_bibtex
build_evidence_table

Demo

Verified with Cursor as an MCP client. Cursor connected to the pubmed-evidence server and called the search_pubmed tool for the query Alzheimer disease machine learning with max_results=3.

Additional result screenshots:

Tools

search_pubmed

Search PubMed and return normalized article metadata.

Inputs:

• query: PubMed search query

• max_results: maximum number of articles to return, capped at 50

• year_from: optional publication year lower bound

• year_to: optional publication year upper bound

• article_types: optional publication type filters, such as Review or Randomized Controlled Trial

get_pubmed_article

Fetch one PubMed article by PMID.

export_bibtex

Fetch PubMed articles by PMID and export BibTeX entries.

build_evidence_table

Fetch PubMed articles by PMID and return compact evidence table rows.

search_trials

Search ClinicalTrials.gov and return compact trial records.

Inputs:

• query: optional general trial query

• condition: optional condition or disease filter

• intervention: optional intervention, drug, or device filter

• status: optional recruitment status filter

• max_results: maximum number of trials to return, capped at 50

get_trial_summary

Fetch one ClinicalTrials.gov trial by NCT ID and return detailed structured metadata including arms, outcomes, eligibility, locations, sponsors, collaborators, references, and result references.

map_trial_to_publications

Map one ClinicalTrials.gov NCT ID to linked PubMed publications when PMIDs are available in ClinicalTrials.gov references.

Development

Run tests:

pytest

Run linting:

ruff check .

Limitations

• PubMed and ClinicalTrials.gov metadata can be incomplete; DOI, abstract, author, journal, publication date, outcomes, locations, or linked PMIDs may be missing.

• Evidence tables are metadata-oriented in the first version and do not extract PICO elements or judge study quality.

• The server does not provide diagnosis, treatment recommendations, or medical advice.

• Network access to PubMed may require a proxy depending on the user's environment.

• Tool outputs should be reviewed by a human before being used in manuscripts, clinical documents, or systematic reviews.

Release Notes

See CHANGELOG.md for v0.1.0 release notes.

Roadmap

• Expand ClinicalTrials.gov result fields and examples

• Add OpenAlex/Crossref DOI resolution

• Add richer evidence table extraction

• Add example MCP client configurations

• Add local PDF library support