# PubMed MCP Server

> Use this tool when you need to search, retrieve, and analyze biomedical literature from PubMed's extensive database of over 36 million citations. It solves problems related to finding relevant research, managing citations, and discovering new information using advanced queries and MeSH terms. The tool accepts search queries and MeSH terms as inputs and provides comprehensive literature results, full-text articles, and citation management outputs.

Canonical page: https://skillsregistry.net/skills/augmented-nature-pubmed-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/augmented-nature-pubmed-mcp-server

## Description

Provides comprehensive access to NCBI's PubMed database of over 36 million biomedical citations, allowing users to search, retrieve, and analyze literature directly through MCP tools. It supports advanced queries, citation management, full-text retrieval from PubMed Central, and precise discovery using MeSH terms.

## Trust

- **Trust score (0–1):** 0.87
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/hnp7dtjrja)
- **Repository:** <https://github.com/Augmented-Nature/PubMed-MCP-Server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "augmented-nature-pubmed-mcp-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/augmented-nature-pubmed-mcp-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/augmented-nature-pubmed-mcp-server/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt