pubmed-mcp-server
# 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.
## Prerequisites
- Python 3.8 or higher
- mcp[cli]
- BioPython
## Setup
1. **Clone the Repository:**
```bash
git clone https://github.com/AIAnytime/MCP-Servers
cd pubmed-mcp-server
```
2. **Install Dependencies:**
You can install the required packages using uv:
```bash
uv add -r requirements.txt
```
3. **Configure Entrez Email:**
Ensure you have set a valid email address in the code (in `main.py`):
```python
Entrez.email = "give an email address"
```
## Running the Server
Start the PubMed MCP server by running:
```bash
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:
```json
{
"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:**
```python
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](LICENSE).
You can adjust paths and details as needed for your specific setup.
TDQS
Scored across 1 tool
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.
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.
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.
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.