| Name | autocleaneeg-pubmedmcp JSON |
| Version |
1.1.4
JSON |
| download |
| home_page | None |
| Summary | A Model Context Protocol (MCP) server for PubMed biomedical research database |
| upload_time | 2025-09-04 02:08:09 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.10 |
| license | MIT License Copyright (c) 2025 Anthropic PBC Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
ai
biomedical
claude
mcp
ncbi
pubmed
research
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# AutoCleanEEG PubMed MCP Server
A Model Context Protocol (MCP) server that provides access to PubMed, the comprehensive biomedical literature database maintained by NCBI. This server enables AI assistants like Claude to search and retrieve detailed information from millions of biomedical research articles.
## Features
- **Search PubMed Database**: Search across 39+ million biomedical articles using flexible query syntax
- **Retrieve Article Details**: Get complete article metadata, abstracts, authors, and publication information
- **Database Information**: Access current PubMed database statistics and status
- **API Key Support**: Optional NCBI API key integration for enhanced rate limits
- **MCP Protocol**: Full Model Context Protocol compliance for seamless AI assistant integration
## Installation
### From PyPI (Recommended)
```bash
pip install autocleaneeg-pubmedmcp
```
### From Source
```bash
git clone <repository-url>
cd claude_code_docker
pip install -e .
```
## Usage
### As MCP Server
The server can be run directly:
```bash
autocleaneeg-pubmedmcp
```
### Claude Desktop Integration
Add to your Claude Desktop configuration (`claude_desktop_config.json`):
```json
{
"mcpServers": {
"pubmed": {
"command": "autocleaneeg-pubmedmcp",
"args": [],
"env": {
"PUBMED_API_KEY": "your_api_key_here_optional"
}
}
}
}
```
## API Key Setup (Optional)
For enhanced rate limits, obtain a free API key from NCBI:
1. Visit [NCBI API Key Settings](https://account.ncbi.nlm.nih.gov/settings/)
2. Create an account or log in
3. Generate an API key
4. Set environment variable: `export PUBMED_API_KEY="your_key_here"`
## Available Tools
### `search_pubmed`
Search the PubMed database with flexible query syntax.
**Parameters:**
- `term` (required): Search query using PubMed syntax
- `retmax` (optional): Maximum results to return (1-1000, default: 20)
- `email` (optional): Your email for NCBI tracking
**Example:**
```json
{
"term": "BRCA1 mutations AND breast cancer",
"retmax": 10
}
```
### `get_pubmed_details`
Retrieve detailed information for specific PubMed articles.
**Parameters:**
- `id` (required): PubMed ID(s) - single ID or array of IDs
**Example:**
```json
{
"id": ["35123456", "35789012"]
}
```
### `get_pubmed_info`
Get current information about the PubMed database.
**Parameters:** None
## Query Syntax Examples
- Basic search: `"covid vaccine"`
- Multiple terms: `"BRCA1 AND breast cancer"`
- Author search: `"Smith J[Author]"`
- Date range: `"covid vaccine" AND 2020:2023[dp]`
- Journal: `"Nature[Journal]"`
- Title search: `"machine learning"[Title]`
## Error Handling
The server provides comprehensive error handling for:
- Invalid queries or parameters
- Network connectivity issues
- Rate limiting (automatically handled)
- Invalid PubMed IDs
- API key validation
## Development
### Testing
Run the test suite:
```bash
python test_focused.py
```
### Requirements
- Python 3.10+
- httpx>=0.25.0
- mcp>=1.0.0
- pydantic>=2.0.0
- email-validator>=2.0.0
## License
MIT License - see LICENSE file for details.
## Contributing
Contributions are welcome! Please feel free to submit pull requests or open issues.
## Support
For issues and questions:
- Check the troubleshooting section below
- Open an issue on the repository
## Troubleshooting
### Connection Issues
- Verify internet connectivity
- Check if NCBI servers are accessible
- Ensure firewall allows outbound HTTPS connections
### Rate Limiting
- Consider adding a PUBMED_API_KEY for higher limits
- Reduce query frequency
- Check NCBI rate limiting guidelines
### Invalid Results
- Verify PubMed ID format (numeric)
- Check query syntax against PubMed documentation
- Ensure search terms are properly formatted
---
**Made with ❤️ for biomedical research and AI assistance**
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"description": "# AutoCleanEEG PubMed MCP Server\n\nA Model Context Protocol (MCP) server that provides access to PubMed, the comprehensive biomedical literature database maintained by NCBI. This server enables AI assistants like Claude to search and retrieve detailed information from millions of biomedical research articles.\n\n## Features\n\n- **Search PubMed Database**: Search across 39+ million biomedical articles using flexible query syntax\n- **Retrieve Article Details**: Get complete article metadata, abstracts, authors, and publication information \n- **Database Information**: Access current PubMed database statistics and status\n- **API Key Support**: Optional NCBI API key integration for enhanced rate limits\n- **MCP Protocol**: Full Model Context Protocol compliance for seamless AI assistant integration\n\n## Installation\n\n### From PyPI (Recommended)\n\n```bash\npip install autocleaneeg-pubmedmcp\n```\n\n### From Source\n\n```bash\ngit clone <repository-url>\ncd claude_code_docker\npip install -e .\n```\n\n## Usage\n\n### As MCP Server\n\nThe server can be run directly:\n\n```bash\nautocleaneeg-pubmedmcp\n```\n\n### Claude Desktop Integration\n\nAdd to your Claude Desktop configuration (`claude_desktop_config.json`):\n\n```json\n{\n \"mcpServers\": {\n \"pubmed\": {\n \"command\": \"autocleaneeg-pubmedmcp\",\n \"args\": [],\n \"env\": {\n \"PUBMED_API_KEY\": \"your_api_key_here_optional\"\n }\n }\n }\n}\n```\n\n## API Key Setup (Optional)\n\nFor enhanced rate limits, obtain a free API key from NCBI:\n\n1. Visit [NCBI API Key Settings](https://account.ncbi.nlm.nih.gov/settings/)\n2. Create an account or log in\n3. Generate an API key\n4. Set environment variable: `export PUBMED_API_KEY=\"your_key_here\"`\n\n## Available Tools\n\n### `search_pubmed`\nSearch the PubMed database with flexible query syntax.\n\n**Parameters:**\n- `term` (required): Search query using PubMed syntax\n- `retmax` (optional): Maximum results to return (1-1000, default: 20)\n- `email` (optional): Your email for NCBI tracking\n\n**Example:**\n```json\n{\n \"term\": \"BRCA1 mutations AND breast cancer\",\n \"retmax\": 10\n}\n```\n\n### `get_pubmed_details`\nRetrieve detailed information for specific PubMed articles.\n\n**Parameters:**\n- `id` (required): PubMed ID(s) - single ID or array of IDs\n\n**Example:**\n```json\n{\n \"id\": [\"35123456\", \"35789012\"]\n}\n```\n\n### `get_pubmed_info`\nGet current information about the PubMed database.\n\n**Parameters:** None\n\n## Query Syntax Examples\n\n- Basic search: `\"covid vaccine\"`\n- Multiple terms: `\"BRCA1 AND breast cancer\"`\n- Author search: `\"Smith J[Author]\"`\n- Date range: `\"covid vaccine\" AND 2020:2023[dp]`\n- Journal: `\"Nature[Journal]\"`\n- Title search: `\"machine learning\"[Title]`\n\n## Error Handling\n\nThe server provides comprehensive error handling for:\n- Invalid queries or parameters\n- Network connectivity issues\n- Rate limiting (automatically handled)\n- Invalid PubMed IDs\n- API key validation\n\n## Development\n\n### Testing\n\nRun the test suite:\n\n```bash\npython test_focused.py\n```\n\n### Requirements\n\n- Python 3.10+\n- httpx>=0.25.0\n- mcp>=1.0.0\n- pydantic>=2.0.0\n- email-validator>=2.0.0\n\n## License\n\nMIT License - see LICENSE file for details.\n\n## Contributing\n\nContributions are welcome! Please feel free to submit pull requests or open issues.\n\n## Support\n\nFor issues and questions:\n- Check the troubleshooting section below\n- Open an issue on the repository\n\n## Troubleshooting\n\n### Connection Issues\n- Verify internet connectivity\n- Check if NCBI servers are accessible\n- Ensure firewall allows outbound HTTPS connections\n\n### Rate Limiting\n- Consider adding a PUBMED_API_KEY for higher limits\n- Reduce query frequency\n- Check NCBI rate limiting guidelines\n\n### Invalid Results\n- Verify PubMed ID format (numeric)\n- Check query syntax against PubMed documentation\n- Ensure search terms are properly formatted\n\n---\n\n**Made with \u2764\ufe0f for biomedical research and AI assistance**",
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