Unofficial Human Protein Atlas MCP Server
A comprehensive Model Context Protocol (MCP) server for accessing Human Protein Atlas data, providing information about protein expression, subcellular localization, pathology, and more.
Overview
The Human Protein Atlas MCP Server enables seamless access to the vast repository of protein data from the Human Protein Atlas (https://www.proteinatlas.org). This server provides tools and resources for:
- Protein Search and Information: Search for proteins by name, gene symbol, or description
- Tissue Expression: Access tissue-specific expression profiles
- Subcellular Localization: Retrieve protein localization data
- Pathology Data: Access cancer-related protein information
- Blood and Brain Expression: Specialized expression data for blood cells and brain regions
- Antibody Information: Validation and staining data for antibodies
- Batch Processing: Efficient lookup of multiple proteins
- Advanced Search: Complex queries with multiple filters
Features
Core Capabilities
- 🔍 Comprehensive Search: Find proteins using various identifiers and keywords
- 🧬 Multi-Modal Data: Access expression, localization, and pathology information
- 🩸 Specialized Atlases: Blood Atlas and Brain Atlas data integration
- 📊 Batch Processing: Efficient handling of multiple protein queries
- 🔬 Research-Grade Data: High-quality, peer-reviewed protein information
- ⚡ Fast Response: Optimized for quick data retrieval
Data Types Available
-
Basic Protein Information
- Gene symbols and Ensembl IDs
- Protein descriptions and classifications
- UniProt cross-references
-
Expression Data
- Tissue-specific RNA expression
- Blood cell expression profiles
- Brain region expression data
- Single-cell expression information
-
Subcellular Localization
- Protein localization patterns
- Reliability scores
- Immunofluorescence data
-
Pathology Information
- Cancer prognostic markers
- Disease associations
- Therapeutic targets
-
Antibody Data
- Antibody validation information
- Staining patterns
- Reliability assessments
Installation
Prerequisites
- Node.js 18 or higher
- npm or yarn package manager
Setup
-
Clone or download the server code
-
Install dependencies:
cd proteinatlas-server npm install -
Build the server:
npm run build -
The server is now ready to use!
Usage
Command Line
Run the server directly:
npm start
# or
node build/index.js
MCP Client Integration
Add to your MCP client configuration:
{
"mcpServers": {
"proteinatlas": {
"command": "node",
"args": ["/path/to/proteinatlas-server/build/index.js"]
}
}
}
Available Tools
Basic Search and Retrieval
search_proteins
Search Human Protein Atlas for proteins by name, gene symbol, or description.
Parameters:
query(required): Search query (gene name, protein name, or keyword)format: Output format (json, tsv) - default: jsoncolumns: Specific columns to include in resultsmaxResults: Maximum number of results (1-10000) - default: 100compress: Whether to compress the response - default: false
Example:
{
"query": "BRCA1",
"format": "json",
"maxResults": 10
}
get_protein_info
Get detailed information for a specific protein by gene symbol.
Parameters:
gene(required): Gene symbol (e.g., BRCA1, TP53)format: Output format (json, tsv, xml, trig) - default: json
get_protein_by_ensembl
Get protein information using Ensembl gene ID.
Parameters:
ensemblId(required): Ensembl gene ID (e.g., ENSG00000139618)format: Output format (json, tsv, xml, trig) - default: json
Expression Analysis
get_tissue_expression
Get tissue-specific expression data for a protein.
Parameters:
gene(required): Gene symbolformat: Output format (json, tsv) - default: json
search_by_tissue
Find proteins highly expressed in specific tissues.
Parameters:
tissue(required): Tissue name (e.g., liver, brain, heart)expressionLevel: Expression level filter (high, medium, low, not detected)format: Output format (json, tsv) - default: jsonmaxResults: Maximum number of results (1-10000) - default: 100
get_blood_expression
Get blood cell expression data for a protein.
get_brain_expression
Get brain region expression data for a protein.
Subcellular Localization
get_subcellular_location
Get subcellular localization data for a protein.
search_by_subcellular_location
Find proteins localized to specific subcellular compartments.
Parameters:
location(required): Subcellular location (e.g., nucleus, mitochondria, cytosol)reliability: Reliability filter (approved, enhanced, supported, uncertain)format: Output format (json, tsv) - default: jsonmaxResults: Maximum number of results (1-10000) - default: 100
Pathology and Cancer
get_pathology_data
Get cancer and pathology data for a protein.
search_cancer_markers
Find proteins associated with specific cancers or with prognostic value.
Parameters:
cancer: Cancer type (e.g., breast cancer, lung cancer)prognostic: Prognostic filter (favorable, unfavorable)format: Output format (json, tsv) - default: jsonmaxResults: Maximum number of results (1-10000) - default: 100
Advanced Features
advanced_search
Perform advanced search with multiple filters and criteria.
Parameters:
query: Base search querytissueSpecific: Tissue-specific expression filtersubcellularLocation: Subcellular localization filtercancerPrognostic: Cancer prognostic filterproteinClass: Protein class filterchromosome: Chromosome filterantibodyReliability: Antibody reliability filterformat: Output format (json, tsv) - default: jsoncolumns: Specific columns to include in resultsmaxResults: Maximum number of results (1-10000) - default: 100
batch_protein_lookup
Look up multiple proteins simultaneously.
Parameters:
genes(required): Array of gene symbols (max 100)format: Output format (json, tsv) - default: jsoncolumns: Specific columns to include in results
compare_expression_profiles
Compare expression profiles between multiple proteins.
Parameters:
genes(required): Array of gene symbols to compare (2-10)expressionType: Type of expression data (tissue, brain, blood, single_cell) - default: tissueformat: Output format (json, tsv) - default: json
Available Resources
The server provides several resource templates for direct data access:
Resource Templates
hpa://protein/{gene}: Complete protein atlas data for a gene symbolhpa://ensembl/{ensemblId}: Complete protein atlas data for an Ensembl gene IDhpa://tissue/{gene}: Tissue-specific expression data for a genehpa://subcellular/{gene}: Subcellular localization information for a genehpa://pathology/{gene}: Cancer and pathology data for a genehpa://blood/{gene}: Blood cell expression data for a genehpa://brain/{gene}: Brain region expression data for a genehpa://antibody/{gene}: Antibody validation and staining information for a genehpa://search/{query}: Search results for proteins matching the query
Example Resource Access
// Access tissue expression data for BRCA1
const resource = await client.readResource("hpa://tissue/BRCA1");
// Search for insulin-related proteins
const searchResults = await client.readResource("hpa://search/insulin");
Data Sources
This server accesses data from:
- Human Protein Atlas: Main protein atlas database
- Tissue Atlas: Normal tissue expression data
- Blood Atlas: Blood cell expression profiles
- Brain Atlas: Brain region expression data
- Pathology Atlas: Cancer-related protein data
- Cell Atlas: Single-cell expression information
Rate Limiting and Best Practices
- The server implements appropriate rate limiting to respect the Human Protein Atlas API
- For batch operations, consider breaking large requests into smaller chunks
- Use specific column selections to reduce response size when possible
- Cache frequently accessed data when appropriate
Error Handling
The server provides comprehensive error handling:
- Invalid Parameters: Clear error messages for incorrect input
- Network Issues: Retry logic for transient failures
- Data Format Errors: Graceful handling of unexpected response formats
- Rate Limiting: Appropriate backoff strategies
Examples
Basic Protein Lookup
// Search for BRCA1 protein
const result = await callTool("search_proteins", {
query: "BRCA1",
format: "json",
});
Tissue Expression Analysis
// Get tissue expression for multiple genes
const comparison = await callTool("compare_expression_profiles", {
genes: ["BRCA1", "BRCA2", "TP53"],
expressionType: "tissue",
});
Cancer Research
// Find breast cancer prognostic markers
const markers = await callTool("search_cancer_markers", {
cancer: "breast cancer",
prognostic: "unfavorable",
maxResults: 50,
});
Batch Processing
// Look up multiple proteins at once
const batchResult = await callTool("batch_protein_lookup", {
genes: ["BRCA1", "BRCA2", "TP53", "EGFR", "MYC"],
format: "json",
});
Development
Building from Source
# Install dependencies
npm install
# Build the project
npm run build
# Run in development mode
npm run dev
Testing
# Run the server
npm start
# Test with MCP client or direct stdio communication
Contributing
Contributions are welcome! Please ensure:
- Code follows TypeScript best practices
- Error handling is comprehensive
- Documentation is updated for new features
- Tests are included for new functionality
License
MIT License - see LICENSE file for details.
Support
For issues and questions:
- Check the Human Protein Atlas documentation: https://www.proteinatlas.org/about/help
- Review the MCP specification: https://modelcontextprotocol.io/
- Submit issues via the project repository
Acknowledgments
- Human Protein Atlas team for providing the comprehensive protein database
- Model Context Protocol community for the standardized communication framework
- TypeScript and Node.js communities for the development tools
This server provides programmatic access to Human Protein Atlas data for research and educational purposes. Please cite appropriate sources when using this data in publications.
Citation
If you use this project in your research or publications, please cite it as follows:
author = {Moudather Chelbi},
title = {Human Protein Atlas MCP Server},
year = {2025},
howpublished = {https://github.com/Augmented-Nature/ProteinAtlas-MCP-Server/},
note = {Accessed: 2025-06-29}