BioMCP
BioMCP is a server designed to enhance language models with protein structure analysis capabilities. You can:
Analyze Active Sites: Examine binding sites and functional residues of proteins using PDB IDs
Search Disease-Related Proteins: Find protein structures associated with specific diseases or medical conditions
Access Integrated Data: Connect seamlessly with the RCSB Protein Data Bank (PDB) for reliable protein structure insights
Provides compatibility with Node.js runtime for running the BioMCP server, specified as a requirement (Node.js 20.0.0 or higher).
Utilizes TypeScript for implementation (TypeScript 5.0+ required), providing type safety for the protein structure analysis tools.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@BioMCP analyze the active site of PDB structure 6LU7"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
BioMCP: Enabling agent-based biomedical R&D

Overview
BioMCP is a Model Context Protocol (MCP) server designed to enhance large language models with protein structure analysis capabilities. It provides tools for analyzing protein active sites and searching for disease-related proteins by interfacing with established protein databases.
Future work will be centered around enabling agents to utilize the BioMCP.
Related MCP server: PubMed MCP Server
Features
Active Site Analysis: Examine the binding sites and functional residues of proteins using PDB IDs
Disease-Protein Search: Find protein structures associated with specific diseases or medical conditions
Integrated Data Access: Connect seamlessly with RCSB Protein Data Bank (PDB)
Technical Details
BioMCP implements the Model Context Protocol, allowing language models to access specialized protein structure knowledge without requiring this information to be part of their training data. The server handles API connections, data formatting, and error handling to provide reliable protein structure insights.
API Endpoints
BioMCP exposes two primary tools:
analyze-active-site: Provides detailed information about protein binding sites using a PDB IDsearch-disease-proteins: Returns proteins related to specified diseases or medical conditions
Getting Started
Installing via Smithery
To install BioMCP for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @acashmoney/bio-mcp --client claudeManual Installation
# Clone the repository
git clone https://github.com/acashmoney/bio-mcp.git
# Install dependencies
npm install
# Start the server
npm startSetup Instructions
Running the MCP Inspector
Start the BioMCP server:
npm startIn a separate terminal, install the MCP Inspector globally (if not already installed):
npm install -g @anthropic-ai/mcp-inspectorLaunch the MCP Inspector and connect to your local BioMCP server:
npx @modelcontextprotocol/inspector node build/index.jsUse the inspector interface to test tools and view responses.
Using with Claude Desktop
Build the BioMCP server:
npm run buildConfigure Claude Desktop to launch the MCP server:
a. Locate your Claude Desktop config.json file (typically in your user directory)
b. Edit the config.json to include the BioMCP server build path. Example configuration:
{ "globalShortcut": "", "mcpServers": { "bio-mcp": { "command": "node", "args": [ "/path/to/your/build/index.js" ] } } }c. Replace
/path/to/your/buildwith your actual path to the project directory.Restart Claude Desktop for the changes to take effect.
You can now ask Claude questions that utilize the BioMCP tools:
"What are the key residues in the active site of PDB structure 6LU7?"
"Find proteins related to Alzheimer's disease"
Example Usage
When integrated with a compatible language model, Bio-MCP enables queries like:
"What are the key residues in the active site of PDB structure 6LU7?"
"Find proteins related to Alzheimer's disease"
Requirements
Node.js 20.0.0 or higher
TypeScript 5.0+
Compatible MCP client implementation
Testing
BioMCP includes a comprehensive testing suite with unit, integration, and end-to-end tests.
Running Tests
Run all tests:
npm testRun specific test suites:
# Unit tests only
npm run test:unit
# Integration tests only (API interactions)
npm run test:integration
# End-to-end tests only
npm run test:e2eLinting
Check code quality:
npm run lintFix linting issues automatically:
npm run lint:fixRoadmap
Expand level of detail for active site descriptions
Leverage 3-D coordinates
Tools for interfacing with literature
Tools for interfacing with computational biology models:
RFdiffusion
ProteinMPNN
ColabFold
Additional protein design and structure prediction tools
Agent-based research pipelines
Introduce client with protein visualization tools
Available Tools
2 toolsanalyze-active-siteC
Analyze the active site of a protein structure
Inputs: pdbId (required).
search-disease-proteinsC
Search for proteins related to a disease
Inputs: disease (required).
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: one analyzes protein structures (active sites), while the other searches for disease-related proteins. There is no overlap in functionality, making it easy for an agent to choose the correct tool based on the task.
Both tools use a consistent verb-noun pattern with hyphens (e.g., analyze-active-site, search-disease-proteins). This naming scheme is readable and predictable, though with only two tools, it's hard to assess full consistency across a larger set.
With only two tools, the server feels thin for a bioinformatics domain, which typically involves more operations like sequence alignment, structure prediction, or data retrieval. This limited set may not cover common workflows adequately.
The tool surface is severely incomplete for a bioinformatics server. It lacks basic operations such as fetching protein sequences, aligning sequences, predicting structures, or managing datasets. This will likely cause agent failures in handling typical tasks in this domain.
Maintenance
Related MCP Connectors
Agent-to-Agent (A2A) + Model Context Protocol (MCP) hub for peptides.
Agent-to-Agent (A2A) + Model Context Protocol (MCP) hub for peptides.
Protein analysis: ESM-2/ESMC embeddings, mutation scoring, landscape scans, ESMFold structure.
Federated protein structure & annotation across experimental (PDB) and predicted (AlphaFold) models.
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