tooluniverse-sdk
ToolUniverse SDK provides a Python interface to compose and execute scientific research pipelines across protein analysis, drug discovery, genomics, and disease databases. Call tools via portable dict API, function methods, or direct instantiation, with batch execution and caching for reproducible workflows.
ToolUniverse SDK lets you build scientific research workflows by calling integrated protein, drug, genomics, and disease analysis tools through Python.
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Install
mims-harvard/ToolUniverse/tooluniverse-sdk · repository language: Python
git clone https://github.com/mims-harvard/ToolUniverse
cp -r ToolUniverse/skills/tooluniverse-sdk ~/.claude/skills/tooluniverse-sdknpx skillfed install mims-harvard/ToolUniverse/tooluniverse-sdkFrequently asked questions
AI-generated answers based on this skill's SKILL.md and metadata
What is the ToolUniverse SDK and how do I use it?
ToolUniverse SDK is a Python interface for composing and executing scientific research pipelines across protein analysis, drug discovery, genomics, and disease databases. You can call tools via a portable dict API, function methods, or direct instantiation. The SDK supports batch execution and caching to ensure reproducible workflows for your research.
How to use tooluniverse SDK for protein structure analysis?
ToolUniverse SDK integrates protein analysis tools including AlphaFold protein prediction and UniProt database access. You can build workflows that leverage these integrated tools through the SDK's portable dict API or function methods, enabling seamless protein structure analysis within your Python research environment.
Can I build AI scientist systems with ToolUniverse?
Yes, ToolUniverse SDK is designed for integrating into custom AI scientist systems and benchmarks. The SDK enables you to compose scientific research workflows using integrated tools, search and discover relevant tools by keyword or embedding, and implement batch processing for reproducible research pipelines.
Does ToolUniverse support drug discovery pipelines?
ToolUniverse SDK provides access to bioinformatics databases including ChEMBL for drug analysis and composition. You can build drug discovery pipelines by accessing and composing these databases through the SDK's Python interface, with batch execution and caching capabilities for reproducible workflows.
How does tool discovery work in ToolUniverse SDK?
ToolUniverse SDK supports searching and discovering relevant scientific tools by keyword or embedding-based search. The tool finder API enables you to locate tools across genomics, proteomics, pathway analysis, literature search, and disease target association databases, streamlining tool selection for your research pipelines.
What databases and integrations does ToolUniverse support?
ToolUniverse SDK integrates UniProt, ChEMBL, KEGG pathway analysis, PubMed literature search, disease target association lookup, and AlphaFold protein prediction. It also supports MCP server integration and batch execution with caching for reproducible scientific workflows across bioinformatics and drug discovery domains.
SKILL.md
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ToolUniverse Python SDK
3 calling patterns -- start with pattern 1:
1. tu.run({"name": ..., "arguments": ...}) -- single tool call, dict API (most portable)
2. tu.tools.ToolName(param=value) -- function API (recommended for interactive use)
3. Direct class instantiation -- advanced, bypasses caching/hooks
Installation
pip install tooluniverse # Standard
pip install tooluniverse[embedding] # Embedding search (GPU)
pip install tooluniverse[all] # All features
export OPENAI_API_KEY="sk-..." # Required for LLM tool search
export NCBI_API_KEY="..." # Optional
Quick Start
```python from tooluniverse import ToolUniverse
tu =
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