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tooluniverse

Discover and execute scientific research tools across bioinformatics and drug-discovery domains.

21|2|Updated Dec 8, 2025
Search Tags:#mcp#bioinformatics#research automation#tool discovery#cheminformatics#tool execution#scientific workflows
One-click install
npx skills add https://github.com/silverstein/claude-scientific-skills-desktop --skill tooluniverse-silverstein
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tooluniverse
Source: https://github.com/silverstein/claude-scientific-skills-desktop/tree/main/corpus/tooluniverse
Command: npx skills add https://github.com/silverstein/claude-scientific-skills-desktop --skill tooluniverse-silverstein

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

ToolUniverse removes the friction of finding the right scientific software and then wiring it into an AI-assisted workflow, so researchers can move from questions to actionable tool outputs more quickly.

Core Features & Use Cases

  • Tool Discovery Across Domains: Search 600+ scientific resources by natural language, keywords, or embeddings for bioinformatics, cheminformatics, genomics, structural biology, proteomics, and drug discovery.
  • Standardized Tool Execution: Run selected tools through a consistent configuration format, including parameter handling for database queries, computation, and model-driven tasks.
  • Workflow Composition: Chain tools into multi-step pipelines (e.g., disease targets → structures → virtual screening → candidate evaluation) and reuse discovery/execution patterns.
  • Reference-Driven Guidance: Leverage bundled reference documents for installation/MCP setup, discovery strategies, execution patterns, composition recipes, and domain categorization.
  • Integration-Friendly (MCP/Python/Claude): Use the Python SDK patterns and enable Claude Desktop/Code integration via an MCP server for interactive tool access.

Quick Start

Run a tool search for “protein structure prediction tools” and then open the best matching tool’s details using the ToolUniverse MCP or Python interface.

Frequently Asked Questions about tooluniverse

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I discover bioinformatics and cheminformatics tools for scientific workflows?▼

Discover bioinformatics and cheminformatics tools by searching 600+ scientific resources via natural language, keywords, or embeddings. The system matches user intent to return standardized tool names and argument dictionaries for immediate research automation.

Can I chain multiple genomics and drug discovery tools into a multi-step pipeline?▼

Chain genomics and drug discovery tools into multi-step scientific workflows by composing pipelines like disease targets to structures to virtual screening. Reuse discovery and execution patterns to automate sequential data and analysis tasks.

Does research automation work with Claude Desktop or Python SDK for tool execution?▼

Research automation works with Claude Desktop and Python SDK through an MCP server integration. Use Python SDK patterns and enable MCP setup to access interactive tool execution and inspect standardized tool details.

What's the best way to find and run protein structure prediction tools?▼

The best way to find and run protein structure prediction tools is searching by natural language intent, then opening the matching tool's details. Execute the selected tool through a consistent configuration format with standardized parameter handling.

Do I need a specific environment setup to execute structural biology and proteomics tools?▼

You need a ToolUniverse instance with tool loading enabled to execute structural biology and proteomics tools. The environment requires MCP setup or Python SDK patterns to handle database queries, computation, and model-driven tasks.

What are the limitations of automated tool discovery for scientific research domains?▼

Automated tool discovery is limited to the 600+ indexed scientific resources across bioinformatics, cheminformatics, genomics, structural biology, proteomics, and drug discovery. Workflow composition requires standardized tool names and argument dictionaries to return structured results.

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