ToolUniverse: Democratizing AI scientists

Install

AI agent (recommended) — open your AI agent and run:

Code

Read https://aiscientist.tools/setup.md and set up ToolUniverse for me.

The agent will walk you through MCP configuration, API keys, skill installation, and validation.

or set up manually

Add to your MCP config file:

config.json

{
  "mcpServers": {
    "tooluniverse": {
      "command": "uvx",
      "args": ["--refresh", "tooluniverse"],
      "env": {"PYTHONIOENCODING": "utf-8"}
    }
  }
}

--refresh checks PyPI for the newest release on every launch. Drop it ("args": ["tooluniverse"]) to start faster from uv's cache — then upgrade with uv cache clean tooluniverse.

Install agent skills:

Terminal

npx skills add mims-harvard/ToolUniverse

Claude Code users — one line, no config file:

Terminal

claude plugin marketplace add mims-harvard/ToolUniverse
claude plugin install tooluniverse@tooluniverse

Python developers — install the SDK. Install uv first and do not use system pip: on a current Mac, pip install tooluniverse fails with externally-managed-environment (PEP 668) and python3 -m venv can fail at ensurepip. uv manages its own Python and avoids both.

Terminal

curl -LsSf https://astral.sh/uv/install.sh | sh   # if you don't have uv
uv venv --python 3.12 && source .venv/bin/activate
uv pip install tooluniverse

The base install covers the API and database tools. Local ML, cheminformatics, and plotting tools need extras — uv pip install 'tooluniverse[all]', or a single group such as [ml], [visualization], [bioinformatics]. Note [all] excludes pdf, singlecell, smolagents, client, and build, which install by name. Run tooluniverse-doctor to see which groups are missing.

tu CLI — discover, inspect, run, and test tools from the terminal. Python SDK — programmatic access for building AI scientist systems.

Building AI Scientists with ToolUniverse

Click to watch the demo (YouTube) (Bilibili)

What is ToolUniverse?

ToolUniverse is an ecosystem for creating AI scientist systems from any large language model. Powered by the AI-Tool Interaction Protocol, it standardizes how LLMs identify and call tools, integrating more than 1000 machine learning models, datasets, APIs, and scientific packages for data analysis, knowledge retrieval, and experimental design.

Key features:

AI-Tool Interaction Protocol: Standardized interface governing how AI scientists issue tool requests and receive results
Universal AI Model Support: Works with Claude, GPT, Gemini, Qwen, Deepseek, and open models
MCP Integration: Native Model Context Protocol server with configurable transport and tool selection
Async Operations: Long-running tasks (protein docking, molecular simulations) with progress tracking and parallel execution
Tool Composition: Chain tools for sequential or parallel execution in self-directed workflows
Compact Mode: Reduces 1000+ tools to 4-5 core discovery tools, saving ~99% context window
CLI (tu): Discover, inspect, run, and test tools directly from the terminal — 9 subcommands for interactive and scripted workflows
Agent Skills: 68 pre-built research workflows for drug discovery, precision oncology, rare disease diagnosis, pharmacovigilance, and more
Literature Search: Unified search across PubMed, Semantic Scholar, ArXiv, BioRxiv, Europe PMC, and more
Two-Tier Result Caching: In-memory LRU + SQLite persistence with per-tool fingerprinting for 10x speedup, offline support, and reproducibility
Continuous Expansion: Register new tools locally or remotely without additional configuration

AI Scientists Powered by ToolUniverse

Building your project with ToolUniverse? Submit via GitHub Pull Request or contact us.

TxAgent: AI Agent for Therapeutic Reasoning [Project] [Paper] [PyPI] [GitHub] [HuggingFace]

TxAgent leverages ToolUniverse's scientific tool ecosystem to solve complex therapeutic reasoning tasks.

Medea: An Omics AI Agent for Therapeutic Discovery [Project] [Paper] [GitHub]

Medea integrates ToolUniverse tools for multi-omics analysis to identify therapeutic targets and predict drug responses across cancer, autoimmune, and other diseases.

Documentation

Full documentation: zitniklab.hms.harvard.edu/ToolUniverse

Community

Shanghua Gao, the lead creator of this project, is currently on the job market.

Slack · GitHub Issues · Shanghua Gao · Marinka Zitnik

Leaders: Shanghua Gao · Marinka Zitnik

Contributors: Shanghua Gao · Richard Zhu · Pengwei Sui · Zhenglun Kong · Sufian Aldogom · Yepeng Huang · Ayush Noori · Reza Shamji · Krishna Parvataneni · Theodoros Tsiligkaridis · Marinka Zitnik

Citation

Code

@article{gao2025democratizingaiscientistsusing,
      title={Democratizing AI scientists using ToolUniverse}, 
      author={Shanghua Gao and Richard Zhu and Pengwei Sui and Zhenglun Kong and Sufian Aldogom and Yepeng Huang and Ayush Noori and Reza Shamji and Krishna Parvataneni and Theodoros Tsiligkaridis and Marinka Zitnik},
      year={2025},
      eprint={2509.23426},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2509.23426}, 
}