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io.github.mims-harvard/tooluniverse MCP Server

io.github.mims-harvard/tooluniverse

2,500+ scientific tools for AI scientists: machine learning, datasets, APIs, and research packages.

What is the io.github.mims-harvard/tooluniverse MCP server?

ToolUniverse is an MCP server that provides access to over 1,000 machine learning models, datasets, APIs, and scientific packages for AI-driven research. It standardizes how LLMs identify and call tools across life sciences, data analysis, knowledge retrieval, and experimental design through the AI-Tool Interaction Protocol.

ToolUniverse democratizes AI scientist systems by integrating a vast ecosystem of scientific tools—from ML models and bioinformatics packages to literature search and molecular simulation—accessible via MCP. It works with Claude, GPT, Gemini, and open models, supports async long-running tasks, tool composition, and includes 68 pre-built agent skills for drug discovery, precision oncology, and rare disease diagnosis.

How to install io.github.mims-harvard/tooluniverse

Copy-paste configuration for popular MCP clients.

transport: stdio
Config generated by PluginBench — verify against the source before use.
Environment / auth
  • OPENAI_API_KEY
    secret

    OpenAI API key for LLM-based tool finding and embedding features

  • ANTHROPIC_API_KEY
    secret

    Anthropic API key for Claude-based features

  • GEMINI_API_KEY
    secret

    Google Gemini API key for Gemini-based features

  • OPENROUTER_API_KEY
    secret

    OpenRouter API key for accessing 100+ LLM models

  • AZURE_OPENAI_API_KEY
    secret

    Azure OpenAI API key (alternative to OpenAI)

  • HF_TOKEN
    secret

    HuggingFace token for accessing models and datasets

  • NCBI_API_KEY
    secret

    NCBI/PubMed API key for higher rate limits (10 req/sec vs 3 req/sec). Register at https://www.ncbi.nlm.nih.gov/account/

  • SEMANTIC_SCHOLAR_API_KEY
    secret

    Semantic Scholar API key for higher rate limits (100 req/sec vs 1 req/sec). Register at https://www.semanticscholar.org/product/api

  • BIOGRID_API_KEY
    secret

    BioGRID API key for protein-protein interaction queries. Register free at https://webservice.thebiogrid.org/

  • DISGENET_API_KEY
    secret

    DisGeNET API key for gene-disease association data. Register free at https://www.disgenet.org/

  • OMIM_API_KEY
    secret

    OMIM API key for Mendelian disease data. Register at https://omim.org/api

  • ONCOKB_API_TOKEN
    secret

    OncoKB API token for precision oncology annotations. Register at https://www.oncokb.org/apiAccess

  • NVIDIA_API_KEY
    secret

    NVIDIA NIM API key for AlphaFold2 structure prediction, molecular docking, and genomics tools. Get key at https://build.nvidia.com

  • USPTO_API_KEY
    secret

    USPTO API key for patent data access. Register at https://developer.uspto.gov/

  • UMLS_API_KEY
    secret

    UMLS API key for medical terminology and concept mapping. Register at https://uts.nlm.nih.gov/uts/

  • BRENDA_EMAIL

    BRENDA enzyme database login email. Register at https://www.brenda-enzymes.org/

  • BRENDA_PASSWORD
    secret

    BRENDA enzyme database login password

~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "tooluniverse": {
      "command": "uvx",
      "args": [
        "tooluniverse",
        "tooluniverse-smcp-stdio",
        "--compact-mode",
        "--categories"
      ],
      "env": {
        "OPENAI_API_KEY": "<YOUR_OPENAI_API_KEY>",
        "ANTHROPIC_API_KEY": "<YOUR_ANTHROPIC_API_KEY>",
        "GEMINI_API_KEY": "<YOUR_GEMINI_API_KEY>",
        "OPENROUTER_API_KEY": "<YOUR_OPENROUTER_API_KEY>",
        "AZURE_OPENAI_API_KEY": "<YOUR_AZURE_OPENAI_API_KEY>",
        "HF_TOKEN": "<YOUR_HF_TOKEN>",
        "NCBI_API_KEY": "<YOUR_NCBI_API_KEY>",
        "SEMANTIC_SCHOLAR_API_KEY": "<YOUR_SEMANTIC_SCHOLAR_API_KEY>",
        "BIOGRID_API_KEY": "<YOUR_BIOGRID_API_KEY>",
        "DISGENET_API_KEY": "<YOUR_DISGENET_API_KEY>",
        "OMIM_API_KEY": "<YOUR_OMIM_API_KEY>",
        "ONCOKB_API_TOKEN": "<YOUR_ONCOKB_API_TOKEN>",
        "NVIDIA_API_KEY": "<YOUR_NVIDIA_API_KEY>",
        "USPTO_API_KEY": "<YOUR_USPTO_API_KEY>",
        "UMLS_API_KEY": "<YOUR_UMLS_API_KEY>",
        "BRENDA_EMAIL": "<YOUR_BRENDA_EMAIL>",
        "BRENDA_PASSWORD": "<YOUR_BRENDA_PASSWORD>"
      }
    }
  }
}

Tools & capabilities

Tools this server exposes to the agent.

  • Literature Search — Unified search across PubMed, Semantic Scholar, ArXiv, BioRxiv, Europe PMC, and more
  • Tool Discovery — Identify and inspect tools from the terminal or programmatically
  • Machine Learning Models — Access to 1000+ ML models for data analysis and prediction
  • Datasets — Scientific datasets for research and experimentation
  • APIs — Integration with scientific and research APIs
  • Bioinformatics Packages — Cheminformatics, molecular simulation, and single-cell analysis tools
  • Visualization Tools — Local ML and plotting capabilities
  • Tool Composition — Chain tools for sequential or parallel execution in workflows
  • Async Operations — Long-running tasks with progress tracking and parallel execution

Use cases

  • Conduct multi-omics analysis to identify therapeutic targets and predict drug responses
  • Search and synthesize scientific literature across PubMed, ArXiv, and bioRxiv to inform research
  • Perform molecular docking and protein simulations for drug discovery
  • Build AI-driven diagnostic systems for rare disease identification
  • Automate pharmacovigilance and adverse event analysis workflows

io.github.mims-harvard/tooluniverse MCP server FAQ

What is ToolUniverse?

ToolUniverse is an MCP server providing 1,000+ scientific tools—ML models, datasets, APIs, and packages—for building AI scientist systems. It standardizes tool discovery and execution via the AI-Tool Interaction Protocol.

Is ToolUniverse free?

Yes, ToolUniverse is open-source and free to use. Some integrated tools and APIs may require authentication or have usage limits.

How do I install ToolUniverse in Claude or Cursor?

For Claude Code users: run `claude plugin marketplace add mims-harvard/ToolUniverse` then `claude plugin install tooluniverse@tooluniverse`. For other agents, add the MCP config with `uvx tooluniverse` or install via `uv pip install tooluniverse`.

What authentication is required?

The base install requires no authentication. Some integrated tools (literature search APIs, ML services) may require API keys, which can be configured during setup.

Does ToolUniverse support async operations?

Yes, it supports long-running tasks like protein docking and molecular simulations with progress tracking and parallel execution.

What are Agent Skills?

Agent Skills are 68 pre-built research workflows for tasks like drug discovery, precision oncology, rare disease diagnosis, and pharmacovigilance that leverage ToolUniverse's tool ecosystem.

README (reference)

Source of truth, from the repository.

<img src="docs/_static/logo.png" alt="ToolUniverse Logo" height="28" style="vertical-align: middle; margin-right: 8px;" /> ToolUniverse: Democratizing AI scientists

Documentation Paper PyPI version MCP Registry Website Slack WeChat LinkedIn X PyPI Downloads

Install

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

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.

<details> <summary>or set up manually</summary>

Add to your MCP config file:

{
  "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:

npx skills add mims-harvard/ToolUniverse
</details>

Claude Code users — one line, no config file:

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.

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

<p align="center"> <a href="https://www.youtube.com/watch?v=fManSJlSs60"> <img src="https://github.com/user-attachments/assets/13ddb54c-4fcc-4507-8695-1c58e7bc1e68" width="600" /> </a> </p>

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
<p align="center"> <img src="https://github.com/user-attachments/assets/eb15bd7c-4e73-464b-8d65-733877c96a51" width="888" /> </p>

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

@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}, 
}

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