---
name: tooluniverse-66b9c7a0edd6
description: "Access 1000+ scientific tools through ToolUniverse for drug discovery, protein analysis, genomics, literature search, clinical data, ADMET prediction, molecular docking, and more. Use when the user needs biomedical or scientific research capabilities."
---

# ToolUniverse — 1000+ Scientific Tools

You have access to **ToolUniverse**, a unified ecosystem of 1000+ scientific tools that covers the full spectrum of biomedical research. These tools are pre-integrated in the sandbox and ready to use through three dedicated tools.

## When to Use

Use ToolUniverse tools when the user needs:

- **Drug Discovery**: target identification, compound screening, ADMET prediction, drug safety, drug-drug interactions, drug repurposing
- **Protein Analysis**: structure retrieval (PDB/AlphaFold), function lookup (UniProt), interaction networks (STRING/BioGRID), therapeutic design
- **Genomics**: gene expression, GWAS analysis, variant interpretation (ACMG), enrichment analysis, single-cell RNA-seq
- **Literature Search**: multi-source paper search (PubMed/PubTator/EuropePMC/Semantic Scholar/OpenAlex), systematic reviews
- **Clinical**: trial matching, guidelines, pharmacovigilance, precision oncology, rare disease diagnosis
- **Molecular**: docking (Boltz2), SMILES-based property prediction, compound similarity, molecular visualization
- **Omics**: transcriptomics, proteomics, metabolomics, multi-omics integration, spatial transcriptomics

## Three-Step Workflow

**Always follow this sequence: Search → Info → Run**

### Step 1: Search for tools

```
tooluniverse_search(query="protein structure prediction", limit=5)
```

This returns a list of matching tools with names and descriptions. Use natural language to describe what you need.

### Step 2: Check tool specification

```
tooluniverse_info(tool_name="UniProt_get_function_by_accession")
```

This returns the full parameter schema (required/optional args, types, descriptions). **Always check this before running a tool** to ensure you provide correct arguments.

### Step 3: Execute the tool

```
tooluniverse_run(
    tool_name="UniProt_get_function_by_accession",
    arguments='{"accession": "P05067"}'
)
```

The `arguments` parameter is a **JSON string** containing the tool's parameters.

## Common Tool Examples

### Protein & Gene
| Tool | Arguments Example |
|------|-------------------|
| `UniProt_get_function_by_accession` | `{"accession": "P05067"}` |
| `UniProt_get_entry_by_accession` | `{"accession": "P05067"}` |

### Drug Safety
| Tool | Arguments Example |
|------|-------------------|
| `FAERS_count_reactions_by_drug_event` | `{"medicinalproduct": "aspirin"}` |

### Disease-Target
| Tool | Arguments Example |
|------|-------------------|
| `OpenTargets_get_associated_targets_by_disease_efoId` | `{"efoId": "EFO_0000685"}` |

### Literature
| Tool | Arguments Example |
|------|-------------------|
| `PubTator_search_publications` | `{"query": "CRISPR cancer therapy", "limit": 10}` |

### ADMET Prediction
| Tool | Arguments Example |
|------|-------------------|
| `ADMETAI_predict_BBB_penetrance` | `{"smiles": ["CCO"]}` |
| `ADMETAI_predict_toxicity` | `{"smiles": ["CCO"]}` |

### Molecular Docking
| Tool | Arguments Example |
|------|-------------------|
| `boltz2_docking` | `{"protein_id": "1ABC", "ligand_smiles": "CCO"}` |

## Multi-Step Research Patterns

### Drug Safety Profile
1. `tooluniverse_search("drug adverse events")` → find FAERS tools
2. `tooluniverse_run("FAERS_count_reactions_by_drug_event", ...)` → get adverse events
3. `tooluniverse_run("FAERS_get_drug_label_info", ...)` → get drug label

### Disease Target Discovery
1. `tooluniverse_run("OpenTargets_get_associated_targets_by_disease_efoId", ...)` → targets
2. `tooluniverse_run("UniProt_get_entry_by_accession", ...)` → protein details
3. `tooluniverse_run("PubTator_search_publications", ...)` → supporting literature

### Compound Property Analysis
1. `tooluniverse_search("ADMET prediction")` → find prediction tools
2. Run multiple ADMET predictions (BBB, toxicity, bioavailability, solubility)
3. Synthesize results into a compound profile

## Tips

- **Tool names follow a pattern**: `Database_action_description` (e.g., `UniProt_get_entry_by_accession`)
- **First call may be slow** (~30s) as ToolUniverse initializes; subsequent calls are fast
- **Results can be large**: focus on the most relevant fields for the user's question
- **When unsure about tool name**: use `tooluniverse_search` with a broad query first
- **Chain multiple tools** for comprehensive analysis — combine data from different sources
- **API keys are optional**: most tools work without keys, but some (NVIDIA, HuggingFace) may need them for specific functionality


---
Source attribution: AgentTeam-TaichuAI
Original project: https://github.com/AgentTeam-TaichuAI/ScienceClaw
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Gabriel Moreira

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: AgentTeam-TaichuAI
Original project: https://github.com/AgentTeam-TaichuAI/ScienceClaw
Attribution basis: Upstream repository explicitly recorded in package mirror path

Fields of work: Data & Analytics, Education & Research, Healthcare & Life Sciences, Product Management
Roles: Business Intelligence Analyst, Clinical Research, Data Scientist, Product Manager, Researcher
Specialties: API
Tools: Tooluniverse
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 2ff618098d25215adc62bfbc42f5a41e855807de68bb13101ea76a08332a7e37