# tox-antitargets-mcp-server

> Use this tool when you need to compute toxicity predictions and mechanistic analyses for explainable computational toxicology. It solves problems related to rodent acute toxicity by linking antitargets to toxicity outcomes, providing deterministic results from a bundled dataset. The tool takes in input data and returns toxicity predictions and mechanistic analysis outputs, making it suitable for use cases requiring accurate and reproducible toxicity assessments.

Canonical page: https://skillsregistry.net/skills/chemagents-tox-antitargets-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/chemagents-tox-antitargets-mcp-server

## Description

An MCP server that reproduces the results of Nikitin et al., 'Towards Explainable Computational Toxicology: Linking Antitargets to Rodent Acute Toxicity' as callable tools, enabling users to compute toxicity predictions and mechanistic analyses deterministically from a bundled dataset.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/yhbj8kgst3)
- **Repository:** <https://github.com/chemagents/tox-antitargets-mcp-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "chemagents-tox-antitargets-mcp-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/chemagents-tox-antitargets-mcp-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/chemagents-tox-antitargets-mcp-server/pull`

---
SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt
