Evo2 Mcp — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Evo2 Mcp (Agent Skill) and scored it 96/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 1 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 1 flagged
A bulleted imperative like {match} tells the agent to never reveal, disclose, or mention something to the user. Used adversarially it can instruct the agent to hide its tool calls or lie about what it did — stripping the transparency a user relies on to trust the agent.
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.

[![Tests][badge-tests]][tests] [![Documentation][badge-docs]][documentation]
[badge-tests]: https://img.shields.io/github/actions/workflow/status/not-a-feature/evo2-mcp/test.yaml?branch=main [badge-docs]: https://img.shields.io/readthedocs/evo2-mcp
The evo2-mcp server exposes Evo 2 as a Model Context Protocol (MCP) server, providing tools for genomic sequence analysis. Any MCP-compatible client can use these tools to score, embed, and generate DNA sequences.
Prerequisites: Python 3.12
conda install -c nvidia cuda-nvcc cuda-cudart-dev
conda install -c conda-forge transformer-engine-torch=2.3.0
pip install flash-attn==2.8.0.post2 --no-build-isolation
pip install evo2 pip install evo2-mcpAdd the following to your mcp.json configuration:
{
"mcpServers": {
"evo2-mcp": {
"command": "python",
"args": ["-m", "evo2_mcp.main"]
}
}
}For detailed installation instructions, see the [Installation Guide][installation].
Once installed, the server can be accessed by any MCP-compatible client. For available tools and usage examples, see the [Tools Documentation][tools].
score_sequence - Evaluate DNA sequence likelihoodembed_sequence - Extract feature representationsgenerate_sequence - Generate novel DNA sequencesscore_snp - Predict variant effectsget_embedding_layers - List available embedding layerslist_available_checkpoints - Show supported model checkpointsSee the [Tools Documentation][tools] for detailed API reference and examples.
You can also find this project on BioContextAI, the community hub for biomedical MCP servers.
If you use evo2-mcp in your research, please cite:
@software{evo2_mcp,
author = {Kreuer, Jules},
title = {evo2-mcp: MCP server for Evo 2 genomic sequence operations},
year = {2025},
url = {https://github.com/not-a-feature/evo2-mcp},
version = {0.2.3}
}For the underlying Evo 2 model, please also cite the original Evo 2 publication.
The banner image in this repository is a modified version of the original Evo 2 banner from the Evo 2 project, which is released under the Apache 2.0 License. It was modified using Google Gemini "Nanobana" and GIMP.
[installation]: https://evo2-mcp.readthedocs.io/en/latest/installation.html [tools]: https://evo2-mcp.readthedocs.io/en/latest/tools.html [development]: https://evo2-mcp.readthedocs.io/en/latest/development.html [issue tracker]: https://github.com/not-a-feature/evo2-mcp/issues [tests]: https://github.com/not-a-feature/evo2-mcp/actions/workflows/test.yaml [documentation]: https://evo2-mcp.readthedocs.io [changelog]: https://evo2-mcp.readthedocs.io/en/latest/changelog.html [pypi]: https://pypi.org/project/evo2-mcp
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.