MCP server for generating, scoring and embedding genomic sequences using Evo 2
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# evo2-mcp  [](https://biocontext.ai/registry/not-a-feature/evo2-mcp) [![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](https://github.com/ArcInstitute/evo2) 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. ## Features - **Sequence Scoring**: Compute log probabilities for DNA sequences - **Sequence Embedding**: Extract learned representations from intermediate model layers - **Sequence Generation**: Generate novel DNA sequences with controlled sampling - **Variant Effect Prediction**: Score SNP mutations for variant prioritization - **Multiple Model Checkpoints**: Support for 7B, 40B, and 1B parameter models ## Getting Started **Prerequisites**: Python 3.12 1. **Install Evo2 dependencies**: See [Installation Guide][installation] for details. ```bash 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 ``` 2. **Install evo2-mcp**: ```bash pip install evo2-mcp ``` 3. **Activate MCP Server**: Add the following to your `mcp.json` configuration: ```json { "mcpServers": { "evo2-mcp": { "command": "python", "args": ["-m", "evo2_mcp.main"] } } } ``` For detailed installation instructions, see the [Installation Gui…
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