Evo2 MCP Server

Evo2 MCP Server

Enables genomic sequence analysis through the Evo 2 model, supporting DNA sequence scoring, embedding, generation, and variant effect prediction with multiple model checkpoints (7B, 40B, 1B parameters).

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evo2-mcp

evo2-mcp banner

BioContextAI - Registry Tests Documentation

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.

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 for details.

    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:

    pip install evo2-mcp
    
  3. Activate MCP Server: Add 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.

Usage

Once installed, the server can be accessed by any MCP-compatible client. For available tools and usage examples, see the Tools Documentation.

Available Tools

  • score_sequence - Evaluate DNA sequence likelihood
  • embed_sequence - Extract feature representations
  • generate_sequence - Generate novel DNA sequences
  • score_snp - Predict variant effects
  • get_embedding_layers - List available embedding layers
  • list_available_checkpoints - Show supported model checkpoints

See the Tools Documentation for detailed API reference and examples.

Documentation

You can also find this project on BioContextAI, the community hub for biomedical MCP servers.

Citation

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 = {0.2.2}
}

For the underlying Evo 2 model, please also cite the original Evo 2 publication.

License and Attribution

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.

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