Protein Design MCP Server

Item: Protein Design MCP Server
Rating: 73
Author: M8ven

Enables LLM agents to design proteins, predict structures, score interfaces, and run molecular dynamics simulations through a unified interface.

→ qfoldit/Protein-Design-MCP · listed on glama

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// key findings

✅

No credential exfiltration, no sensitive file access, no obfuscation

Static analysis found nothing flowing your secrets to unexpected places.

✅

Open source with a license and README

Anyone can audit the code, the license is declared, and the publisher documents what it does.

// required environment variables

This server reads these from process.env. You'll be asked to provide them before it can run.

configTORCH_HOME— ESM model weights directory (PyTorch default)

configRFDIFFUSION_PATH— For full GPU pipeline, install [RFdiffusion](https://github.com/RosettaCommons/RFdiffusion) and [ProteinMPNN](https://github.com/dauparas/ProteinMPNN) separately and set / PROTEINMPNN_PATH.

configPROTEINMPNN_PATH— For full GPU pipeline, install [RFdiffusion](https://github.com/RosettaCommons/RFdiffusion) and [ProteinMPNN](https://github.com/dauparas/ProteinMPNN) separately and set RFDIFFUSION_PATH / .

configMODELS_DIR

configMODAL_URL— "": "https://<your-workspace>--protein-design-tools.modal.run"

configCOLABFOLD_BACKEND— "api" (remote MSA) or "local" (local DB) api

configCOLABFOLD_NUM_MODELS

configCOLABFOLD_NUM_RECYCLES

configESM2_MODEL

configESMFOLD_MODEL

configBIO_PYTHON_PATH

configDEVICE— For CPU-only hosts, drop "--gpus", "all" and add "-e", "=cpu".

configBOLTZ_CONDA_ENV

configBOLTZ_NO_KERNELS

configCACHE_DIR— Cache directory ~/.cache/protein-design-mcp

// full audit trail

The full breakdown of what we checked, the deductions that landed, the network hosts, the dependency advisories, and concrete fix guidance is available to verified publishers.

// improvement guidance — verified publishers only

We have 4 concrete improvements we can share with the publisher of this MCP. Each comes with specific guidance to raise the trust score.

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commit: 817d1cf3505646b48e2023d2a91b81e53cefd976

code hash: 33c2bc21895452cf8f8cef9d3408d70754b7ed01b8db55c3a99b8c62ffc407ec

verified: 7/11/2026, 8:22:05 AM

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