# Msa Search Nim

Generate multiple sequence alignments (MSAs) for protein sequences using the ColabFold...

- Repository: https://github.com/NVIDIA/skills (3812 stars)
- Category: DevOps
- License: Apache-2.0 AND CC-BY-4.0
- Last updated: 2026-10-30
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add NVIDIA/skills --skill msa-search-nim -g -a claude-code -y`
Codex: `npx skills add NVIDIA/skills --skill msa-search-nim -g -a codex -y`
Cursor: `npx skills add NVIDIA/skills --skill msa-search-nim -g -a cursor -y`
Gemini CLI: `npx skills add NVIDIA/skills --skill msa-search-nim -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add NVIDIA/skills`

## Description

Generate multiple sequence alignments (MSAs) for protein sequences using the ColabFold MSA-Search NIM. Use for homolog search, UniRef30/ColabFold env searches, A3M or FASTA alignments, paired MSA search for complexes, PDB70 structural templates, hosted NVIDIA API calls, or local Docker deployment. For local deployment, download the databases in parallel with aria2c and launch via NIM_MODEL_NAME (the recommended default fast path, ~14 min vs over 80 min for the built-in downloader); a plain docker run uses the slow built-in downloader.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# MSA-Search NIM

Generate protein MSAs with GPU-accelerated MMSeqs2. Use this guide for
first-pass hosted/local usage; load supplemental files only when needed:

- `references/api.md`: exact endpoints, schemas, Docker flags, response fields.
- `references/science.md`: MSA purpose, pairing/templates, limits, handoffs.
- `references/parameters.md`: database, pairing, depth, and template tuning.
- `references/validation.md`: alignment, template, and artifact checks.
- `references/examples.md`: compact hosted/local request patterns.

## Choose Mode And Endpoint

Ask only when context is unclear:

> Hosted NVIDIA API or local Docker NIM?

- Hosted standard MSA: `https://health.api.nvidia.com/v1/biology/colabfold/msa-search/predict`
- Hosted paired MSA: `https://health.api.nvidia.com/v1/biology/colabfold/msa-search/paired/predict`
- Local standard MSA: `http://localhost:8000/biology/colabfold/msa-search/predict`
- Local paired MSA: `http://localhost:8000/biology/colabfold/msa-search/paired/predict`
- Local templates: `http://localhost:8000/biology/colabfold/msa-search/structure-templates/predict`

Local inference paths do not include `/v1/`. Hosted requests use `Authorization: Bearer $NGC_API_KEY`. Supported local Docker
startup uses `NGC_API_KEY` (or `NVIDIA_API_KEY` via the preflight) for
registry login, entitlement checks, and first-run model downloads; pass it
into the container with `-e NGC_API_KEY`. Local inference requests use no
auth header after readiness. Warm-cache key-free startup varies by
image/version and should not be assumed.
The hosted template path returned HTTP 404 in validation, so use local Docker
for template search unless the hosted docs/service changes.

## Local Docker

The rest: https://github.com/NVIDIA/skills/blob/HEAD/skills/bionemo-msa-search-nim/SKILL.md