open-index/open-npm huggingface dataset:
npm package: @iflow-mcp/silverstein-scientific-skills-desktop
Description: A Claude Desktop extension (.mcpb) that delivers the `claude-scientific-skills` corpus via a tiny librarian tool surface. Built as a self-contained Bun binary (no Node/Python required for users). Offline fat bundle by default; optional thin/auto-update mo
Latest version: 0.1.0

# Scientific Skills Desktop (Bun MCPB)

A Claude Desktop extension (.mcpb) that delivers the `claude-scientific-skills` corpus via a tiny librarian tool surface. Built as a self-contained Bun binary (no Node/Python required for users). Offline fat bundle by default; optional thin/auto-update mode.

## Features
- 128+ curated scientific skills, JIT-loaded to avoid prompt bloat
- Tools: `search_skills`, `read_skill`, `list_skills`
- Domains: bioinformatics, cheminformatics, proteomics, clinical, materials, physics, ML
- Data sources: PubMed, ChEMBL, COSMIC, UniProt, ClinicalTrials.gov (26+)
- Libraries: RDKit, Scanpy, DeepChem, DiffDock, scvi-tools, Qiskit (54+)
- Integrations: Benchling, OMERO, Protocols.io (15+)
- Offline fat bundle; optional thin/auto-update via `CORPUS_URL`

## Install (Desktop)
1) Download `scientific-skills-fat.mcpb` (fat/offline) from Releases.
2) Claude Desktop → Settings → Extensions → Install Extension → select the .mcpb.

## Usage
```jsonc
// Search for a skill
{ "tool": "search_skills", "arguments": { "query": "biopython" } }

// Read a skill (full doc)
{ "tool": "read_skill", "arguments": { "id": "bioinformatics/biopython/SKILL.md" } }

// Read a section with truncation
{ "tool": "read_skill", "arguments": { "id": "bioinformatics/biopython/SKILL.md", "section": "Installation", "max_chars": 4000 } }
```

## Thin/auto-update mode (optional)
- Set `CORPUS_URL` (env) to a tar.gz corpus; server will download to `${__dirname}/.cache` on first run.
- `CORPUS_PATH` and `CACHE_DIR` are set via manifest env to the bundle root by default.

## Build
```bash
bun build src/index.ts --compile --outfile bin/skills-mcp
./scripts/pack-fat.sh   # fat bundle with corpus
./scripts/pack-thin.sh  # thin bundle (no corpus)
```

## Credits
- Corpus and original MCP concept: [K-Dense-AI/claude-scientific-skills](https://github.com/K-Dense-AI/claude-scientific-skills) (MIT)
- Desktop packaging and Bun binary: Mat Silverstein

## License
MIT