xuzhougeng/wisp-science
Open-source, local-first desktop AI research workbench for scientific computing with Python/R, MCP bioinformatics tools, SSH/WSL/GPU runtimes, and OpenAI/Anthropic models. observed · 2026-09-03
Health v2 · maintenance only
81/100
- Activity 100
- Release rhythm 100
- Longevity 4
Flags: young
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 1
- age_days: 63
- days_rel: 0
- days_push: 0
- n_releases_24m: 52
Adoption not part of the score
1087 stars · 113 forks observed · 2026-09-03
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
Wisp Science is an open-source, local-first desktop AI research workbench that combines an LLM agent with persistent Python/R kernels, MCP-connected scientific databases, and SSH/WSL/GPU remote runtimes. It organizes literature, data, code, tool calls, and outputs into traceable, reproducible research projects while keeping data and credentials on the user's machine.
Use cases
- run AI-assisted bioinformatics analyses like RNA-seq workflows locally
- chat with an LLM agent that can execute Python and R code on my data
- search PubMed and GEO and other scientific databases from an AI workbench
- keep a reproducible record of analysis runs, figures, and decisions
- run long compute jobs on remote SSH or WSL servers from a desktop app
- use my own OpenAI or Anthropic API key with a local research assistant
- organize papers, datasets, and code into one research project
When to choose
- you want a local-first, privacy-conscious AI workbench where data and credentials stay on your machine
- you do scientific computing in Python or R and want persistent, isolated kernels per conversation
- you need MCP-based access to scientific databases like PubMed and GEO
- you want reproducible research trails with approval gates and project-scoped artifacts
- you need to orchestrate compute across laptop, WSL, and SSH/GPU servers
When to avoid
- you need a hosted, zero-setup AI assistant that works without your own model API keys
- you only need a plain chatbot without code execution or scientific tooling
- you require a web-based multi-user platform rather than a desktop application
- your workflow depends on cloud-native collaboration and automatic sync out of the box
Facets
application · maturity active
agent-framework mcp llm-inference chat-interface developer-tools sdk workflow-automation artificial-intelligence bioinformatics data-science large-language-models developer-tools self-hosted windows cli cross-platform local-first ai4science scientific-computing reproducible-research research-assistant bioinformatics-tools python-r-kernels ssh-remote-compute byom agent-skills ai-agents macos linux desktop tauri
5 sources
- readme: https://github.com/xuzhougeng/wisp-science · fetched 2026-09-03 · 93b5adcf28a7
- homepage: https://wispscience.com/ · fetched 2026-08-29 · 6ee7f242647e
- site_page: https://wispscience.com/about · fetched 2026-08-29 · c08e85e4527c
- site_page: https://wispscience.com/releases/v1.7.1 · fetched 2026-08-29 · 3e954c370d0b
- site_page: https://wispscience.com/releases · fetched 2026-08-29 · e6c5b6f44e7c
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| xuzhougeng/wisp-science | main | 81 |
For agents
markdown · JSON · MCP: product_card(name="xuzhougeng/wisp-science")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem