# 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.

Repository: https://github.com/xuzhougeng/wisp-science
Canonical: https://ross.abutalabs.com/products/wisp-science
Homepage: https://wispscience.com/
Language: Rust
License: AGPL-3.0
License Family: copyleft
Topics: ai4science, agent-skills, ai-agent, ai-assistant, ai-for-science, bioinformatics, computational-biology, desktop-app, llm, local-first, mcp, model-context-protocol, python, reproducible-research, research-assistant, rstats, rust, scientific-computing, scientific-workflow, tauri
Last push: 2026-09-02T22:51:41+00:00

## Health v2 (maintenance only)
Score: 81/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 100, release rhythm 100, longevity 4
- inputs: {"age_days": 63, "days_push": 0, "days_rel": 0, "gap_med": 1, "n_releases_24m": 52}
- flags: young
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1087, forks 113 (observed 2026-09-03T02:15:20.736798+00:00)

## What it is
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
- artifact type: application
- maturity: active
- function: agent-framework, mcp, llm-inference, chat-interface, developer-tools, sdk, workflow-automation
- domain: artificial-intelligence, bioinformatics, data-science, large-language-models, developer-tools, self-hosted
- platform: windows, cli, cross-platform
- tags: 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

## Member repositories
- xuzhougeng/wisp-science (main) score 81

## Provenance
- Observed fields: from GitHub, fetched 2026-09-03T02:15:20.736798+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:02:01.147539+00:00, confidence not recorded.
  - readme: https://github.com/xuzhougeng/wisp-science (fetched 2026-09-03T02:15:20.736798+00:00, sha 93b5adcf28a7)
  - homepage: https://wispscience.com/ (fetched 2026-08-29T13:02:44.358629+00:00, sha 6ee7f242647e)
  - site_page: https://wispscience.com/about (fetched 2026-08-29T13:02:44.371995+00:00, sha c08e85e4527c)
  - site_page: https://wispscience.com/releases/v1.7.1 (fetched 2026-08-29T13:02:44.367980+00:00, sha 3e954c370d0b)
  - site_page: https://wispscience.com/releases (fetched 2026-08-29T13:02:44.369931+00:00, sha e6c5b6f44e7c)
- Data as of 2026-08-30T08:39:29.467469+00:00.