Compare two AI tools side by side
Put any two skills or MCP servers next to each other: risk grade, what each can access, how popular it is, and how to install it.
| What | open-science | open-codex-computer-use |
|---|---|---|
| Risk grade | CC · Moderate risk signals Based on public adoption and transparency signals as of Oct 30, 2026. Our opinion, not a code audit or security guarantee. | BB · Some risk signals Based on public adoption and transparency signals as of Oct 16, 2026. Our opinion, not a code audit or security guarantee. |
| Type | App connector | App connector |
| Est. context load | ~1.1k tokens / turn (~6 tool schemas, 0.53% of 200k context) | ~850 tokens / turn (~5 tool schemas, 0.43% of 200k context) |
| GitHub stars | 2.1k | 2.5k |
| Weekly npm downloads | — | 13.1k |
| Local files | No local folder access noted | No local folder access noted |
| Command execution | No shell command runner noted | Runs shell or system commands |
| Network reach | Connects to outside service API | Local or standard API calls |
| Credentials | No API token required | No API token required |
| Package source | GitHub (ai4s-research/open-science) | npm (open-computer-use) |
| Install command | Source repo only | npx -y open-computer-use |
| Bottom line | This tool runs on your machine with broad access to your files and can send data to external AI services, so only use it with research you're comfortable sharing and only install connectors from trusted sources. | open-codex-computer-use (MCP server) requires careful permission scoping — elevated privileges: Computer automation agents typically require OS-level access; misconfiguration could allow agents to execute unintended system commands or access sensitive files. |
Based on public adoption and transparency signals as of Oct 29, 2026. Our opinion, not a code audit or security guarantee.
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