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A persistent Linux computer for your AI: what it installs and writes survives the session.

The last two health checks of this connector failed. If this server requires authentication, missing or expired test credentials may be the cause. A test profile lets Glama authenticate for health checks and discover tools; it is separate from your personal connections.

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Status
Unhealthy
Uptime
0.0% over the last 24 hours
OAuth
Works in Glama
Last Tested
Transport
Streamable HTTP
URL
ChatGPT
–
Claude
–

TDQS

A3.8/5.0

Scored across 18 tools

Disambiguation4/5

Most tools target a distinct resource+action (files, commands, packages, ports, checkpoints, environments) and are easy to tell apart. The one soft spot is the trio list_environments / get_environment_info / get_active_environment, which all return environment metadata and could be momentarily confused, though the descriptions do draw the line between 'which computer is active' and 'status/resources'.

Naming Consistency5/5

Every tool follows a clean verb_noun snake_case pattern (create_checkpoint, list_environments, expose_port, install_package, run_command). Affixed forms like expose_port/unexpose_port/list_exposed_ports stay predictably related, and there is no mixing of conventions.

Tool Count4/5

18 tools is on the heavier side but each maps to a real operation across six coherent domains (environments, checkpoints, files, commands, packages, ports). Nothing looks redundant, though it sits just above the ideal 3-15 range.

Completeness4/5

Checkpoints are full CRUD and files/commands/packages/ports are well covered, so core workflows have no dead ends. The notable gap is the absence of delete_environment (and file delete/rename), which matters since create_environment explicitly fails when you're at your machine limit.

Publisher details

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Vendor relationship
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Restrictions
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