Side-by-side comparison of two Model Context Protocol servers — install paths, tools, quality signals, and directory engagement so you can pick the right one for Claude, Cursor, and other MCP clients.
Stateful, structured, auditable shell sessions for AI agents over local, SSH, and Docker. Secret redaction, output budgeting, SSH host-key verification, and a loopback read-only browser viewer that streams the live transcript.
Local-first CLI and MCP wrapper for AI coding agents. Routes shell commands through sage run --, stores command history locally, and returns compressed terminal output to reduce context noise.
Quality signal
44/100 (Fair)
52/100 (Fair)
Install path
pip · high
npx · high
Engagement
3 0 0 7
2 0 0 10
Tools
Persistent sessions with stateful working directory and environmentStructured ExecResult with stdout, stderr, exit code, duration, and cwdPolicy fence to allow or deny commands before executionSecret redaction and output size bounding to prevent data leaks and floodingSupport for local, SSH, and Docker transports with uniform APISession checkpoint and restore for undoing remote workspace changes
Runs commands and returns compressed terminal output summariesKeeps full raw output and command history locallySupports shortcuts for common commands (e.g., pytest, npm test, git status)Tracks token savings and command success metricsOptional cloud mode for sending aggregate proof metricsCompatible with multiple AI coding agents and CI scripts