antigravity-mcp
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- AlicenseAqualityBmaintenanceEnables MCP clients such as Claude Code, Codex, and Cursor to dispatch background subagent jobs to the Antigravity IDE's local agent engine and collect results asynchronously. Jobs run through the IDE's authenticated session without an API key, with optional Gemini REST fallback and on-disk job history.62MIT
- AlicenseNot gradedqualityBmaintenanceEnables MCP clients to launch, supervise, inspect, cancel, and clean up autonomous coding jobs executed by the Google Antigravity CLI in isolated git worktrees and branches, with optional verification, review, and security auditing.Apache 2.0
- FlicenseNot gradedqualityDmaintenanceEnables AI clients to run Google Antigravity coding sub-agents as MCP tools, with synchronous and asynchronous execution, task polling, and sandboxed Docker workspace isolation.-
- AlicenseNot gradedqualityBmaintenanceEnables any MCP client to start, inspect, wait for, and communicate with fleets of coding agents in worktrees, with structured status, completion events, orchestration mail, and terminal control.MIT
- AlicenseAqualityCmaintenanceEnables MCP clients to delegate background subagent jobs to an IDE's local agent engine, queue and monitor them, and retrieve results while the orchestrator continues working.7MIT
- AlicenseBqualityBmaintenanceAn MCP bridge that lets Codex delegate long-running agent work to the Antigravity CLI, providing observable and resumable tool-based execution with project scoping.1439 PyPI17MIT
TDQS
Scored across 8 tools
Most tools have clearly distinct purposes (dispatch, cancel, list, supervise, model listing, synchronous code search). The one genuinely confusable pair is check_agent_job vs get_agent_job_status, which both read job status, but the descriptions draw a useful line between full logs/output versus compact low-token status.
Seven of eight tools follow a clear verb_noun pattern (list_available_models, check_agent_job, cancel_agent_job, get_agent_job_status, etc.). The single outlier, gemini_code_search, is noun-first and breaks the convention, but overall the set is predictable.
Eight tools is well-scoped for a dispatch-and-monitor server, with each tool covering a distinct lifecycle step (discover models, dispatch, poll, cancel, supervise, list, code search). Nothing feels redundant or missing at the count level.
The surface covers the full lifecycle of dispatching, monitoring, supervising, and cancelling background jobs, plus model discovery and synchronous code search. Minor gaps exist around job cleanup/retention and retry/resume of failed jobs, which agents can work around.