cursor-cloud-agents-mcp
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Alternatives to cursor-cloud-agents-mcp
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Related Servers
- AlicenseAqualityBmaintenanceEnables AI assistants and MCP clients to launch and manage Cursor Cloud Agents on repositories or without one, select models, follow up mid-run, retrieve or cancel results, and check usage and cost.9MIT
- AlicenseAqualityDmaintenanceEnables MCP clients to invoke Cursor SDK's agent runtime, run coding agents, list models, and continue conversations.41MIT
- AlicenseNot gradedqualityCmaintenanceExposes Cursor Cloud Agent operations as native MCP tools, letting MCP-capable clients launch new agents, list and inspect recent ones, send follow-up prompts to resume them, and cancel running runs. Tool arguments are validated with Zod schemas and results include agent ID, URL, and final assistant output.MIT
- AlicenseNot gradedqualityCmaintenanceEnables programmatic control of Cursor's cloud-based AI agents for automated code generation and repository management via standardized MCP tools.5 npm6MIT
- AlicenseAqualityBmaintenanceEnables a supervisor agent to dispatch, monitor, follow up on, cancel, and inspect Cursor CLI code tasks through a governed MCP interface, with permission tiers, workspace allowlists, isolated git worktrees, and auditable artifacts. It also exposes an A2A-compatible HTTP endpoint for agent discovery and scheduling.9MIT
- AlicenseAqualityBmaintenanceEnables delegating coding tasks to Cursor Cloud Agents from Claude Code, Codex, or Grok, with scoped repository access, progress monitoring, follow-ups, and result reporting.23MIT
TDQS
Scored across 9 tools
Each tool targets a distinct lifecycle action: launch, status, followup, result, cancel, list, models, whoami, usage. The overlap between cursor_status and cursor_result is explicitly resolved in descriptions (result is a convenience wrapper that waits server-side). No real ambiguity.
All tools follow a consistent cursor_<verb/noun> snake_case pattern (cursor_launch, cursor_status, cursor_followup, cursor_list, cursor_models, etc.). Predictable and uniform throughout, and prefixing avoids collision with other servers.
Nine tools is well-scoped for a cloud agent orchestration server. Each earns its place: launch/poll/followup/cancel cover the run lifecycle, plus auxiliary helpers (models, list, whoami, usage) that are genuinely useful rather than filler.
Full agent lifecycle is covered: model discovery, launch, status, follow-up, result, cancel, list, auth check, and usage. Minor gaps exist such as no explicit archive/delete agent or run-logs streaming tool, but core workflows are complete and descriptions preempt common dead ends (idempotency, unknown status reconciliation).