"Providing GitHub projects for reading in Cursor" matching MCP servers:

An MCP server that lets Claude spawn Cursor subagents as async, bounded workers, enabling non-blocking task delegation with asynchronous completion notifications.

Enables delegating coding tasks to Cursor Cloud Agents from Claude Code, Codex, or Grok, with scoped repository access, progress monitoring, follow-ups, and result reporting.

Enables an Alexa+ host to place and manage customer-care calls by building a case, navigating phone menus, waiting on hold, explaining the issue, guarding sensitive disclosures, handing off identity checks, recording ticket numbers and promises, and scheduling follow-ups.

Monitors your Cursor usage and provides a conserve flag to the agent, helping you manage request quota by batching questions, preferring defaults, and cutting unnecessary confirmations.

Enables an orchestrator like Claude Code to hand coding work off to Cursor SDK agents, run as detached background jobs that survive the session and can be listed, inspected, steered, resumed, or stopped. Agents are asynchronous and reusable across follow-up turns, letting expensive frontier models delegate cheaply without blocking or paying to read the results.

An MCP relay that adds a use_jev tool to every connected server, letting the Jev model autonomously select and execute tool calls while the calling model supplies any required text values. It enables agents to delegate multi-step tool use across all configured MCP servers through a single unified interface.

Enables MCP clients to delegate bounded tasks to an explicitly selected Cursor model with durable, restart-safe run state, idempotent runs, and fail-closed security defaults.

Enables delegating coding tasks to the local cursor-agent CLI synchronously, blocking until completion and returning a compact report with diff, status, and session ID.

Enables Claude Code to delegate tasks to Cursor's headless agent, run adversarial reviews, and verify findings with prosecutor/advocate roles.

Enables two-way delegation between Codex and Cursor agents with background jobs, handoff plans, and isolated worktrees, allowing either editor to offload investigation, review, planning, or implementation to the other and continue the same native session later.

Enables AI assistants and other MCP clients to launch and steer Cursor Cloud Agents on repositories or as repo-less research tasks, including model selection, mid-run follow-ups, cancellation, result retrieval, and run listing. Also exposes authentication checks and per-agent or per-run token usage and cost reporting.

Allows AI assistants to access and analyze your Cursor conversation history, enabling personalized coding assistance based on your actual development patterns.

Enables 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.

Exposes GitHub issue and pull-request triage capabilities to any MCP client: fetching repository context, classifying and prioritizing requests, finding duplicates, and applying labels, comments, assignments, closures, or reopenings. All writes are policy-gated, dry-run by default, and destructive actions require explicit two-step human confirmation.

Enables users to control the cursor in Figma through verbal commands using an agentic AI agent, streamlining the design process with a new interaction method.

Give any LLM agent a real Android or iPhone. 62 MCP tools: tap, swipe, type, screenshot, screen-tree reading, app launch, camera, TTS, crash reports, batched execution. Android via ADB, iPhone via WebDriverAgent, on-device inference, Docker+KVM emulators. Works with Claude Code, Cursor, LangChain, LlamaIndex, and any MCP client. MIT.

A simple template for creating custom tools for Cursor IDE using Model Context Protocol, deployable via Heroku, Docker, or directly within Cursor IDE.

Wraps the cursor-agent CLI to provide cost-effective tools for repository analysis, code search, planning, and editing. Offloads heavy thinking tasks from the host AI to reduce token usage while maintaining precise, scoped workspace operations.

Enables AI agents and project managers to turn GitHub Projects v2 into an autonomous project-management layer, handling task checkout, atomic claims, heartbeats, reviews, token budgets, and AI-powered PRD, sprint, triage, and roadmap workflows. It also provides GitHub Actions, Releases, Branches, MCP Resources, and MCP Prompts support with GitHub-native storage.

Enables AI coding agents to self-assign, coordinate, review, and ship work through GitHub Projects v2, with AI-powered PRD generation, sprint planning, issue triage, and token-budget enforcement.

Enables AI coding agents and human managers to coordinate work on GitHub Projects v2 through 20 tools and 169 actions for autonomous task checkout, heartbeats, reviews, token budgets, PRD generation, sprint planning, issue triage, and PRD-to-issues pipelines, backed by GitHub-native storage and MCP resources/prompts.

Enables AI coding agents to register, atomically claim tasks, heartbeat, and review each other's work while turning GitHub Projects v2 into an autonomous task backbone. Also provides AI-powered PRD generation, sprint planning, issue triage, and a PRD-to-issues pipeline backed entirely by GitHub-native storage.

Turns GitHub Projects v2 into an agentic project management layer where AI coding agents self-assign tasks, coordinate via heartbeats, submit work for review, and stay within token budgets. It also provides AI-powered PRD generation, sprint planning, issue triage, and a PRD-to-issues pipeline, all backed by GitHub-native storage with no external infrastructure.

Turns GitHub Projects v2 into an agentic project-management layer where AI coding agents can register, claim tasks, coordinate, submit work for review, and enforce token budgets, while humans can generate PRDs, plan sprints, triage issues, and create roadmaps using GitHub-native storage.

Turns GitHub Projects v2 into an agentic project-management layer where AI coding agents register, atomically claim and self-assign tasks, heartbeat, review each other's work products, and operate within token budgets. It also exposes 20 compound tools (169 actions) plus MCP resources, prompts, and sampling for AI-powered PRD generation, task breakdown, sprint planning, issue triage, and a PRD-to-issues pipeline, all stored natively in GitHub with no external infrastructure.

Enables AI coding agents and teams to turn GitHub Projects v2 into an agentic task substrate where agents register, claim work atomically, heartbeat, review each other, and track token budgets. It also provides AI-powered PRD generation, task breakdown, sprint planning, issue triage, roadmap creation, and GitHub Actions/Releases/Branches management with no external infrastructure.

Enables AI coding agents and project managers to turn GitHub Projects v2 into an autonomous project management layer with task checkout, multi-agent swarms, PRD-to-issue pipelines, sprint planning, triage, and GitHub Actions/Releases/Branches support via 20 compound tools and 169 actions.

Enables AI agents and project managers to turn GitHub Projects v2 into an autonomous project management platform with task checkout, multi-agent coordination, PRD-to-issue pipelines, sprint planning, triage, and GitHub-native storage.

Enables AI coding agents and teams to turn GitHub Projects v2 into an autonomous task substrate for registering, claiming, tracking, reviewing, and completing work, while also supporting AI-powered PRD generation, sprint planning, issue triage, roadmap creation, GitHub Actions/releases/branches, and MCP resources/prompts.

Enables AI agents to use GitHub Projects v2 as a persistent task backbone: registering, atomically claiming tasks, coordinating via heartbeats, submitting work for review, and enforcing token budgets. It also supports AI-powered PRD generation, task breakdown, sprint planning, issue triage, roadmap creation, and materializing tasks into GitHub issues, milestones, and sprints.