"Automating Workflows and Project Management with Cursor" matching MCP servers:

Run dynamic, multi-agent workflow scripts — agent(), parallel(), pipeline() — over real coding agents (Claude Code and OpenAI Codex), with deterministic journaling, resume, token budgets, and git-worktree isolation.

MCP server for authoring, validating, simulating, and publishing workflows for the Runbook workflow engine, including branch and run management.

MCP server for storing and managing QA workflows, encrypted credentials, and browser test run history. Enables agents to create targets, workflows, and retrieve decrypted credential bundles for test execution.

An MCP server that turns deployed n8n workflows into callable tools for AI agents, enabling discovery and execution of tagged workflows via a standard interface without rewriting integrations.

Enables MCP clients to run declarative agents and DAG workflows as plain tools, with parallel nodes, review loops, and per-run least-privilege sandboxing.

Enables AI assistants to manage project analysis, code metrics, documentation, Git operations, code quality, and file organization through natural language commands.

Enables AI agents to discover, understand, and execute complex multi-step workflows defined in YAML files through the Model Context Protocol.

Provides tools for managing project knowledge graphs, enabling structured representation of projects, tasks, milestones, resources, and team members.

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 AI assistants in Cursor IDE to manage n8n workflows through the n8n REST API, including creating, updating, activating workflows, viewing execution history, and triggering webhooks.

AI coding usage analytics — track spend, model usage, and costs across Cursor and Claude Code sessions.

MCP server that wraps Cursor Enterprise API to enable AI agents to answer questions about team spending, usage, and model adoption.

Enables LLMs to read and write local user data, generate fake users via sampling, and interact with structured prompts and resources.

Provides MCP tools and hooks for agent coordination within Cursor workspaces, enabling claim-based scope management, compliance auditing, and production readiness checks.

Enables AI agents to query a repository's verified semantic model, including capabilities, ownership, contracts, constraints, impact, health, and verification status, without re-deriving project facts. It exposes read-only tools for inspecting, reasoning about, and verifying the provenance-tracked surface.

MCP bridge from OpenCode to Cursor agent CLI, enabling code review, debugging, and planning via Cursor cloud.

A local MCP server that improves token efficiency for Cursor's agent by providing cheaper tools like search_code, outline_file, read_snippet, project_map, and handoff, along with rules that steer the agent to use them and reduce excessive context usage.

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

An MCP server that audits a project for documentation, rules, skills, and knowledge artifacts, compares against a reference concept catalog, and generates a prescription plan with frontmatter todos to guide creation of missing or incomplete elements.