Side-by-side comparison
Cursor vs Devin
vs
Side-by-side comparison based on our agenticness evaluation framework
At a glance
Quick Facts
| Feature | Cursor | Devin |
|---|---|---|
| Category | Coding Agents | Coding Agents |
| Deployment | On-device / local | Cloud-hosted |
| Autonomy Level | Semi-autonomous | Fully autonomous |
| Model Support | Multi-model | Single model |
| Open Source | No | No |
| MCP Support | Yes | No |
| Team Support | Enterprise | Small team |
| Pricing Model | Freemium | Usage-based |
| Interface | ide, cli | gui, chat |
36-point evaluation
Agenticness
21/36
Adaptive Collaborator
Cursor
17/36
Adaptive Collaborator
Devin
Dimension Breakdown (0-4 each)
Action Capability
Cursor
3
Devin
3
Autonomy
Cursor
3
Devin
3
Planning
Cursor
3
Devin
3
Adaptation
Cursor
2
Devin
2
State & Memory
Cursor
1
Devin
2
Reliability
Cursor
3
Devin
1
Interoperability
Cursor
2
Devin
1
Safety
Cursor
2
Devin
2
Scores from our agenticness evaluation framework. Higher is more autonomous.
Features & Use Cases
Cursor
Features
- AI agents that can use an integrated browser and terminal to browse the web and run shell commands as part of workflows
- Rich context system with semantic search, ignore rules, skills, subagents, and rules to keep agents grounded in large codebases
- Model Context Protocol (MCP) support for connecting external tools and services as agent capabilities
- Automation-focused CLI with headless mode, permissions, parameters, and output formatting for scripting and CI/CD use
- Prebuilt CLI cookbooks for tasks like automated code review, fixing CI issues, secret audits, translating localization keys, and updating documentation
- Cloud agent API with HTTP endpoints and webhooks for embedding Cursor-powered agents into web and mobile applications
- Integrations with Git, GitHub, GitLab, and deeplinks to align agents with existing repository workflows
- Editor-like environment with inline editing, terminal integration, configurable keyboard shortcuts, themes, shell configuration, and multi-language support (e.g., Python, JavaScript/TypeScript, Java, Swift)
Use Cases
- Automating code review in CI using the Cursor CLI and GitHub Actions to comment on pull requests and suggest changes
- Diagnosing and fixing failing CI pipelines by letting an agent inspect logs, run terminal commands, and propose patches
- Running recurring security and hygiene checks such as secret audits or config reviews across repositories
- Translating and maintaining localization key files with an automated workflow instead of manual editing
- Keeping documentation in sync with code changes by using CLI recipes that scan code and update docs automatically
Devin
Features
- Delegates coding tasks to cloud agents
- Breaks work into ticket, plan, test, and PR stages
- Integrates with Slack, Teams, Linear, and Jira
- Tests code changes before handing them off
- Creates pull requests for native review
- Handles migration and refactor workflows
- Supports parallel work across multiple subtasks
Use Cases
- Large codebase migrations where repetitive refactoring needs to be delegated
- Modernizing monoliths into smaller modules
- Fixing high-volume lint or style issues across many files
- Delegating engineering backlog work to an AI agent while engineers review changes
- Running structured refactor tasks that need testing and PR creation
Pricing
Cursor
- **Hobby (Free):** 2000 completions/month, limited slow requests
- **Pro ($20/mo):** Unlimited completions, 500 fast requests/month
- **Business ($40/seat/mo):** Everything in Pro + admin dashboard, usage analytics, SAML SSO
Devin
Pricing not publicly available.
Analysis
Our Verdict
Choose Cursor when AI needs to be part of hands-on repository operations: developers can use its editor and terminal experience, automate recurring engineering work through a headless CLI and CI/CD recipes, connect external capabilities with MCP, or embed its agents in their own applications. Choose Devin when the priority is delegating structured tickets from Slack, Teams, Linear, or Jira to parallel cloud agents that plan, implement, test, and open PRs—especially for migrations, refactors, and backlog cleanup.
Choose Cursor if...
- +Choose Cursor if you need agents to work interactively inside an editor-like environment with inline edits, terminal integration, configurable shortcuts, and support for languages including Python, JavaScript/TypeScript, Java, and Swift.
- +Choose Cursor if you want to operationalize repository maintenance through a headless CLI or CI/CD—for example, automated PR code review, CI-failure diagnosis, secret audits, localization-file updates, or keeping documentation synchronized with code.
- +Choose Cursor if agents need broader tool connectivity: it supports MCP for external tools and services, and its agents can use an integrated browser and terminal during workflows.
- +Choose Cursor if you need to embed a code-context-aware agent in your own web or mobile product through HTTP API endpoints and webhooks, or require enterprise administration such as SCIM, service accounts, analytics APIs, and network/privacy controls.
Choose Devin if...
- +Choose Devin if your team wants to delegate well-scoped engineering tickets through the collaboration and project-management tools it already uses—Slack, Teams, Linear, or Jira.
- +Choose Devin if the core workflow is cloud-agent execution from ticket to proposed plan, tested implementation, and pull request for human review.
- +Choose Devin if you need to parallelize substantial repetitive change programs, such as large migrations, monolith modularization, broad refactors, or high-volume lint and style remediation.
- +Choose Devin if engineers primarily want to offload backlog implementation work to autonomous cloud agents while retaining PR-based review rather than working through an editor and scripting-oriented CLI workflow.