# Cursor vs Donely

Cursor records 23,297,751 monthly visits with +8.4% month-over-month growth and Freemium pricing. Donely records 10,995 monthly visits with -0.9% growth and Freemium, Free Trial pricing.

| Metric | [Cursor](https://openaitools.app/tool/cursor) | [Donely](https://openaitools.app/tool/donely) |
| :--- | :--- | :--- |
| Website URL | https://www.cursor.com | https://donely.ai |
| Categories | AI Code Assistant, AI Developer Tools, AI Agent | AI Agent, No-Code&Low-Code, AI Assistant, AI Productivity Tools |
| Pricing Model | Freemium | Freemium, Free Trial |
| Monthly Visits | 23,297,751 | 10,995 |
| MoM Growth Rate | +8.4% | -0.9% |
| Primary Market | United States | United States |
| Direct Visits | 14,683,770 | 4,554 |
| Review Score | 4.7 | 4.2 |
| Saved Count | 29 | 0 |
| Supported Platforms | Website | Website |

## Cursor

Cursor's editor looks familiar to anyone who has used a modern IDE, but the center of gravity is the agent. Instead of only suggesting the next line, it can read a task description, inspect the repository, produce an implementation plan, modify many files, run commands, and report back with a summary of what changed. Developers keep control by approving plans, reviewing diffs, and stepping in wherever judgment is needed.

The product has expanded well beyond a single application. Cloud agents can run on their own machines for extended periods, Cursor ships a CLI, and integrations bring the same agent into Slack and GitHub so work can be handed off without switching tools. A model picker lets you use frontier models from several providers, or rely on automatic selection per task.

This makes Cursor a good fit for teams that want measurable velocity gains on large codebases while keeping human review in the loop. The trade-offs are mostly about cost and process: capable agents consume quota, remote indexing raises questions for security-conscious organizations, and teams need light conventions for when to delegate versus write code directly.

**Pricing & Plans:** Cursor uses a freemium model: you can start for free with limited usage, then move to paid Pro, team, and enterprise tiers that unlock higher model limits, cloud agents, and administrative controls. Exact seats and credit allowances change over time, so check cursor.com/pricing for current numbers.

- **Agent-driven code changes:** An agentic mode that plans changes, edits several files at once, runs tests, and iterates until the task is complete.
- **Cloud and parallel agents:** Background agents spin up their own environments to build, test, and demo features in parallel, then hand back results for review.
- **Tab completion and codebase context:** Fast inline suggestions plus codebase-wide semantic search and indexing so answers reflect your actual repository.
- **Multi-model flexibility:** Switch between leading frontier models from multiple providers, or let Cursor select a model automatically for each task.
- **CLI, Slack and GitHub workflows:** Run Cursor from the terminal, chat with it in Slack, and let it review or open pull requests in GitHub without leaving your workflow.

**Strengths:** Strong repository-wide context and multi-file edits; Agent runs in the editor, cloud, CLI, Slack, and GitHub; Choose from multiple frontier models in one place; Familiar IDE experience for developers coming from other editors

**Limitations:** Requires a paid plan for the most capable models and higher usage; Learning curve to use agentic workflows effectively; Heavy cloud agent usage can consume plan quota quickly; Codebase indexing sends code to remote services, which some compliance teams must review

[Profile (Markdown)](https://openaitools.app/tool/cursor.md)

## Donely

Donely provides managed infrastructure for autonomous AI employees, with a strong current focus on security. Its headline agent, Sentinel, acts as an always-on adversary: a persistent coordinator maps your attack surface across domains, repositories or API specs, then directs thousands of short-lived agents in parallel, each pursuing one narrow objective such as SQL injection, SSRF, IDOR, auth bypass or business-logic abuse. Deterministic validators then attempt to reproduce each result before it is surfaced.

The distinguishing claim is proof over probability. Findings are only reported after a controlled, production-safe challenge has reproduced them, so each one arrives with a reproducible proof of concept, request and response detail, blast radius and a suggested patch. Results flow into GitHub, GitLab, Jira, Linear, Slack, Notion, Discord and data platforms, and the system advertises continuous re-testing on every deploy for compliance evidence such as SOC 2, ISO 27001 and PCI.

The platform emphasises safety and control while running against production: non-destructive read-only validation, full logging and replay of agent actions, per-target least-privilege credentials, rate limits, blast-radius caps and an instant kill switch. Deployment options range from SaaS to a dedicated tenant, in-VPC and air-gapped builds. The site also points to a rebrand toward HOG 3 for the security line, and to hosted OpenClaw/NemoClaw agent offerings elsewhere on the platform.

**Pricing & Plans:** Freemium and enterprise tiers; the site advertises a free trial path and contact-based enterprise pricing, including dedicated, in-VPC and air-gapped deployments.

- **Exploit-validated findings:** Every reported issue comes with a reproducible proof of concept, request and response detail and a blast-radius assessment.
- **Parallel agent swarm:** Thousands of short-lived agents each pursue one focused attack objective under a persistent coordinator.
- **Real offensive tooling:** A steerable headless browser plus Burp, ZAP, Nuclei, sqlmap, Semgrep and custom payloads.
- **Continuous re-testing:** Trigger from CI on every merge, or run continuously against staging and production to keep pace with releases.
- **Guardrails and audit evidence:** Least-privilege keys, rate limits, full action logging and an instant kill switch, with exportable signed traces.

**Strengths:** Only surfaces findings it can actually reproduce, cutting false-positive triage; Runs continuously rather than in annual windows; Broad delivery integrations covering issue trackers, chat and data platforms; Strong safety framing for production testing, with logged, reversible actions

**Limitations:** Enterprise-oriented engagement and pricing, not a self-serve tool for individuals; Product positioning has shifted over time, so older descriptions may not match today's offering; Validated continuous testing is not a substitute for human judgement on business-logic threat modelling

[Profile (Markdown)](https://openaitools.app/tool/donely.md)

## Frequently Asked Questions

### How do Cursor and Donely compare in monthly traffic?

Cursor has 23,297,751 monthly visits, while Donely has 10,995. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Cursor has a month-over-month growth rate of +8.4%; Donely has -0.9%.

### How does pricing compare?

Cursor: Freemium. Cursor uses a freemium model: you can start for free with limited usage, then move to paid Pro, team, and enterprise tiers that unlock higher model limits, cloud agents, and administrative controls. Exact seats and credit allowances change over time, so check cursor.com/pricing for current numbers. Donely: Freemium, Free Trial. Freemium and enterprise tiers; the site advertises a free trial path and contact-based enterprise pricing, including dedicated, in-VPC and air-gapped deployments.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Google Antigravity](https://openaitools.app/tool/google-antigravity) | 16,054,109 | +8.1% | Freemium | Provides powerful parallel AI coding agents via a desktop command center, but is less integrated into a traditional editor. | [.md](https://openaitools.app/tool/google-antigravity.md) |
| 2 | [Replit](https://openaitools.app/tool/replit) | 10,016,437 | -7.7% | Freemium, Paid | Enables instant cloud-based full-stack app building from natural language, but is less suited for local offline repositories. | [.md](https://openaitools.app/tool/replit.md) |
| 3 | [VS Code](https://openaitools.app/tool/vs-code) | 7,397,370 | -3.8% | Freemium | Offers unmatched extension support and official Copilot integration, but lacks Cursor's out-of-the-box deep codebase indexing and agentic editing. | [.md](https://openaitools.app/tool/vs-code.md) |
| 4 | [Qoder](https://openaitools.app/tool/qoder) | 5,145,040 | +81.8% | Freemium, Free Trial, Free | Features advanced multi-file planning and codebase reading, but lacks Cursor's smooth chat-to-edit inline workflows. | [.md](https://openaitools.app/tool/qoder.md) |
| 5 | [Kiro](https://openaitools.app/tool/kiro) | 3,330,476 | +4.6% | Freemium | Focuses on spec-driven engineering and structured agent planning, but offers less fluid ad-hoc inline code generation than Cursor. | [.md](https://openaitools.app/tool/kiro.md) |
| 6 | [Devin](https://openaitools.app/tool/devin) | 2,549,346 | +1% | Paid | Operates as a fully autonomous software engineer for complex tasks, but lacks the snappy interactive inline editing of Cursor. | [.md](https://openaitools.app/tool/devin.md) |
| 7 | [Command Code](https://openaitools.app/tool/command-code) | 2,358,177 | -12.1% | Freemium, Contact for Pricing | The coding agent that learns your coding taste | [.md](https://openaitools.app/tool/command-code.md) |
| 8 | [KaneAI](https://openaitools.app/tool/kaneai) | 901,340 | +13.2% | Freemium, Paid, Contact for Pricing | GenAI-native end-to-end QA agent that plans, writes and heals tests in plain language | [.md](https://openaitools.app/tool/kaneai.md) |
| 9 | [Aikido Security](https://openaitools.app/tool/aikido-security) | 757,491 | +9.6% | Freemium | All-in-one AppSec platform that finds and auto-fixes vulnerabilities | [.md](https://openaitools.app/tool/aikido-security.md) |
| 10 | [Trae](https://openaitools.app/tool/trae) | 702,366 | -7.8% | Freemium | Delivers a polished AI-native IDE experience with multi-file generation, but has a smaller ecosystem than Cursor. | [.md](https://openaitools.app/tool/trae.md) |

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Source: https://openaitools.app/compare/cursor-vs-donely

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