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Cursor
75 posts about Cursor. Every summary links to the original.
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Over 30 new plugins join the Cursor Marketplace
Cursor is adding more than 30 plugins to its Marketplace, including integrations from Atlassian, Datadog, GitLab, Glean, Hugging Face, monday.com, and PlanetScale. The plugins extend Cursor across infrastructure and productivity workflows: users can query observability data, manage GitLab repositories and pipelines, work with PlanetScale schemas and queries, handle Atlassian issues and backlogs, search company knowledge in Glean, and manage monday.com boards and tasks. Each plugin bundles capabilities such as MCPs with skills that instruct an agent how to use them, and those tools can support manually started or automatically invoked cloud agents. Cursor also supports community-built plugins, while Teams and Enterprise admins can create private team marketplaces. Automations can run agents on schedules or events with custom instructions.
Build agents that run automatically
Cursor Automations introduces always-on agents that run on schedules or react to events from Slack, Linear, GitHub, PagerDuty, or custom webhooks. Each invocation spins up a cloud sandbox, uses configured models and MCPs, verifies its output, and can draw on memory from past runs. The product supports review and monitoring workflows, including security audits on pushes to main, risk-based codeowner assignment, and PagerDuty-driven incident investigation that proposes fixes. Other automations generate weekly repository digests, add tests after merged code, triage Slack bug reports through Linear, and assemble cross-tool dashboards. Examples from Cursor and Rippling report faster incident response and reduced repetitive work, while Runlayer describes a software factory built with Runlayer MCP and plugins.
Cursor is now available in JetBrains IDEs
Cursor is now available in IntelliJ IDEA, PyCharm, WebStorm, and other JetBrains IDEs through the Agent Client Protocol (ACP), extending its agent-driven development experience to developers using those environments. The integration lets users choose frontier models from OpenAI, Anthropic, Google, and Cursor, while Cursor provides a custom-built agent harness for each model. Cursor's secure codebase indexing and semantic search are combined with JetBrains IDE code intelligence and tooling to support work on large enterprise codebases. Users install Cursor ACP from the ACP Registry and authenticate with an existing Cursor account; it is free for users on paid plans, and the release is described as a foundation for deeper JetBrains integrations.
How technical support at Cursor uses Cursor
Cursor’s technical support team treats customer investigations as research problems, using a single session to combine code, logs, team knowledge, and past conversations. Engineers typically start in Ask Mode, use semantic search across a locally indexed codebase and documentation, and group related repositories with multi-root workspaces. MCP servers bring customer data, Datadog logs and traces, Slack and support history, runbooks, account details, and ticketing context into those investigations; Linear MCP turns evidence into escalations, while a Slack-mentioned cloud agent can open documentation pull requests. Slash commands, Rules, Skills, and parallel subagents automate repeated work, including failure analysis, known-issue searches, ticket writing, and customer-response drafting. The team reports that more than 75% of support interactions run through Cursor, with stated throughput gains of 5–10x and estimated productivity improvements of up to an order of magnitude.
Cursor agents can now control their own computers
Cursor describes cloud agents running in isolated virtual machines with full development environments, letting them use and test the software they create rather than stopping at code generation. Available through the web, mobile, desktop, Slack, and GitHub, the agents onboard onto codebases, produce merge-ready pull requests, and attach videos, screenshots, and logs as validation artifacts. Each agent receives an isolated VM for parallel work and can interact directly with browsers, desktop applications, and other tools; users can control its remote desktop and edit without checking out the branch locally. Examples include implementing and verifying Marketplace source links, reproducing a clipboard-exfiltration vulnerability, testing lint-label changes in Cursor, and walking through cursor.com/docs. Cursor reports that more than 30% of its merged PRs are created by autonomous cloud-sandbox agents, while its next goals include coordinating agents, learning from past runs, and eventually managing production changes end to end.
How Stripe rolled out a consistent Cursor experience for 3,000 engineers
Stripe rolled out Cursor to more than 3,000 engineers while preserving its standards for developer experience and API uptime. The company preloaded Cursor on every machine, taught it in onboarding labs alongside VS Code and IntelliJ, and used Cursor Rules to supply codebase and coding-standard context, with teams able to add local rules. Adoption was reinforced by power users, while code review evolved to use LLMs to flag complex methods and risky files so reviewers could focus attention without sacrificing quality. An internal survey found developer sentiment at a five-year high, and MacVicar observed the largest productivity gains among longest-tenured engineers rather than junior developers. That finding has prompted exploration of letting new hires learn the codebase before receiving Cursor access, reinforcing MacVicar’s advice to start before every AI-workflow question is settled.
Extend Cursor with plugins
Cursor now supports plugins, allowing agents to connect to external tools and acquire new knowledge. Plugins bundle MCP servers, skills, subagents, rules, and hooks to add custom functionality. The initial curated set includes Amplitude, AWS, Figma, Linear, Stripe, Cloudflare, Vercel, Databricks, Snowflake, and Hex, covering planning, design, payments, infrastructure, data, and analytics workflows. Users can install prebuilt plugins from the Cursor Marketplace or create and share their own, while plugin primitives let agents discover domain-specific skills, run subagents in parallel, connect through MCP servers, observe behavior with hooks, and follow rules. The announcement also introduces the Cursor Team Kit for internal CI, code review, and testing workflows, and says private team marketplaces with governance and security controls are coming.
Box chooses Cursor for enterprise-grade quality, security, and control
Box selected Cursor as its enterprise agentic coding platform after evaluating data privacy, security, and agent-quality controls. More than 85% of Box developers, or over 800 people, now use Cursor daily, while the company reports a 30–50% increase in product-roadmap throughput and migrations completed 80–90% faster. Box encodes agent guardrails in custom Cursor rules and commands, including a frontend AI toolkit, automated test-coverage work, and rules for React and design-system migrations. A mentorship program pairing power users with newer adopters increased Cursor usage by 75% and power users by 25% in six weeks, while Box says it can move faster without compromising product quality, security, or accessibility.
Increased usage for agents
Cursor has raised limits for Auto and Composer 1.5 for all individual plans. The update introduces separate first-party models and API usage pools: first-party usage is increased for Auto and Composer 1.5, while API pricing and plan allowances remain unchanged. Composer 1.5 has a standard limit of three times Composer 1’s, with a temporary increase to six times through February 16. Cursor says this supports developers moving from autocomplete toward daily agentic coding while accommodating different preferences for speed, intelligence, and affordability. Composer 1.5 is described as scoring above Sonnet 4.5 on Terminal-Bench 2.0 but below the best frontier models, and both pools reset with the monthly usage cycle; the limits are live for Pro, Pro Plus, and Ultra plans.
NVIDIA commits 3x more code across 30,000 developers with Cursor
NVIDIA has deployed Cursor across its software development lifecycle, with more than 30,000 developers using it daily and committing over three times as much code as before. NVIDIA’s long-lived, interdependent codebases and varied technology stacks made it difficult to understand downstream effects and keep pace with rapid change. Cursor maps and semantically reasons over large codebases, retrieving relevant context, while custom rules and MCP servers extend it from code generation into reviews, testing, debugging, issue-driven fixes, CI troubleshooting, and git-flow automation. The company also uses it to help new hires learn unfamiliar systems and experienced engineers work across programming languages and stack areas. NVIDIA reports that bug rates have remained flat despite higher coding velocity, while code-style consistency has improved.
Securely indexing large codebases
Cursor describes a secure way to index large codebases for semantic search, where naive processing can delay availability for hours. The system builds a Merkle tree of file and directory hashes, synchronizes only divergent branches, and caches embeddings by chunk content to reduce repeated work. For new users, a client-generated simhash finds a similar index within the same team or user's indexes, which is copied while background synchronization reconciles differences. Content proofs derived from the client's full Merkle tree filter search results so users see only files they can prove they possess. Reported time-to-first-query falls from 7.87 seconds to 525 milliseconds for the median repository, and from 4.03 hours to 21 seconds at the 99th percentile.
Dropbox uses Cursor to index over 550,000 files and build an AI-native SDLC
Dropbox adopted Cursor to increase software-development velocity across a demanding environment: its own data centers handle more than 300,000 requests per second, while thousands of engineers maintain a monorepo exceeding 550,000 files. Engineers first experimented organically in 2024, then AI champions, easier sign-up, and a company-wide hackathon helped broaden adoption; CTO Ali Dasdan’s two-hour “smart finder” experience reinforced executive support. Cursor indexed the monorepo by scanning non-ignored files, splitting code into structured chunks, and generating embeddings for a semantic index that supports code generation and editing. More than 90 percent of engineers now use AI tools weekly, with Cursor appearing across coding, review, testing, documentation, and migrations. Dropbox reports that PR throughput and cycle time have moved into the upper tier of industry benchmarks, while describing an ongoing redesign of its software-development lifecycle.
Salesforce accelerates velocity by over 30% and ships higher-quality code with Cursor
Salesforce has made Cursor available to thousands of engineers working across a codebase built over more than 25 years, and reports more than 30% higher velocity alongside gains in code quality. Junior engineers used it to understand existing code and contribute more effectively, while senior engineers began with tedious tasks before expanding to higher-value work as trust grew. Adoption spread from small groups that demonstrated impact, and AI eventually reached every part of the software development lifecycle rather than code writing alone. Salesforce tracks cycle time, quality measured by bug count, and throughput; it reports double-digit improvements across all three, an 85% reduction in one team’s legacy code coverage time, and far more unit tests generated with Cursor.
Best practices for coding with agents
Cursor's guide presents practices for using coding agents that can run for hours, complete multi-file refactors, and iterate until tests pass. Planning first is emphasized: Plan Mode researches the codebase, asks clarifying questions, creates a reviewable implementation plan, and waits for approval. The guidance recommends letting the agent discover context, starting new conversations when focus declines, and using Rules for persistent project instructions while Skills provide dynamic workflows. It also describes hooks for long-running loops, worktrees for isolated changes, parallel model runs, cloud agents, and Debug Mode's hypothesis-and-instrumentation process. Careful diff review, specific prompts, and verifiable goals remain necessary because generated code can be subtly wrong.
Hooks for security and platform teams
Cursor has announced ecosystem partnerships around hooks, which run before or after defined stages of its agent loop to observe, block, or modify behavior. The integrations target MCP governance, code security, dependency scanning, agent safety, and secrets management, connecting Cursor with security tooling, observability platforms, secrets managers, and compliance systems. MintMCP, Oasis Security, and Runlayer provide MCP inventory, least-privilege enforcement, audit trails, and centralized tool-interaction visibility, while Corridor and Semgrep give coding-time feedback and vulnerability scanning. Endor Labs intercepts package installations to scan for malicious dependencies, Snyk’s Evo Agent Guard reviews agent actions for prompt injection and dangerous tool calls, and 1Password validates that all required environment files from 1Password Environments are properly mounted before shell commands execute, enabling just-in-time secrets access without writing credentials to disk.
A visual editor for the Cursor Browser
Cursor has released a visual editor for its Browser that combines a web app, codebase, and visual editing tools in one window. Users can drag rendered elements across the DOM tree, inspect React component props, adjust styles and design-system color tokens, and interactively test layout, typography, and component variants. Point-and-prompt interactions let users select interface elements and describe changes such as resizing, recoloring, or reordering; agents run these prompts in parallel and make changes live within seconds. Once a visual arrangement is settled, the agent locates relevant components and updates the underlying code. The release positions the editor as a way to connect visual design and coding more directly, with features documented for Cursor 2.2.
Improving Cursor’s agent for OpenAI Codex models
Cursor describes adapting its agent harness for OpenAI's latest frontier coding model, GPT-5.1-Codex-Max, by pairing model-familiar instructions with Cursor-specific tools and tuning against Cursor Bench. The Codex integration adopts a more shell-forward design, aligns tool names with commands such as rg, explicitly prefers tools over shell commands, and uses sandboxing to limit unauthorized file and network access. It also limits reasoning summaries to one or two sentences, gives literal guidance for invoking read_lints after substantive edits, removes mid-turn user-communication language, and biases the agent toward taking action unless a plan is requested. Preserving Responses API reasoning items is treated as critical: Cursor reports a 30% performance drop for GPT-5-Codex when traces were removed, compared with OpenAI's observed 3% SWE-bench degradation for GPT-5, while prompt-ordering lessons led it to remove wording that discouraged ambitious work.
Past, Present, and Future
Cursor has announced a $2.3 billion Series D financing at a $29.3 billion post-money valuation, nearly two years after describing a vision for an AI-assisted code editor that could make programming more helpful, answer codebase questions instantly, and reduce the visibility of source code. The company says the early stages of that vision are taking shape while substantial work remains to realize Cursor’s potential. It reports a team of more than 300 engineers, researchers, designers, and operators, over $1 billion in annualized revenue, millions of developers and major engineering organizations as customers, and in-house models generating more code than almost any other LLMs in the world. Existing investors Accel, Thrive, and Andreessen Horowitz participated alongside new partners Coatue, NVIDIA, and Google, while the funding will support further research and Cursor’s next magical moments.
The productivity impact of coding agents
The study examines how developers use Cursor’s agent and how its adoption affects software productivity across tens of thousands of users. After the agent became the default for eligible organizations, the rate of merged pull requests increased 39% relative to time trends in a baseline group, while revert rates did not change significantly, bugfix rates slightly decreased, and average lines edited and files touched per merged pull request were unchanged. Agent acceptance varied with experience: each standard-deviation increase in years of experience corresponded to an approximately 6% increase in acceptance relative to the mean, and experienced developers were more likely to plan before coding. In a sample of 1,000 users, about 61% of conversation-starting requests concerned implementation, with others focused on explanation or planning. The authors say no single metric yet captures AI’s economic impact on software engineering.
Introducing Cursor for Enterprise
Cursor is introducing enterprise features intended to make its coding agents more capable, transparent, and secure for organizations already using the product. Hooks expose the agent loop to custom scripts that can log actions and tool calls, enforce compliance or command allowlists, scrub sensitive material, connect external systems, and trigger automations; they can be distributed through MDM or Cursor’s cloud option. Team Rules provide shared context and can recommend or require standards such as API schemas, conventions, and workflows, while upgraded analytics report activity, adoption, AI lines of code, directory-group filters, and exportable data with updates every two minutes. The release also adds an Audit Log covering 19 event types and Sandbox Mode, which restricts network and file access by default, with administrators controlling availability and team-wide Git and network access.
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