Ship AI-built code with confidence.
Progressively release changes and roll back instantly based on real-time impact.
Agent integrations
Go agent-native
from Day 1.
LaunchDarkly works inside tools like Claude Code, Cursor, and your entire agent stack. Control how changes behave in production without switching apps.
Install with AI using this prompt.
Drop this into your favorite coding assistant and get up and running with AI in seconds.
Onboard me to LaunchDarkly. Start by installing the onboarding skill: `npx skills add launchdarkly/agent-skills --skill onboarding -y`. source-launchdarkly
Start using LaunchDarkly from your tools.
Operate LaunchDarkly directly from tools like Claude Code, Cursor, terminal, or your IDE. Manage code and agents from wherever you already work.
MCP
Give your AI assistant direct access to LaunchDarkly. Ask it to wrap code in flags, set up guarded releases, build experiments, and configure agent behavior in plain English.
View docs
CLI
Manage LaunchDarkly directly from your terminal. Run operations across flags, guarded releases, experiments, and agent configurations in scripts, CI/CD pipelines, or agent-driven workflows.
View docs
IDE integration
Use LaunchDarkly without leaving your editor. The GitHub Copilot extension lets you manage flags and run cleanup workflows. For MCP-enabled editors like Cursor, connect via the LaunchDarkly MCP server.
Explore integrations
Agent Skills
Automate full workflows.
Agent Skills give your agent the playbook for working in LaunchDarkly—creating flags, setting up guarded releases, managing agent behavior and experiments, and cleaning up stale flags. The right steps are already built in.
01Feature flag workflows
Create, update, and manage flags.
02Flag targeting & rollout workflows
Target users, configure rules, and roll out changes progressively.
03Guarded release workflows
Set release health thresholds, configure rollback rules, and automatically protect production.
04Flag cleanup workflows
Find and remove stale flags more safely.
05Agent behavior workflows
Create and manage prompts and models, test agent variations, and run online evals.
06Experimentation workflows
Set up metrics, instrument your code and agent variations, and build experiments.
See what teams can do with agents in production.
From release control to self-healing systems, teams can solve problems like these using runtime control right from their existing toolset.
Learn more
Control and govern AI agents in production.
Monitor agent behavior, detect drift, and take action—without redeploying.
Optimize AI performance
and cost.
Test prompts and models in production and dynamically route traffic to the best option.
Enable self-healing systems.
Automatically prevent issues, understand change behavior, and fix issues instantly with suggested changes and PRs.
Experiment continuously.
Experiment with code and agents in production and optimize based on real-world results.
Trusted in production, proven at scale.
Built for real production workflows with the scale, speed, and reliability developers and enterprises expect.
50T+
Flag evaluations per day
< 200ms
Global change propagation
99.99%
Enterprise uptime SLA
SOC 2 Type II
Certified
ISO 27001
Certified
ISO 27701
Certified
DPF
Data privacy program in accordance with privacy laws including GDPR
We fit right in.
Whatever your stack,
we’ve got you covered.
- 25+ SDKs across frontend, backend, and mobile.
- Works with tools like Claude Code, Cursor, terminal, and your IDE.
- Integrates with your CI/CD and observability tools.
Works across your entire workflow.
GitHub
Gitlab
Vercel
Datadog
Elastic
Cloudflare
Segment
Sentry
VS Code
Cursor
Claude
Frequently Asked Questions (FAQs)
Yes. LaunchDarkly support agents through MCP (Model Context Protocol), CLI, and IDE integrations, allowing AI assistants to interact with LaunchDarkly directly.
