Unleash

Drive the product through a documented public API G

Agent access

Connect an agent via an official MCP server G

Agent access

Delegate tasks to a built-in AI assistant inside the product G

Agentic features

Plug MCP servers into this product so it can use their tools G

Agent access

Point an agent at llms.txt or agent-oriented docs G

Agent access

Build against official SDKs G

Agent access

Run the product headlessly / in CI for automation G

Agent access

Operate the product with natural-language commands G

Agentic features

Issue scoped/least-privilege API credentials for an agent G

Agent access

Set up automations that run autonomously in the background G

Agentic features

Download a machine-readable API spec (OpenAPI or equivalent) G

Api quality

Get AI-generated insights and suggestions from my data inside the product G

Agentic features

Rely on versioned APIs with a documented deprecation policy G

Api quality

Explore an interactive API reference with runnable examples G

Api quality

Subscribe to events via webhooks G

Agent access

Use an official CLI G

Agent access

Test against a sandbox environment without touching production data G

Api quality

Create a feature flag and toggle it live in production within minutes of signing up C

Flags

Roll a flag out progressively by percentage with consistent bucketing, ramping from 1% to 100% without redeploying C

Rollouts

Self-host the core product G

Self-host the full flag platform from an open-source distribution, keeping evaluation data on my infrastructure C

Self host

Require approvals or change requests before production flag changes go live C

Approvals

Create and toggle flags through documented APIs, CLIs, or MCP — and the platform can force my changes through approval workflows instead of letting me write to production unreviewed C

Agent ops

Target flags with attribute-based rules and reusable segments so the right users see the right variation C

Targeting

Define rules that trigger actions automatically on events G

Export all of my data in open formats and leave G

Run A/B and multivariate experiments on flags and see which variation wins on my metrics C

Experiments

My server SDKs evaluate flags locally from a cached ruleset — microsecond decisions with no network call per flag check C

Evaluation

Every flag change is recorded in an audit log — who changed what, when, and to which value G

Audit

Prevent my data from being used to train AI models G

Manage separate environments (dev/staging/prod) with independent flag states and scoped SDK keys C

Environments

Evaluate flags at the edge (CDN workers or an edge/relay layer) close to users C

Edge

Restrict who can change which flags with roles, permissions, and scoped API tokens C

Access

Do everything through the API that I can do in the UI G

Guard a rollout with metrics so a regression is detected and the release is rolled back automatically C

Rollouts

Serve multivariate flags and dynamic configuration values (strings, numbers, JSON), not just booleans C

Flags

Choose where my data is stored (region/residency) G

Read the product's source under an open license G

Use official SDKs across my whole stack — backend, web, and mobile — with consistent flag behavior C

Sdks

Flag changes propagate to connected SDKs in seconds via streaming or fast polling — a kill switch actually kills C

Streaming

Perform bulk operations across many items at once G

See published pricing and understand what drives cost (seats, MAUs, events, requests) before committing G

Pricing

Schedule recurring jobs or workflows G

Trust a documented statistics engine (Bayesian or frequentist, with variance-reduction options) behind experiment results C

Analysis

Control data retention and deletion G

Define experiment metrics from my own data — warehouse tables or ingested events — instead of a black-box metric store C

Metrics

Find stale flags and code references so temporary flags actually get removed from the codebase C

Lifecycle

Opt out of telemetry and usage tracking G

Run a relay/edge proxy so flags stay served when the vendor is unreachable and SDK traffic stays inside my network C

Proxy

Schedule flag changes and releases to happen at a specific future time C

Scheduling

Target or exclude specific individual users for a flag (allowlists, beta testers, internal accounts) C

Targeting

Read experiment configurations and results programmatically to summarize outcomes and recommend ship/rollback decisions C

Agent ops

Version, review, and roll back my automations G

Use the vendor through OpenFeature providers so my flag code isn't locked to one vendor's SDK API C

Standards