You can now separate the ability to delete configs from the ability to edit them.
Manage Edit, Archive, and Delete as distinct permissions on your Role Permissions page
Previously, delete was bundled into a single "Edit Delete Configs" permission with no way to separate them. Now, you can grant edit access broadly and keep delete access narrow, without having to create workarounds or roles with too many extra permissions.
This is opt-in and not on by default. To enable granular delete permissions for your organization, contact your Statsig account team. Once enabled, the separate Delete permission will appear on your Role Permissions page under Project Settings.
Learn more in the Statsig Access Management docs.
The full experiment review lifecycle is now accessible over the Console API and the Statsig MCP.
We now have eight new CAPI endpoints and niine new MCP tools cover the complete review lifecycle:
Create a review proposing a change to an experiment
List an experiment's reviews, newest first
Get a single review including status, proposed change, author, and reviewers
Look up who is eligible to approve or reject
Edit a pending review's metadata
Approve or reject an in-flight review
Cancel a pending review
Commit an approved review to apply it to the live experiment
Before, creating and moving an experiment review through approval required the console, blocking any automated workflow that touched a review-gated experiment. Now you can propose, approve, and commit experiment changes entirely through the API or MCP, with no manual console step in the way.
If you have the Statsig MCP set up, try a prompt like:
"Open a review to make a decision on
experiment_name, shipping the Test group."
Review the full API reference in the Statsig Console API docs.
You can now query all overrides across your project in a single API call.
We now have one new endpoint available on statsigapi.net/console/v1/:
GET /console/v1/overrides
Before , finding where a user was overridden meant querying each gate, experiment, and layer one by one. Now you can audit overrides project-wide in a single call, whether you're debugging unexpected behavior for a specific user, running a compliance audit, or cleaning up override sprawl.
Review the full API reference in the Statsig Overrides Audit docs.
You can now follow and unfollow Dynamic Configs to get notified when they're updated.
Follow a Dynamic Config to receive notifications whenever it's updated
Unfollow at any time to stop receiving notifications
Dynamic Configs often control things like API settings and rollout thresholds. Being able to follow means the right people get notified the moment a Dynamic Config updated, without having to watch the console or find out after the fact.
Open a Dynamic Config in the Statsig console and click Follow to subscribe to updates.
Learn more in the Statsig Console docs.
The full feature gate review lifecycle is now exposed over the Console API.
Eight new endpoints cover the complete review lifecycle:
POST /gates/:id/reviews create a review with the proposed change
GET /gates/:id/reviews list reviews, newest first
GET /gates/:id/reviews/:reviewID get a single review
PUT /gates/:id/reviews/:reviewID edit metadata or content
PUT /gates/:id/reviews/:reviewID/approve approve
PUT /gates/:id/reviews/:reviewID/reject reject
DELETE /gates/:id/reviews/:reviewID cancel an in-flight review
GET /gates/:id/eligible_reviewers look up eligible reviewers
Before , creating and moving a review through approval required the console, blocking any automated workflow that touched a review-gated gate. Now you can propose, approve, and commit gate changes entirely through the API, with no manual console step in the way.
Review the full API reference in the Statsig Console API docs.
You can now create and manage Parameter Stores directly through the Statsig MCP.
Three new tools are available on api.statsig.com/v1/mcp:
Create_Param_Store
Update_Param_Store
Delete_Param_Store
Now, you can create a store, define its parameters, and point them at a gate or experiment without leaving your agent flow, making end-to-end feature provisioning possible for the first time.
If you have the Statsig MCP set up, try a prompt like:
"Using the Statsig MCP, create a Parameter Store called checkout-config and add a static boolean parameter "express_checkout_enabled" set to true.
Learn more in the docs: Statsig MCP Overview.
Experiment reads just got a lot leaner and easier.
Trimmed and batched experiment reads
Fetch multiple experiments in a single call instead of one round-trip per experiment.
A single experiment trims from ~66 fields down to just what you ask for, achieving up to 95-99% context reduction.
For agentic workflows reasoning across many experiments, pulling full payloads burns through context windows fast. Field trimming and batching keep those workflows lean.
Learn more in the docs: Statsig MCP Overview.
The Statsig MCP now supports read-only users.
Read-only MCP access
Users on a read-only role can now connect to the Statsig MCP and use it for analysis workflows.
Now teams can give people who are on a read-only role access to use Statsig MCP for analysis.
If you have the Statsig MCP set up, try a prompt like: "Using the Statsig MCP, fetch experiments exp_a and exp_b and show only their hypothesis and primaryMetrics."
Learn more in the docs: Statsig MCP Overview.
Now, you can create an Autotune (multi-armed bandit) experiment directly through the Statsig MCP, no console required.
Create an Autotune by describing the arms, success event, exploration and attribution windows, and winner threshold.
Autotunes are created as drafts by default, so no traffic is reallocated until you start it from the console.
The agent confirms before writing, prompting for confirmation before anything is created.
One new tool is available on api.statsig.com/v1/mcp:
Create_autotune
Teams running Autotune for live AI agent experiments can now manage the full setup through agents. Instead of manually configuring a multi-armed bandit in the console, you can describe what you want and let the agent build it, keeping your agentic workflows end-to-end.
If you have the Statsig MCP set up, try a prompt like:
"Using the Statsig MCP, create an Autotune called checkout-button-color with a control variant {color: blue} and a treatment variant {color: green}, optimizing for the event 'checkout', with 24hr exploration and attribution windows and a 95% winner threshold."
Learn more in the docs: Statsig MCP Overview.
You can now delete individual experiment and layer overrides directly via the Console API, no GET-mutate-POST workaround needed.
Delete a single conditional or userID override from an experiment or layer via path-param DELETEs.
Target a specific environment with an optional environment query param, or omit it for the all-environments bucket.
Call these endpoints cleanly from OpenAPI-generated or SDK-based clients, since they use path and query params only with no DELETE body.
Four new endpoints are available on statsigapi.net/console/v1/:
DELETE /experiments/:id/overrides/conditional/:type/:name
DELETE /experiments/:id/overrides/userID/:userID
DELETE /layers/:id/overrides/conditional/:type/:name
DELETE /layers/:id/overrides/userID/:userID
:type is gate or segment. :name is the gate or segment name. All four endpoints are idempotent, returning 200 even when no matching override exists.
SDK-based E2E testing frameworks often need to clean up individual overrides between test runs. The previous approach required fetching the full overrides object, mutating it locally, and re-posting it, which is fragile and hard to parallelize. These endpoints make override teardown a single, safe, idempotent call.
Review the full API reference in the Statsig Console API docs.