Statsig Release Notes

You can now remove an individual user from a Feature Gate override without touching the rest of the list.

What you can do now

One new endpoint is available on statsigapi.net/console/v1/ :

DELETE /console/v1/gates/{gateName}/overrides/userID/{userID}

Why this matters

Before this, removing a single user override meant fetching the full override list, mutating it locally, and re-posting it, which could be risky when test runs are happening concurrently. Now, you can target and remove exactly one user, leaving every other override untouched.

Try it out

Review the full API reference in the Statsig Console API docs.

Statsig Topline Alerts can now page PagerDuty directly.

What you can do now

• Add PagerDuty services to the Integrations catalog once with a name and Events API v2 routing key.
• Select one or more PagerDuty services per alert in the Notifications settings.
• Test your wiring end-to-end before you rely on it — test pages are tagged [TEST] and never collide with real incidents.
• Deleting a PagerDuty service that an alert still references is blocked, and disabled integrations are clearly flagged.

Why this matters

Topline Alerts catch anomalies in your most critical product metrics, but a notification that in Slack or email isn't always enough when something is on fire. Now, the same alert that fires in Statsig can page your on-call team in PagerDuty, closing the gap between detecting a problem and fixing it quickly.

Try it out

Go to Integrations in the Statsig console, add your PagerDuty service, then open any Topline Alert and configure PagerDuty under Notifications.
Learn more in the Statsig Topline Alerts docs.

✅ Autotune Reviews via Console, Console API, and MCP

You can now submit Autotune changes for review and manage the full review lifecycle across the console, Console API, and MCP.

What you can do now

• Submit Autotune configuration changes for review before they reach production.
• Approve, reject, or cancel in-flight Autotune reviews from the console, via CAPI, or through the MCP.
• Teams with reviews required can now enforce that same approval workflow on Autotunes, the same way they do for gates and experiments.

Why this matters

Teams running Autotune for high-stakes decisions need the same guardrails they have everywhere else. Any change to a live Autotune can shift traffic allocation immediately, so being able to require an approval before it goes out matters. Reviews are now consistent across gates, experiments, and Autotunes.

Try it out

If you have the Statsig MCP set up, try a prompt like:

"Using the Statsig MCP, open a review to update the winner threshold on autotune_name and submit it for approval."

Learn more in the Statsig Reviews docs.

You can now separate the ability to delete configs from the ability to edit them.

What you can do now

• Manage Edit, Archive, and Delete as distinct permissions on your Role Permissions page

Why this matters

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.

FYI!

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.

Try it out

Learn more in the

Statsig Access Management docs

.

The full experiment review lifecycle is now accessible over the Console API and the Statsig MCP.

What you can do now

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

Why this matters

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.

Try it out

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
.

🔎 Audit Overrides Across Your Entire Project

You can now query all overrides across your project in a single API call.

What you can do now

We now have one new endpoint available on statsigapi.net/console/v1/ :

GET /console/v1/overrides

Why this matters

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.

Try it out

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.

What you can do now

• Follow a Dynamic Config to receive notifications whenever it's updated
• Unfollow at any time to stop receiving notifications

Why this matters

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.

Try it out

Open a Dynamic Config in the Statsig console and click Follow to subscribe to updates.
Learn more in the Statsig Console docs.

Feature Gate Reviews in the Console API

The full feature gate review lifecycle is now exposed over the Console API.

What you can do now

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

Why this matters

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.

Try it out

Review the full API reference in the Statsig Console API docs.

🗄️ Parameter Store Management in the Statsig MCP

You can now create and manage Parameter Stores directly through the Statsig MCP.

What you can do now

Three new tools are available on

api.statsig.com/v1/mcp

:

• Create_Param_Store
• Update_Param_Store
• Delete_Param_Store

Why this matters

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.

Try it out

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.

What you can do now

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.

Why this matters

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, and experiment reads got a lot leaner.

What you can do now

Read-only MCP access

• Users on a read-only role can now connect to the Statsig MCP and use it for analysis workflows.

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.

Why this matters

Now teams can give people who are on a read-only role access to use Statsig MCP for analysis. And for agentic workflows reasoning across many experiments, pulling full payloads burns through context windows fast. Field trimming and batching keep those workflows lean.

Try it out

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.

What you can do now

• 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

Why this matters

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.

Try it out

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.

What you can do now

• 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.

Why this matters

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.

Try it out

Review the full API reference in the Statsig Console API docs.

Statsig MCP now lets you pull the full edit history of any Feature Gate, Experiment, or Dynamic Config without a console.

What you can do now

• Retrieve the complete version timeline for a feature gate, experiment, or dynamic config.
• See who made each change, when, and exactly what was modified: rules, ID type, enabled state, allocation, variants, and values.
• Access config history programmatically to power agentic workflows that reason about how configs have changed over time.

Three new tools are available on api.statsig.com/v1/mcp:

• Get_Gate_Version_History
• Get_Experiment_Version_History
• Get_Dynamic_Config_Version_History

Why this matters

Config history is critical for debugging, incident reviews, and agentic reasoning, but it's been locked behind manual console navigation. Now, you can understand when behavior changed, reconstruct a timeline for an incident post-mortem or feed agents that need to detect or reason about config drift over time.

Try it out

If you have the Statsig MCP, try a prompt like:

• "Using the Statsig MCP, pull the version history for gate feature-gate-name and summarize what changed across versions."

Learn more in the docs: Statsig MCP Overview.

Today, we’re launching agent-skills, our new public repository for reusable Statsig skills. It’s designed to help teams run common Statsig workflows faster and more consistently from AI agents.

What you can do now

• Create Dashboard: Generate Statsig dashboards with a repeatable, structured workflow instead of manual one-off setup.
• Create Cloud Metric: Define cloud metrics through a guided skill flow, including key configuration steps that are easy to miss in ad hoc API calls.

Why this matters

Skills turn complex Statsig workflows into repeatable, shareable agent instructions you can personalize or share and reuse across your team's projects. With Skills, you can direct your agents to execute multi-step logic, stitching together Console API calls, MCP tool calls, and prompt instructions.

Getting started

1. Ensure you have a Console API Key -- this is required for the skill to carry out Statsig Console API actions.
2. Install the Statsig agent-skills repo with the Vercel skills CLI:

npx skills add statsig-io/agent-skills

1. Instruct your agent to use the skill (e.g., "Codex, help me create a cloud ratio metric for checkout rate).
2. Watch your agent follow your direction and the skill instructions to work with Statsig!

Explore the repo and start building repeatable Statsig workflows: statsig-io/agent-skills.