Unleash MCP. Audit feature flags, environments, and user contexts instantly.
Unleash connects your AI agent directly to your feature flag system. It lets you manage complex product rollouts—from auditing environments to checking if a specific user sees a new beta feature—all through natural conversation. You can evaluate flags, list projects, and monitor usage metrics without ever opening the Unleash UI.
Give Claude and any AI agent real-world access
List every project, environment, and segment defined in your Unleash system to understand the full scope of your feature management.
Evaluate which features are enabled for a specific user, or based on client properties, simulating how your application will render flags in real time.
Get comprehensive details on all feature flags within a project, verifying their current rollout status and strategy configurations.
Report flag usage data from both backend SDKs and frontend clients directly through the agent's tools.
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What AI agents can do with Unleash (Feature Toggles): 11 Tools Available
These tools give your AI agent programmatic access to every core function of your feature flag system, allowing you to audit configurations and track usage data directly.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Unleash (Feature Toggles) MCPList Environments
Retrieves a comprehensive list of all operational environments configured in Unleash.
List Project Features
Lists every single feature flag defined within a specific project ID.
List Projects
Fetches an exhaustive list of all projects managed by Unleash.
List Segments
Retrieves details on every user segment configured in your feature management system.
List Users
Provides a list of all individual users and their associated IDs within Unleash.
Get Client Features
Fetches the complete set of feature flags and strategies for server-side evaluation.
Report Client Metrics
Sends flag usage metrics data reported from a backend SDK instance.
Register Client
Registers and authenticates a new backend SDK instance for metric reporting.
Get Frontend Features
Determines which feature flags are enabled by optionally providing context like user...
Report Frontend Metrics
Sends flag usage metrics data reported from a frontend SDK instance.
Register Frontend
Registers and authenticates a new frontend SDK instance for metric reporting.
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Unleash (Feature Toggles), then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
- Connections are secured and governed automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Unleash. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Auditing your feature rollout status used to mean jumping between five different tabs.
Today, checking the full scope of a new release is tedious. You have to navigate to the Project list, then check the environments, and for every single flag, you might need to cross-reference segments or users just to see who gets access. It's clicking through dashboards until your finger hurts.
With this MCP, that entire audit becomes a conversation. Ask your agent to 'List all projects and their associated environments.' You get the full infrastructure map instantly. What changes is that you stop navigating; you start asking.
Unleash (Feature Toggles) gives you real-time feature context.
Previously, if a developer wanted to know how the code would behave for a specific user in a test environment, they had to manually simulate that user's properties and run checks. This was slow and error-prone.
Now, you can pass context variables directly to your agent. By using `get_frontend_features`, you tell your AI client exactly who the user is and what their profile looks like, so it evaluates the flags correctly, every single time.
What Unleash MCP does for your AI
Managing features across different parts of your application is complicated. You need to know if 'new-dashboard-v2' should only show up for internal users or if it’s rolled out globally, depending on where the request comes from. This MCP gives your agent full control over that process.
It lets you audit your entire feature setup—listing all projects and environments configured across your infrastructure. You can verify targeting rules by listing users and segments, checking who is supposed to see what. Need to know if a flag works for the backend or only on the client side? The agent handles it.
Plus, you don't have to manually report usage metrics; you can send that data straight back through your AI client, making sure everything stays synced. When you connect this MCP via Vinkius, your entire feature lifecycle becomes conversational.
019e3902-039a-71b2-97c4-7a329a71a79f How to set up Unleash MCP
The bottom line is you gain an API-driven conversational interface to manage complex, mission-critical feature rollouts without writing code or navigating web UIs.
Subscribe to this MCP, then enter your Unleash API URL and the required API Token (whether it’s for Admin, Client, or Frontend access).
Your AI client authenticates with the platform, giving your agent full read/write control over feature flag data.
You simply ask your agent questions—like 'What flags are active for user 123?'—and get immediate answers backed by your Unleash source of truth.
Who uses Unleash MCP
DevOps engineers who get frustrated having to click through multiple dashboards just to check a flag's status. Product Managers who need instant confirmation of rollout scope before announcing a feature, and Software Engineers who want to verify flag evaluation context right from their editor.
Quickly auditing environments and segments across multiple projects without leaving the command line or chat window.
Checking the status of a feature toggle's rollout strategy across different user groups or markets for a planned launch.
Verifying flag evaluations and context properties directly while coding, ensuring features behave correctly before testing even begins.
Benefits of connecting Unleash MCP
Stop relying on guesswork. You can check the exact status of a feature flag for a specific user context using the get_frontend_features tool, verifying visibility before code deployment.
Gain total infrastructure oversight by running list_projects, list_environments, and list_segments directly through your agent—all without leaving your chat interface.
Automate metric reporting. Instead of manually compiling usage data, you can use report_client_metrics or report_frontend_metrics to feed live analytics back into the system.
Simplify user validation. The agent lets you call list_users and list_segments, allowing you to quickly verify targeting rules for complex rollouts.
Speed up development cycles. You can use get_client_features to audit the entire feature set on the server side, making sure all flags are accounted for before a major release.
Unleash MCP use cases
Checking Rollout Scope for a Beta Feature
A PM needs to confirm if the 'new-dashboard-v2' feature is visible only to internal users. They ask their agent, and it uses get_frontend_features to check the flag status using specific user properties, providing an instant yes/no answer without needing a sandbox environment.
Auditing Multi-Environment Configuration
An SRE suspects a staging environment is configured incorrectly. They use list_environments and then list_projects to quickly map out the entire infrastructure layout, identifying which project belongs to which deployment stage.
Verifying Backend Feature Availability
A developer needs to know if a certain feature is enabled for the backend API. They ask their agent, and it invokes get_client_features, returning the full server-side flag status list immediately.
Tracking Live User Behavior
The team needs to track how often users interact with a new checkout flow. An engineer uses register_frontend first, then calls report_frontend_metrics, ensuring the usage data flows back into their analytics dashboard.
Unleash MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Assuming Flag Status
A developer assumes a feature is enabled because they saw it in documentation, but fail to check its current status against active user contexts.
Always verify the flag state using get_frontend_features by providing the target User ID and relevant context properties. This guarantees you're working with the live system truth.
Manually Listing Everything
A PM has to jump between the Environments tab, Projects list, and Users section of the Unleash UI just to get an overview.
Use list_environments combined with list_projects through your agent. You get a single, comprehensive audit report in one conversation.
Missing Context on Reporting
The team reports usage metrics without specifying if the data came from the client or the backend SDK.
Be precise: use report_client_metrics for backend data, and register_frontend followed by report_frontend_metrics for web-based user activity.
When to use Unleash MCP
Use this MCP if your primary pain point is the complexity of feature governance. You need to programmatically audit, evaluate, or report on feature flag states across multiple contexts (client vs. server). This tool shines when you need to answer questions like, 'For user X in environment Y, should feature Z be visible?'
Don't use this if your goal is simple CRUD operations outside of flags—like just managing API keys or sending emails; those require a messaging MCP. Also, don't use it if you only need to list projects once and never check status again; simply reading the list_projects tool might suffice.
However, you must use this if you need to combine multiple actions: checking project details (list_projects), verifying segments (list_segments), AND evaluating flags for a user context (get_frontend_features). The combination of tools is what makes it powerful.
Frequently asked questions about Unleash MCP
How do I check if a feature flag works on the backend with Unleash (Feature Toggles) MCP? +
You use the get_client_features tool. This fetches all feature flags and strategies specifically for server-side evaluation, giving you the definitive backend status.
Can I list user data using Unleash (Feature Toggles) MCP? +
Yes, use the list_users tool. It fetches a comprehensive list of all users configured in your feature management system so you can verify targeting rules.
What if I need to track usage data from my mobile app? Should I use Unleash (Feature Toggles) MCP? +
Yes. You should register the client using register_client and then send usage metrics with report_client_metrics to ensure your backend SDK is reporting accurately.
Is Unleash (Feature Toggles) MCP better than just checking flags in the UI? +
Absolutely. The agent allows you to chain together multiple checks—like listing projects, then checking flag status for a segment—in one go, which is impossible manually.
How do I ensure my frontend metrics are tracked correctly with Unleash (Feature Toggles) MCP? +
First, use register_frontend to authenticate the web instance. Then, pass usage data via report_frontend_metrics for accurate front-end tracking.