VWO MCP. Analyze tests and toggle features from chat.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
VWO MCP Server manages A/B tests and feature flags directly through your AI agent. It lets you list active optimization campaigns, retrieve statistical performance results, check specific feature flag configurations, and toggle features across staging or production environments.
What your AI agents can do
Get campaign details
Pulls the setup information, parameters, and structure for a single VWO campaign.
Get campaign results
Retrieves statistical data on a specific VWO campaign, including performance metrics like conversion rate lift.
Get feature flag details
Shows the current configuration and scope for one particular feature flag.
Lists all ongoing A/B tests and personalization campaigns currently running on your site.
Retrieves the configuration details for a single feature flag, including its current status (on/off).
Fetches statistical results for any campaign, showing conversion rate lift and significance levels.
Lists all pre-defined audience segments used for testing or personalization efforts.
Enables or disables a feature flag by providing its ID and the desired boolean status (true/false).
Ask AI about this MCP
Supported MCP Clients
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VWO MCP Server: 10 Tools for Web Optimization
Use these tools to manage the entire web experimentation lifecycle—from listing goals to toggling live feature flags.
019d761dget campaign details
Pulls the setup information, parameters, and structure for a single VWO campaign.
019d761dget campaign results
Retrieves statistical data on a specific VWO campaign, including performance metrics like conversion rate lift.
019d761dget feature flag details
Shows the current configuration and scope for one particular feature flag.
019d761dget vwo account info
Retrieves basic account information to confirm which VWO client you are connected through.
019d761dlist audience segments
Lists all predefined user segments that your site uses for targeting and testing.
019d761dlist conversion goals
Returns a list of every conversion goal (e.g., signups, purchases) currently being measured on the site.
019d761dlist feature flags
Provides an inventory listing of all available feature flags in your VWO account.
019d761dlist optimization campaigns
Lists every active A/B test and personalization campaign running on the site.
019d761dlist vwo environments
Shows all configured VWO environments, such as Staging or Production.
019d761dtoggle feature flag
Changes the active status of a feature flag (on or off) across your specified environment.
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 every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with VWO, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
This server lets your AI agent manage everything in VWO, handling A/B testing campaigns and feature flag rollouts using natural language commands. You can list active tests and pull deep data on performance or tweak flags across staging and production environments.
Managing Optimization Campaigns
You'll start by listing every ongoing test or personalization campaign with list_optimization_campaigns. To see the specific setup details, including parameters and structure for any single test, you just run get_campaign_details. Once a test wraps up, your agent pulls statistical data using get_campaign_results; this shows things like conversion rate lift and whether the results are statistically significant.
You can track which variation won and by how much.
Controlling Feature Flags
To manage feature flags, you first get an inventory listing of every flag available in your VWO account using list_feature_flags. If you need to check what a specific flag is doing—its current configuration and scope—run get_feature_flag_details. To change the status of any flag across environments, use toggle_feature_flag, giving it an ID and telling it whether you want it on or off.
This lets you flip switches globally.
Defining Scope and Context
You need context to run these tests, so your agent can list all conversion goals currently being measured on the site via list_conversion_goals (like purchases or signups). For targeting groups, it pulls a list of every pre-defined user segment used for testing or personalization efforts with list_audience_segments. To know which VWO environments you’re working in—Staging or Production—you check the available settings using list_vwo_environments.
You can also confirm basic account details and verify which VWO client your agent is connected through by running get_vwo_account_info.
How VWO MCP Works
- 1 Subscribe to the VWO server and provide your API Token and Account ID.
- 2 Your AI client connects using natural conversation. You ask it to perform an action, like 'What are the results for camp-102?'
- 3 The agent calls
get_campaign_results, processes the data, and returns a plain English summary of the statistical winner.
The bottom line is you manage your entire web experimentation lifecycle from one chat window, instead of jumping between dashboards.
Who Is VWO MCP For?
Product Managers who need to push features live quickly. Growth Managers who spend hours manually exporting and comparing A/B test results. Data Analysts who have to track down conversion goal metrics across different user segments.
Checks get_campaign_results frequently to determine if a running A/B test has hit statistical significance, avoiding manual data pulls.
Uses the server to list environments (list_vwo_environments) and then runs toggle_feature_flag to deploy new features to staging or production.
Runs list_conversion_goals and list_audience_segments together to understand exactly which metrics are being tracked for specific user groups.
What Changes When You Connect
- Stop manual data exports. Instead of downloading spreadsheets to compare test results, simply ask the agent for
get_campaign_results. It gives you the winner and the statistical significance in one response. - Control rollouts instantly. Need to disable a feature flag globally? Use
toggle_feature_flag—you don't need to log into the dashboard. You just tell your AI client to flip the switch, referencing the correct ID. - Understand your scope immediately. Before starting any work, run
list_vwo_environmentsandget_vwo_account_info. This confirms which version (Staging vs. Production) you are talking about, eliminating deployment errors. - Map out dependencies easily. Need to know what features exist before testing? Run
list_feature_flagsfirst. Then, useget_feature_flag_detailson a specific flag to see its exact setup and scope. - Audit your metrics. Use
list_conversion_goalsto see every KPI you're tracking (e.g., clicks vs. revenue). This keeps your focus tight when running optimization campaigns. - Targeting is explicit. Instead of guessing who sees a test, use
list_audience_segments. Knowing the exact segment ID ensures your analysis isn't based on guesswork.
Real-World Use Cases
Rollback a faulty feature flag.
The Product Manager just pushed 'new_checkout_flow' to production, and it broke the funnel. They ask their agent to check list_feature_flags, identify the ID for 'new_checkout_flow', and then run toggle_feature_flag with the status set to false. The system confirms the rollback instantly.
Determine the winner of a complex test.
The Growth Manager has three running tests. They use list_optimization_campaigns to get all IDs, then run get_campaign_results on each one. The agent summarizes which variation achieved 98% statistical significance and how much conversion it improved.
Verify a feature is ready for launch.
The Ops Engineer needs to confirm that the 'beta_dashboard' flag is set up correctly in the Staging environment. They use list_vwo_environments to ensure they are scoped correctly, then run get_feature_flag_details to validate the configuration before telling their team it’s ready for UAT.
Analyze segment performance changes.
The Data Analyst wants to know if a specific high-value user group is reacting differently. They run list_audience_segments to get the ID, then ask their agent to cross-reference that segment with the conversion goals using list_conversion_goals. This pinpoints where performance gaps exist.
The Tradeoffs
Mixing up details and results.
A user runs get_campaign_details assuming it will tell them which variation performed better. It just gives them the setup, forcing them to manually run another call for results.
→
Don't stop at configuration. After running get_campaign_details, always follow up with get_campaign_results. That second tool is what tells you if the test actually worked.
Ignoring the environment context.
A developer runs a feature toggle command, assuming it's happening on Staging when it was configured for Production. This leads to accidental live changes.
→
Always start by running list_vwo_environments and confirm your scope. Then use the environment name when calling toggle_feature_flag.
Treating segments as static data.
Assuming that a segment list is exhaustive, they forget to verify which specific conversion goals are tied to that group's performance metrics.
→
Check the full picture. Run list_audience_segments first, then run list_conversion_goals. This gives you the two dimensions needed for accurate analysis.
When It Fits, When It Doesn't
Use this server if your job involves managing the full lifecycle of web experimentation—from setting up a test and defining its target audience to finally rolling it out or rolling it back. You need coordinated data: campaign setup + segment list + performance results. Don't use this if you only need to know 'how many flags do I have?' — list_feature_flags handles that simple inventory check. Also, don't use it for deep attribution modeling; it provides VWO's internal metrics, but cross-platform data linking requires external tools.
The key is: if you need to act (toggle a flag) or validate (check results), this server has the right tools.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by VWO. 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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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
The Dashboard Hopscotch
Today, checking on an A/B test feels like playing hopscotch across multiple tabs. You start in Campaign Management to list active tests, then click over to a separate 'Reports' tab to find the results. If you want to know what metrics matter for that specific campaign, you have to go hit the Goals dashboard and manually cross-reference everything.
With this MCP server, your AI agent handles the jump. You tell it: 'Give me the performance summary for camp-102.' It calls `get_campaign_results` and gives you a single, definitive answer without you touching another URL.
VWO MCP Server: Full Feature Control
Manual feature management means logging into the platform just to see if a flag is on or off. You have to check multiple environments (Staging, Prod) and manually verify its status before telling your team it's safe to use.
Now, you ask: 'What's the status of the new payment gateway feature?' The agent runs `get_feature_flag_details` across all listed environments in one go. It gives you a structured answer—it’s that simple.
Common Questions About VWO MCP
How do I find out which tests are running right now using list_optimization_campaigns? +
Run list_optimization_campaigns. This tool immediately gives you a comprehensive inventory of all active A/B test and personalization campaigns. It's your starting point for any analysis.
What is the difference between get_campaign_details and get_campaign_results? +
Details shows how the campaign was built (the parameters, setup, etc.). Results runs the math and tells you if it worked—it provides statistical significance on performance metrics.
Can I use toggle_feature_flag to switch a feature in Production? +
Yes, provided your credentials cover that environment. The toggle_feature_flag tool requires you specify the desired status (true/false) and confirms the update across all configured VWO environments.
What if I need to check multiple audience segments? +
First, use list_audience_segments to see every available segment ID. Then, you can ask for metrics related to those specific IDs using your AI client's context.
How do I verify my VWO account credentials before running any changes using get_vwo_account_info? +
It immediately returns your core account details and confirmed API access rights. This step is essential for troubleshooting setup issues or confirming the exact user context your agent is operating under.
Before I run a feature flag change, how do I list all available deployment environments with list_vwo_environments? +
It lists every environment (like Staging, Development, and Production) configured in your VWO account. This prevents you from accidentally targeting the wrong area when managing flags.
What specific metrics does the list_conversion_goals tool show for all tracked KPIs? +
The tool lists every conversion goal and associated metric being tracked. You'll get names, IDs, and the type of measurement (like clicks or revenue) without having to guess VWO’s tracking scope.
If I run get_campaign_results and receive an error, what does that typically mean? +
The error message directs you to the specific API limitation or permission problem. Usually, it means either the campaign ID is wrong, or your current token lacks read access for reporting metrics.
Can I check the winning variation of an A/B test through the agent? +
Yes. The get_campaign_results tool allows your AI agent to pull detailed performance metrics for any experiment, showing improvement percentages and statistical significance for each variation compared to the control.
Is it possible to enable or disable feature flags via chat? +
Absolutely. Using the toggle_feature_flag tool, you can instruct your agent to enable or disable any feature flag for a specific rollout or emergency kill-switch scenario, ensuring fast control without opening the VWO dashboard.
How can I see what conversion goals are being tracked for my campaigns? +
You can use the list_conversion_goals tool to retrieve all metrics and KPIs (like clicks, form submissions, or revenue) currently being monitored in your VWO account.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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