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.

VWO MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: VWO
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect VWO through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "vwo": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using VWO, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About VWO MCP Server

Connect your VWO (Visual Website Optimizer) account to any AI agent and take control of your experimentation and feature rollout workflows through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with VWO through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

What you can do

Optimization Campaigns — List and monitor active A/B tests and personalization campaigns directly from your agent
Feature Management — List all feature flags and toggle their status across different environments for instant rollouts
Experiment Results — Retrieve statistical results for any campaign, including performance metrics and significance levels
Conversion Tracking — Browse conversion goals and KPIs being tracked to understand your optimization impact
Audience Segmentation — List pre-defined segments to see how you are targeting different user groups
Environment Control — Manage features across staging, production, and other configured VWO environments

The VWO MCP Server exposes 10 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect VWO to LangChain via MCP

Follow these steps to integrate the VWO MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 10 tools from VWO via MCP

Why Use LangChain with the VWO MCP Server

LangChain provides unique advantages when paired with VWO through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine VWO MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across VWO queries for multi-turn workflows

VWO + LangChain Use Cases

Practical scenarios where LangChain combined with the VWO MCP Server delivers measurable value.

RAG with live data: combine VWO tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query VWO, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain VWO tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every VWO tool call, measure latency, and optimize your agent's performance

VWO MCP Tools for LangChain (10)

These 10 tools become available when you connect VWO to LangChain via MCP:

get_campaign_details

Retrieves details for a specific VWO campaign

get_campaign_results

Retrieves statistical results for a VWO campaign

get_feature_flag_details

Retrieves configuration for a specific VWO feature flag

get_vwo_account_info

Retrieves details about the authenticated VWO account

list_audience_segments

Lists all audience segments

list_conversion_goals

g. clicks, revenue) are being tracked. Lists all conversion goals and metrics

list_feature_flags

Lists all VWO feature flags

list_optimization_campaigns

Lists all VWO A/B test and personalization campaigns

list_vwo_environments

g. Production, Staging) for feature flag management. Lists all configured VWO environments

toggle_feature_flag

Provide the feature ID and the desired enabled status (true/false). Enables or disables a VWO feature flag

Example Prompts for VWO in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with VWO immediately.

"List all my active A/B testing campaigns."

"What are the results for the 'Checkout Flow Optimization' campaign?"

"Disable the feature flag for 'new_payment_gateway'."

Troubleshooting VWO MCP Server with LangChain

Common issues when connecting VWO to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

VWO + LangChain FAQ

Common questions about integrating VWO MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.