VWO MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add VWO as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to VWO. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in VWO?"
)
print(response)
asyncio.run(main())
* 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.
LlamaIndex agents combine VWO tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the VWO MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from VWO
Why Use LlamaIndex with the VWO MCP Server
LlamaIndex provides unique advantages when paired with VWO through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine VWO tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain VWO tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query VWO, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what VWO tools were called, what data was returned, and how it influenced the final answer
VWO + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the VWO MCP Server delivers measurable value.
Hybrid search: combine VWO real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query VWO to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying VWO for fresh data
Analytical workflows: chain VWO queries with LlamaIndex's data connectors to build multi-source analytical reports
VWO MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect VWO to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting VWO to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpVWO + LlamaIndex FAQ
Common questions about integrating VWO MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect VWO with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect VWO to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.