Can I check the items in a specific data catalog?

Yes! Use the `get_catalog_items` tool with the Catalog ID. Your agent will fetch the items and their metadata directly from your Bloomreach instance.

How do I see all the customer segments I have created?

Simply ask the agent to `list_segments` or `list_segmentations`. It will retrieve the definitions and names of the customer groups you've configured in the Engagement platform.

Does the integration allow exporting customer properties?

Yes. Use the `get_customer_properties` tool with a registered Customer ID. The agent will retrieve core properties like name and email based on your project configuration.

Bloomreach MCP Server for LlamaIndex 10 tools — connect in under 2 minutes

Name: Bloomreach
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Bloomreach as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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 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 Bloomreach. "
            "You have 10 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Bloomreach?"
    )
    print(response)

asyncio.run(main())

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* 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 Bloomreach MCP Server

Connect your Bloomreach Engagement account to any AI agent and orchestrate your marketing automation and data workflows through natural conversation.

LlamaIndex agents combine Bloomreach tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through 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

Catalog Oversight — List and retrieve items from your data catalogs to ensure product and metadata accuracy.
Campaign Management — Query and monitor marketing campaigns to track outreach and performance.
Customer Segmentation — Access and list customer segments and segmentations for targeted marketing analysis.
Event Tracking Discovery — List all tracked event types to understand your data collection footprint.
Attribute & Property Auditing — Retrieve configured customer attributes and catalog properties.
Webhook Monitoring — List configured webhooks to verify real-time data integrations.

The Bloomreach 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 Bloomreach to LlamaIndex via MCP

Follow these steps to integrate the Bloomreach 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 Bloomreach

Why Use LlamaIndex with the Bloomreach MCP Server

LlamaIndex provides unique advantages when paired with Bloomreach through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Bloomreach tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Bloomreach tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Bloomreach, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Bloomreach tools were called, what data was returned, and how it influenced the final answer

Bloomreach + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Bloomreach MCP Server delivers measurable value.

Hybrid search: combine Bloomreach real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Bloomreach 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 Bloomreach for fresh data

Analytical workflows: chain Bloomreach queries with LlamaIndex's data connectors to build multi-source analytical reports

Bloomreach MCP Tools for LlamaIndex (10)

These 10 tools become available when you connect Bloomreach to LlamaIndex via MCP:

get_catalog_items

Retrieve items from a specific data catalog

get_customer_properties

Export properties for a specific registered customer

list_attributes

List all customer attributes

list_campaigns

List all marketing campaigns

list_catalogs

List all Bloomreach data catalogs

list_event_types

List all tracked event types

list_properties

List all catalog properties

list_segmentations

List all customer segmentations

list_segments

List all customer segments

list_webhooks

List configured webhooks

Example Prompts for Bloomreach in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Bloomreach immediately.

"List all active marketing campaigns in Bloomreach."

"Show me the items in the 'Top Products' catalog."

"List all customer segments."

Troubleshooting Bloomreach MCP Server with LlamaIndex

Common issues when connecting Bloomreach to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Bloomreach + LlamaIndex FAQ

Common questions about integrating Bloomreach MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Bloomreach tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.