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How to Use the Bazaarvoice MCP in LlamaIndex

Index live Bazaarvoice content into your LlamaIndex knowledge base for grounded, API-accurate answers.

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LlamaIndex

Connect Bazaarvoice MCP to LlamaIndex

Create your Vinkius account to connect Bazaarvoice to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Vectorize Bazaarvoice content for LlamaIndex

Use the `list_reviews` and `list_questions` tools to pull raw text into your index. LlamaIndex then creates embeddings for these inputs, allowing your agent to query past feedback. This stops your agent from guessing about product details. It retrieves the actual content stored in your Bazaarvoice account.

Query Bazaarvoice data with LlamaIndex RAG

Build a RAG pipeline that combines your documents with live `get_product` results. You get answers that reflect current inventory rather than stale cached data. Your index stays fresh because the agent executes the tools before finalizing an answer. This keeps your LlamaIndex application grounded in real-time information.

Filter Bazaarvoice tool access in LlamaIndex

Restrict which tools your agent can use by configuring the `allowed_tools` list. You keep control over your Bazaarvoice data access while letting the agent browse products. This approach limits the blast radius of your agents. Only the tools you explicitly permit will be available for execution.

Setup guide

Set up Bazaarvoice MCP in LlamaIndex

Prerequisites

  • Python 3.10+ installed
  • llama-index-tools-mcp package
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install dependencies

    Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.

  2. 2

    Connect with BasicMCPClient

    Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.

  3. 3

    Convert to LlamaIndex tools

    Call mcp_tool_spec.to_tool_list_async() to convert all Bazaarvoice MCP tools into native FunctionTool objects that any LlamaIndex agent can use.

  4. 4

    Run with any LLM

    Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Bazaarvoice tools.",
)
response = await agent.run("List recent Bazaarvoice data")

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Bazaarvoice. 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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Common questions about Bazaarvoice MCP in LlamaIndex

The MCP server feeds review text to your ingestion pipeline. LlamaIndex then chunks and embeds this data for semantic searching.
You call `list_products` to gather IDs. Then, you use those IDs to pull details into your searchable index.
It is. You pass the tools to your agent, which then queries the API based on the user's natural language request.
Yes. Since the tools fetch live data, your LlamaIndex application always sees the most recent reviews and questions.
Vinkius runs the server in an ephemeral container. Your Bazaarvoice authentication tokens are encrypted and strictly isolated.

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