Klevu (E-commerce AI Search) 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 Klevu (E-commerce AI Search) as an MCP tool provider through 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 Klevu (E-commerce AI Search). "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Klevu (E-commerce AI Search)?"
)
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 Klevu (E-commerce AI Search) MCP Server
Connect your Klevu account to any AI agent and take full control of your e-commerce search foundation and product discovery through natural conversation.
LlamaIndex agents combine Klevu (E-commerce AI Search) 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
- AI Keyword Search — Execute high-relevancy keyword searches against your product catalog, categories, and CMS pages directly from your agent
- Category Merchandising — Retrieve products configured for specific category navigation paths to audit smart merchandising rules and display sequences
- Facet & Filter Analytics — Perform complex filtered searches using explicit facets like color, size, or brand to identify specific product segments
- Predictive Autocomplete — Access fast autocomplete suggestions and popular product matches based on partial search terms to improve UX navigation
- ML Recommendations — Fetch visually similar, frequently bought together, or trending product recommendations driven by Klevu's machine learning models
- Trending Intelligence — Monitor global product velocity and relevance to identify top-selling items and seasonal trends across your entire store
- Raw API Access — Execute custom JSON search payloads for deeply nested query configurations and specific V2 API settings
The Klevu (E-commerce AI Search) 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 Klevu (E-commerce AI Search) to LlamaIndex via MCP
Follow these steps to integrate the Klevu (E-commerce AI Search) 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 Klevu (E-commerce AI Search)
Why Use LlamaIndex with the Klevu (E-commerce AI Search) MCP Server
LlamaIndex provides unique advantages when paired with Klevu (E-commerce AI Search) through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Klevu (E-commerce AI Search) tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Klevu (E-commerce AI Search) tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Klevu (E-commerce AI Search), a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Klevu (E-commerce AI Search) tools were called, what data was returned, and how it influenced the final answer
Klevu (E-commerce AI Search) + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Klevu (E-commerce AI Search) MCP Server delivers measurable value.
Hybrid search: combine Klevu (E-commerce AI Search) real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Klevu (E-commerce AI Search) 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 Klevu (E-commerce AI Search) for fresh data
Analytical workflows: chain Klevu (E-commerce AI Search) queries with LlamaIndex's data connectors to build multi-source analytical reports
Klevu (E-commerce AI Search) MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Klevu (E-commerce AI Search) to LlamaIndex via MCP:
search_autocomplete
Fetch search autocomplete suggestions as the user types
search_category
Retrieve products for a specific category page (Smart Category Merchandising)
search_filtered
g., color, size, brand) applied to narrow down the result set. Search the Klevu catalog with specific facet filters applied
search_keyword
Search catalog by keyword using Klevu AI
search_pagination
Retrieve paginated results for a search query
search_product_id
Retrieve details for a specific catalog product by ID
search_raw
Execute a custom JSON search payload against the Klevu API
search_recs
Fetch Klevu AI product recommendations
search_sorted
Perform a keyword search with a custom sorting order
search_trending
View currently trending and most relevant global products
Example Prompts for Klevu (E-commerce AI Search) in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Klevu (E-commerce AI Search) immediately.
"Search for 'waterproof jackets' in my Klevu catalog"
"Show me trending products for the 'Home Decor' category"
"Execute a filtered search for 'sneakers' with brand 'Nike'"
Troubleshooting Klevu (E-commerce AI Search) MCP Server with LlamaIndex
Common issues when connecting Klevu (E-commerce AI Search) to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpKlevu (E-commerce AI Search) + LlamaIndex FAQ
Common questions about integrating Klevu (E-commerce AI Search) 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 Klevu (E-commerce AI Search) with your favorite client
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Connect Klevu (E-commerce AI Search) to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.