Klevu (E-commerce AI Search) MCP Server for CrewAI 10 tools — connect in under 2 minutes
Connect your CrewAI agents to Klevu (E-commerce AI Search) through Vinkius, pass the Edge URL in the `mcps` parameter and every Klevu (E-commerce AI Search) tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
from crewai import Agent, Task, Crew
agent = Agent(
role="Klevu (E-commerce AI Search) Specialist",
goal="Help users interact with Klevu (E-commerce AI Search) effectively",
backstory=(
"You are an expert at leveraging Klevu (E-commerce AI Search) tools "
"for automation and data analysis."
),
# Your Vinkius token. get it at cloud.vinkius.com
mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)
task = Task(
description=(
"Explore all available tools in Klevu (E-commerce AI Search) "
"and summarize their capabilities."
),
agent=agent,
expected_output=(
"A detailed summary of 10 available tools "
"and what they can do."
),
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)
* 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.
When paired with CrewAI, Klevu (E-commerce AI Search) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Klevu (E-commerce AI Search) tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
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 CrewAI 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 CrewAI via MCP
Follow these steps to integrate the Klevu (E-commerce AI Search) MCP Server with CrewAI.
Install CrewAI
Run pip install crewai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Customize the agent
Adjust the role, goal, and backstory to fit your use case
Run the crew
Run python crew.py. CrewAI auto-discovers 10 tools from Klevu (E-commerce AI Search)
Why Use CrewAI with the Klevu (E-commerce AI Search) MCP Server
CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Klevu (E-commerce AI Search) through the Model Context Protocol.
Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools
CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime
Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls
Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
Klevu (E-commerce AI Search) + CrewAI Use Cases
Practical scenarios where CrewAI combined with the Klevu (E-commerce AI Search) MCP Server delivers measurable value.
Automated multi-step research: a reconnaissance agent queries Klevu (E-commerce AI Search) for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff
Scheduled intelligence reports: set up a crew that periodically queries Klevu (E-commerce AI Search), analyzes trends over time, and generates executive briefings in markdown or PDF format
Multi-source enrichment pipelines: chain Klevu (E-commerce AI Search) tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow
Compliance and audit automation: a compliance agent queries Klevu (E-commerce AI Search) against predefined policy rules, generates deviation reports, and routes findings to the appropriate team
Klevu (E-commerce AI Search) MCP Tools for CrewAI (10)
These 10 tools become available when you connect Klevu (E-commerce AI Search) to CrewAI 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 CrewAI
Ready-to-use prompts you can give your CrewAI 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 CrewAI
Common issues when connecting Klevu (E-commerce AI Search) to CrewAI through the Vinkius, and how to resolve them.
MCP tools not discovered
Agent not using tools
Timeout errors
Rate limiting or 429 errors
Klevu (E-commerce AI Search) + CrewAI FAQ
Common questions about integrating Klevu (E-commerce AI Search) MCP Server with CrewAI.
How does CrewAI discover and connect to MCP tools?
tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.Can different agents in the same crew use different MCP servers?
mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.What happens when an MCP tool call fails during a crew run?
Can CrewAI agents call multiple MCP tools in parallel?
process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.Can I run CrewAI crews on a schedule (cron)?
crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.Connect Klevu (E-commerce AI Search) with your favorite client
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Connect Klevu (E-commerce AI Search) to CrewAI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.