Zakeke MCP Server for LlamaIndex 9 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Zakeke 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 Zakeke. "
"You have 9 tools available."
),
)
response = await agent.run(
"What tools are available in Zakeke?"
)
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 Zakeke MCP Server
Connect your Zakeke account to any AI agent to streamline your visual product customization and 3D configuration workflows. This MCP server enables your agent to interact with customer designs, 3D compositions, and specialized e-commerce orders directly.
LlamaIndex agents combine Zakeke tool responses with indexed documents for comprehensive, grounded answers. Connect 9 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
- Design Oversight — List and retrieve detailed configurations for visual product designs created by your customers
- 3D Configuration Management — Access pricing and attribute data for complex 3D product compositions
- Order Synchronization — Query and monitor orders containing customized products to ensure smooth fulfillment
- Print-Ready Access — Retrieve ZIP files of all output files for production-ready designs instantly
- Cart Integration — Get necessary technical data to add 3D configured products to any shopping cart
The Zakeke MCP Server exposes 9 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 Zakeke to LlamaIndex via MCP
Follow these steps to integrate the Zakeke 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 9 tools from Zakeke
Why Use LlamaIndex with the Zakeke MCP Server
LlamaIndex provides unique advantages when paired with Zakeke through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Zakeke tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Zakeke tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Zakeke, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Zakeke tools were called, what data was returned, and how it influenced the final answer
Zakeke + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Zakeke MCP Server delivers measurable value.
Hybrid search: combine Zakeke real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Zakeke 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 Zakeke for fresh data
Analytical workflows: chain Zakeke queries with LlamaIndex's data connectors to build multi-source analytical reports
Zakeke MCP Tools for LlamaIndex (9)
These 9 tools become available when you connect Zakeke to LlamaIndex via MCP:
get_cart_info
Get cart information for a 3D configuration
get_composition_details
Get details for a specific 3D configuration
get_design_details
Get details for a specific design
get_design_print_files
Get ZIP file of print-ready outputs for a design
get_order_details
Get details for a specific order
list_compositions
List all 3D product configurations
list_designs
List all customer-created designs
list_orders
List all customized product orders
list_products
List all products available for customization
Example Prompts for Zakeke in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Zakeke immediately.
"Show me all visual designs created by customers today in Zakeke."
"List my customized product orders from Zakeke."
"Get the print-ready ZIP for design ID 'DESIGN_12345'."
Troubleshooting Zakeke MCP Server with LlamaIndex
Common issues when connecting Zakeke to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpZakeke + LlamaIndex FAQ
Common questions about integrating Zakeke 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 Zakeke 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 Zakeke to LlamaIndex
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.