Konnektive 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 Konnektive 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 Konnektive. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Konnektive?"
)
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 Konnektive MCP Server
Connect your AI agent to Konnektive CRM to automate and streamline your e-commerce operations.
LlamaIndex agents combine Konnektive 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.
Core Capabilities
- Order Management — Query and retrieve detailed information about customer orders including shipping and billing data
- Customer CRM Access — Search and audit customer profiles directly from your chat client
- Transaction Auditing — Track and verify payment transactions across your integrated gateways
- Product & Campaign Insights — List available products and active marketing campaigns to inform your strategy
- Administrative Actions — Update order shipping addresses and monitor system audit logs
Setup Requirements
1. Subscribe to this server
2. Obtain your API Login ID and API Password from the Konnektive dashboard (API settings)
3. Start managing your e-commerce data via natural language
The Konnektive 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 Konnektive to LlamaIndex via MCP
Follow these steps to integrate the Konnektive 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 Konnektive
Why Use LlamaIndex with the Konnektive MCP Server
LlamaIndex provides unique advantages when paired with Konnektive through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Konnektive tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Konnektive tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Konnektive, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Konnektive tools were called, what data was returned, and how it influenced the final answer
Konnektive + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Konnektive MCP Server delivers measurable value.
Hybrid search: combine Konnektive real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Konnektive 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 Konnektive for fresh data
Analytical workflows: chain Konnektive queries with LlamaIndex's data connectors to build multi-source analytical reports
Konnektive MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Konnektive to LlamaIndex via MCP:
get_customer_details
Get details for a specific customer
get_konnektive_audit_logs
Provide filters as a JSON string. Retrieve system audit logs
get_order_details
Get details for a specific order
list_billing_campaigns
List all campaigns
list_fulfillment_houses
List fulfillment centers
list_konnektive_products
List all products
query_konnektive_customers
Provide filters as a JSON string. Search for customers
query_konnektive_orders
Provide filters as a JSON string. Search for orders in Konnektive
query_konnektive_transactions
Provide filters as a JSON string. Search for payment transactions
update_order_shipping_address
Provide address as a JSON string. Update the shipping address for an order
Example Prompts for Konnektive in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Konnektive immediately.
"List all orders from yesterday"
"Show details for order 'ORD-12345'"
"Find customer with email 'jane@example.com'"
Troubleshooting Konnektive MCP Server with LlamaIndex
Common issues when connecting Konnektive to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpKonnektive + LlamaIndex FAQ
Common questions about integrating Konnektive 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 Konnektive 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 Konnektive to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.