How to Use the Konnektive MCP in LlamaIndex

Q: Can LlamaIndex search through Konnektive billing campaigns?

Yes, the agent can call listbillingcampaigns to pull active offers and index them. This allows your RAG pipeline to recommend specific campaigns to users based on their search queries.

Q: Can I filter which MCP tools are exposed to the agent?

Yes, you can use the allowedtools filter when initializing the tool spec. This lets you restrict write operations like updateordershippingaddress if you only want to build a read-only search agent.

Q: How does this MCP Server protect Konnektive shipping addresses and billing details?

No shipping addresses or billing data retrieved via getorderdetails are stored on Vinkius servers. The server operates as a secure, ephemeral gateway, transmitting data directly to your local LlamaIndex environment over an encrypted connection.

Build RAG applications that index live Konnektive data directly into your LlamaIndex vector store.

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Connect Konnektive MCP to LlamaIndex

Create your Vinkius account to connect Konnektive 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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Setup Konnektive with LlamaIndex

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Index Konnektive CRM data into LlamaIndex

This MCP Server exposes `query_konnektive_customers` and `get_customer_details` to LlamaIndex so you can feed live customer profiles into your vector stores. Stop letting your customer support data sit idle in static tables. You can query past interactions and get answers grounded in real CRM history rather than model guesses. The integration allows you to build knowledge-augmented workflows. When a customer asks about their subscription status, the agent uses `get_customer_details` to fetch the record, indexes it on the fly, and generates a personalized response. It bridges the gap between your raw billing database and your semantic search engine.

Query live transaction logs with semantic search

This MCP Server uses `query_konnektive_transactions` and `get_konnektive_audit_logs` to feed payment records directly into your LlamaIndex semantic search index. Finding specific billing anomalies usually requires complex SQL queries. You can then ask natural language questions like "show me recent failed transactions that look like duplicate charges." The agent uses `get_konnektive_audit_logs` to retrieve the system history and feed it directly into your index. This means your support team can search through technical system logs using simple, plain-English questions. It turns raw audit trails into an interactive knowledge base.

Map products and fulfillment centers dynamically

Your LlamaIndex agent uses `list_konnektive_products` and `list_fulfillment_houses` to map current inventory levels across different shipping hubs. Keep your inventory context fresh. LlamaIndex stores this mapping in memory to guide the agent's routing decisions. If a shipping address needs to be updated, the agent pulls the order details via `get_order_details` and runs `update_order_shipping_address` with the corrected details. The updated order state is immediately re-indexed, ensuring the agent's internal knowledge base remains perfectly synchronized with the CRM.

Setup guide

Set up Konnektive MCP in LlamaIndex

Prerequisites

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

1

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

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Konnektive MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
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 Konnektive tools.",
)
response = await agent.run("List recent Konnektive data")

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

Install llama-index-tools-mcp and initialize the BasicMCPClient with your Vinkius server URL. Wrap it in McpToolSpec and pass the converted tool list to your FunctionAgent.

Yes, the agent can call list_billing_campaigns to pull active offers and index them. This allows your RAG pipeline to recommend specific campaigns to users based on their search queries.

The FunctionAgent automatically structures the JSON filter strings for tools like query_konnektive_orders. It uses the schema metadata to ensure the parameters match what the CRM expects.

Yes, you can use the allowed_tools filter when initializing the tool spec. This lets you restrict write operations like update_order_shipping_address if you only want to build a read-only search agent.

No shipping addresses or billing data retrieved via get_order_details are stored on Vinkius servers. The server operates as a secure, ephemeral gateway, transmitting data directly to your local LlamaIndex environment over an encrypted connection.

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