Kavkom MCP Server for LlamaIndexGive LlamaIndex instant access to 7 tools to Create Contact, Get Call Details, List Calls, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Kavkom 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 App Connector for LlamaIndex
The Kavkom app connector for LlamaIndex is a standout in the Customer Support category — giving your AI agent 7 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Kavkom. "
"You have 7 tools available."
),
)
response = await agent.run(
"What tools are available in Kavkom?"
)
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 Kavkom MCP Server
Connect your Kavkom account to any AI agent and manage phone communications through natural conversation.
LlamaIndex agents combine Kavkom tool responses with indexed documents for comprehensive, grounded answers. Connect 7 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
- Contact Management — List and inspect contacts with call history
- Call Logs — Browse call history with duration, direction, and status
- Phone Lines — List available phone lines and their assignments
- Voicemail — Access voicemail messages with transcripts
- Call Recordings — Retrieve and review call recordings
The Kavkom MCP Server exposes 7 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.
All 7 Kavkom tools available for LlamaIndex
When LlamaIndex connects to Kavkom through Vinkius, your AI agent gets direct access to every tool listed below — spanning cloud-telephony, ivr, call-routing, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Add a new contact
Get details for a specific call
List Kavkom call history
List synced contacts
List sent and received SMS
List account users
Send an SMS message
Connect Kavkom to LlamaIndex via MCP
Follow these steps to wire Kavkom into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Kavkom MCP Server
LlamaIndex provides unique advantages when paired with Kavkom through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Kavkom tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Kavkom tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Kavkom, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Kavkom tools were called, what data was returned, and how it influenced the final answer
Kavkom + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Kavkom MCP Server delivers measurable value.
Hybrid search: combine Kavkom real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Kavkom 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 Kavkom for fresh data
Analytical workflows: chain Kavkom queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Kavkom in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Kavkom immediately.
"Show today's call log and any pending voicemails."
"List all contacts and the phone lines assigned to the team."
"Show call recordings from this week for the sales line."
Troubleshooting Kavkom MCP Server with LlamaIndex
Common issues when connecting Kavkom to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpKavkom + LlamaIndex FAQ
Common questions about integrating Kavkom MCP Server with LlamaIndex.