Kontak 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 Kontak 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 Kontak. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Kontak?"
)
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 Kontak MCP Server
Connect your AI agent to Kontak to automate your customer communications and message auditing.
LlamaIndex agents combine Kontak 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.
Key Features
- Unified Messaging history — List and audit all sent and received SMS and call logs
- Contact Management — Access and manage your Kontak address book via natural language
- Outbound SMS — Send text messages to customers directly from your chat client
- Template Access — Browse available message templates for consistent communication
- Audit & Analytics — Retrieve system logs and account metadata to monitor performance
Quick Setup
1. Subscribe to this server
2. Log in to your Kontak account, go to API Settings and generate a Bearer Token
3. Enter your token in the configuration panel
4. Start managing your communications via chat
The Kontak 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 Kontak to LlamaIndex via MCP
Follow these steps to integrate the Kontak 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 Kontak
Why Use LlamaIndex with the Kontak MCP Server
LlamaIndex provides unique advantages when paired with Kontak through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Kontak tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Kontak tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Kontak, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Kontak tools were called, what data was returned, and how it influenced the final answer
Kontak + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Kontak MCP Server delivers measurable value.
Hybrid search: combine Kontak real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Kontak 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 Kontak for fresh data
Analytical workflows: chain Kontak queries with LlamaIndex's data connectors to build multi-source analytical reports
Kontak MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Kontak to LlamaIndex via MCP:
get_contact_details
Get details for a specific contact
get_kontak_account_info
Get account settings and info
get_kontak_audit_logs
Retrieve system audit logs
get_message_details
Get details for a specific message
list_kontak_contacts
List all contacts
list_kontak_messages
List all sent and received messages
list_kontak_tags
List all contact tags
list_kontak_templates
List available message templates
list_kontak_webhooks
List configured webhooks
send_outbound_sms
Send a new SMS message
Example Prompts for Kontak in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Kontak immediately.
"List the last 5 messages from my Kontak account"
"Send an SMS to +1987654321 saying 'Hello from AI'"
"Find contact named 'Robert'"
Troubleshooting Kontak MCP Server with LlamaIndex
Common issues when connecting Kontak to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpKontak + LlamaIndex FAQ
Common questions about integrating Kontak 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 Kontak 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 Kontak to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.