Vapi 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 Vapi as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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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 Vapi. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Vapi?"
)
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 Vapi MCP Server
Connect your Vapi account to any AI agent and bring the power of automated voice communication into your standard conversational workspace.
LlamaIndex agents combine Vapi tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the 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
- Phone Calling — Send commands instructing the agent to place outbound human-like phone calls and establish web ringing connections through Vapi's PSTN/WebRTC capabilities.
- Call Transcripts — Search through recent call logs, retrieve call details natively, and pull raw voice-to-text transcripts or conversation metrics.
- Persona Engineering — Ask your chat agent to build new Vapi assistants, update their system prompts, change its specific model, or mutate Voice IDs on the fly.
- Squad Routing — List available telephony numbers, tools, and multi-agent squads natively to configure advanced conversational pathways.
The Vapi 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 Vapi to LlamaIndex via MCP
Follow these steps to integrate the Vapi 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 Vapi
Why Use LlamaIndex with the Vapi MCP Server
LlamaIndex provides unique advantages when paired with Vapi through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Vapi tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Vapi tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Vapi, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Vapi tools were called, what data was returned, and how it influenced the final answer
Vapi + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Vapi MCP Server delivers measurable value.
Hybrid search: combine Vapi real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Vapi 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 Vapi for fresh data
Analytical workflows: chain Vapi queries with LlamaIndex's data connectors to build multi-source analytical reports
Vapi MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Vapi to LlamaIndex via MCP:
create_assistant
Provide configuration for transcriber, model, and voice as a JSON string. Create a new Voice AI assistant persona
create_phone_call
Provide the phone number ID and customer details. Start a new outbound phone call via Vapi
create_web_call
Returns a web call configuration. Generate a new web-based voice call link
get_call_details
Retrieves details, transcripts, and metrics for a specific call
list_agent_tools
List all tools available to Vapi assistants
list_assistants
List all Voice AI assistants configured in Vapi
list_calls
List recent and active voice calls managed by Vapi
list_phone_numbers
List all phone numbers connected to Vapi
list_squads
List all multi-agent squads
update_assistant
Update an existing assistant configuration
Example Prompts for Vapi in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Vapi immediately.
"List all our configured Voice assistants and their IDs."
"Get the details and full transcript for call ID 'vapi1234'."
"Update assistant 'Bot Support' to change its `model.model` parameter to `gpt-4o-mini`."
Troubleshooting Vapi MCP Server with LlamaIndex
Common issues when connecting Vapi to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpVapi + LlamaIndex FAQ
Common questions about integrating Vapi 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 Vapi 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 Vapi to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.