MiiTel MCP Server for LlamaIndexGive LlamaIndex instant access to 6 tools to Get Call Details, Get Meeting Details, List Calls, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add MiiTel 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 MiiTel app connector for LlamaIndex is a standout in the Customer Support category — giving your AI agent 6 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 MiiTel. "
"You have 6 tools available."
),
)
response = await agent.run(
"What tools are available in MiiTel?"
)
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 MiiTel MCP Server
Connect your MiiTel account to any AI agent and manage AI-powered speech analysis and call data through natural conversation.
LlamaIndex agents combine MiiTel tool responses with indexed documents for comprehensive, grounded answers. Connect 6 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
- Call Transcripts — Access full text transcriptions of sales and support calls
- Speech Analytics — Analyze talk ratio, speech rate, overlaps, and silence
- Recordings — Retrieve call recording metadata and audio links
- Agent Performance — Monitor call volume, duration, and conversion rates
- Emotion Analysis — Track sentiment and energy levels during conversations
The MiiTel MCP Server exposes 6 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 6 MiiTel tools available for LlamaIndex
When LlamaIndex connects to MiiTel through Vinkius, your AI agent gets direct access to every tool listed below — spanning call-transcription, speech-analytics, sentiment-analysis, 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.
Get details for a specific call
Get details for a specific meeting
List MiiTel call history
List MiiTel account users
List online meeting history
List CRM contacts
Connect MiiTel to LlamaIndex via MCP
Follow these steps to wire MiiTel 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 MiiTel MCP Server
LlamaIndex provides unique advantages when paired with MiiTel through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine MiiTel tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain MiiTel tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query MiiTel, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what MiiTel tools were called, what data was returned, and how it influenced the final answer
MiiTel + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the MiiTel MCP Server delivers measurable value.
Hybrid search: combine MiiTel real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query MiiTel 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 MiiTel for fresh data
Analytical workflows: chain MiiTel queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for MiiTel in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with MiiTel immediately.
"Show speech analytics for Mike's latest sales call."
"Get the transcript summary for call call_890."
"Show today's call volume and team performance."
Troubleshooting MiiTel MCP Server with LlamaIndex
Common issues when connecting MiiTel to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpMiiTel + LlamaIndex FAQ
Common questions about integrating MiiTel MCP Server with LlamaIndex.