Moneypenny MCP Server for LlamaIndexGive LlamaIndex instant access to 10 tools to Check Moneypenny Status, Get Activity Summary, Get Recent Chats, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Moneypenny 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 Moneypenny app connector for LlamaIndex is a standout in the Communication Messaging category — giving your AI agent 10 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 Moneypenny. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Moneypenny?"
)
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 Moneypenny MCP Server
Connect your Moneypenny account to any AI agent and review your business communications through natural conversation.
LlamaIndex agents combine Moneypenny 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.
What you can do
- Call Messages — Browse telephone answering messages by day, week, month, or custom date range.
- Live Chat Logs — Access live chat conversation transcripts with time-based filtering.
- Activity Summary — Get a combined overview of today's calls and chats in a single dashboard view.
- Time-Based Views — Instantly access today's, this week's, or this month's communications.
The Moneypenny 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.
All 10 Moneypenny tools available for LlamaIndex
When LlamaIndex connects to Moneypenny through Vinkius, your AI agent gets direct access to every tool listed below — spanning virtual-receptionist, live-chat, call-answering, 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.
Verify Moneypenny API connectivity
Get a summary of all calls and chats for today
Returns all new chat conversations. Get the most recent live chat conversations
Get all call messages from the current month
Get all call messages from the past 7 days
Get all live chat conversations from the past 7 days
Get all call messages from today
Get all live chat conversations from today
Format dates as MM/DD/YYYY. List telephone answering messages by date range
Optionally filter by start and end time (ISO 8601). List live chat conversation logs by date range
Connect Moneypenny to LlamaIndex via MCP
Follow these steps to wire Moneypenny 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 Moneypenny MCP Server
LlamaIndex provides unique advantages when paired with Moneypenny through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Moneypenny tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Moneypenny tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Moneypenny, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Moneypenny tools were called, what data was returned, and how it influenced the final answer
Moneypenny + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Moneypenny MCP Server delivers measurable value.
Hybrid search: combine Moneypenny real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Moneypenny 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 Moneypenny for fresh data
Analytical workflows: chain Moneypenny queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Moneypenny in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Moneypenny immediately.
"Show me today's call messages."
"Give me a summary of today's activity."
"Show me the live chat logs from this week."
Troubleshooting Moneypenny MCP Server with LlamaIndex
Common issues when connecting Moneypenny to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpMoneypenny + LlamaIndex FAQ
Common questions about integrating Moneypenny MCP Server with LlamaIndex.