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How to Use the Chili Piper MCP in LlamaIndex

Index your Chili Piper routing queues and meeting analytics directly into LlamaIndex for semantic search.

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LlamaIndex

Connect Chili Piper MCP to LlamaIndex

Create your Vinkius account to connect Chili Piper to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Querying historical meeting analytics

Sales ops teams waste hours digging through dashboards. You can wire this MCP Server into LlamaIndex and pull physical white-space statistics using `get_availability`. The framework indexes this output into your vector store. You just ask your agent why the SDR team missed quota, and it queries the grounded API data instead of guessing.

LlamaIndex MCP Server router mapping

Concierge rules get complicated fast. Your agent calls `list_routes` and `get_route_details` to ingest the exact properties driving your active router mapping. That structural extraction becomes part of your searchable RAG application. A new sales manager can ask the agent how enterprise leads are routed, and it answers based on live configuration data.

Auditing queues and member accounts

You need to know exactly who sits in which distribution bucket. The agent pulls native Round-Robin grouping via `list_queues` and explicit cloud logging through `list_members`. It cross-references this against your CRM documents. If a rep leaves the company, your RAG setup can instantly identify which active scheduling lists still include them by checking `list_meetings`.

Setup guide

Set up Chili Piper MCP in LlamaIndex

Prerequisites

  • Python 3.10+ installed
  • llama-index-tools-mcp package
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install dependencies

    Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.

  2. 2

    Connect with BasicMCPClient

    Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.

  3. 3

    Convert to LlamaIndex tools

    Call mcp_tool_spec.to_tool_list_async() to convert all Chili Piper MCP tools into native FunctionTool objects that any LlamaIndex agent can use.

  4. 4

    Run with any LLM

    Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Chili Piper tools.",
)
response = await agent.run("List recent Chili Piper data")

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Chili Piper. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Chili Piper MCP in LlamaIndex

Install llama-index-tools-mcp. Connect BasicMCPClient to your endpoint, wrap it in McpToolSpec, and pass the async tool list to your FunctionAgent.
Yes. It runs get_meeting_details to fetch the structural matching payloads. The framework indexes those records so you can run semantic queries on past sales calls.
You can use the allowed_tools filter to restrict what the agent touches. Turn on include_resources=True to let it ingest raw scheduling logs.
Your agent executes cancel_meeting when a user requests it. It then updates the vector store to reflect the newly freed scheduling blocks.
Vinkius runs a zero-trust architecture. When your agent indexes concierge routes and weight distributions, the transaction happens in an ephemeral sandbox that vaporizes the moment the data transfers.

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