How to Use the CommPeak MCP in LlamaIndex

Q: How do I build a RAG pipeline with CommPeak and LlamaIndex?

You use listleads to pull lead records and index them into a VectorStoreIndex. Your agent then queries this index to find target prospects before calling sendsms.

Q: Can LlamaIndex query dialer campaign performance via CommPeak?

Yes. Your agent runs listdialercampaigns and getcampaigndetails to retrieve active performance metrics, which it then indexes for natural language queries.

Q: Can I filter which tools the agent can access?

Yes, you can pass an allowedtools list during initialization. This limits your agent to safe actions like getsmsstatus while blocking destructive MCP tools.

Index CommPeak dialer metrics and lead profiles into your LlamaIndex vector store for context-rich sales workflows.

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Connect CommPeak MCP to LlamaIndex

Create your Vinkius account to connect CommPeak 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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Setup CommPeak with LlamaIndex

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Indexing dialer data into LlamaIndex

The `list_leads` tool pulls live contact records from your campaigns so your agent can index them for semantic search. The MCP server outputs these records as document nodes, letting your query engine find relevant leads based on past interactions. You use `get_campaign_details` to append real-time dialer statistics directly to your index context. This ensures your RAG agent knows which campaigns are active before suggesting sales strategies.

Context-aware texting with CommPeak MCP Server

The `send_sms` tool sends text messages that are grounded in your indexed knowledge base. Your LlamaIndex agent queries past lead interactions, drafts a personalized message, and transmits it via the API. Tracking those messages is done with `list_recent_sms` and `get_sms_status`. The tool outputs are instantly converted into index nodes, keeping your message history searchable and up to date.

Real-time lead profile lookups

The `get_lead_details` tool fetches complete contact histories to resolve user queries during active chat sessions. When a user asks about a prospect, LlamaIndex calls this tool to inject the lead's current status into the prompt context. Managing your database is simplified with `create_lead` and `delete_lead` to sync changes back to the dialer. Your agent modifies the index and calls these tools to keep the remote CommPeak lists updated.

Setup guide

Set up CommPeak MCP in LlamaIndex

Prerequisites

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

1

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

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all CommPeak MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
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 CommPeak tools.",
)
response = await agent.run("List recent CommPeak data")

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Common questions about CommPeak MCP in LlamaIndex

You use `list_leads` to pull lead records and index them into a VectorStoreIndex. Your agent then queries this index to find target prospects before calling `send_sms`.

Yes. Your agent runs `list_dialer_campaigns` and `get_campaign_details` to retrieve active performance metrics, which it then indexes for natural language queries.

You load the tools via the MCP tool spec and pass them to a FunctionAgent. The agent automatically selects tools like `get_lead_details` when users ask about specific prospects.

Yes, you can pass an allowed_tools list during initialization. This limits your agent to safe actions like `get_sms_status` while blocking destructive MCP tools.

Your lead contact details and API credentials are kept in memory within the Vinkius isolate. They are never cached on disk or exposed to external indexing services.

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