Can my AI automatically add a new lead to BatchDialer?

Yes! Use the `add_lead` action with the contact's name and phone number. Your agent will register the lead in your BatchDialer system instantly.

How do I easily list all recent call logs?

Simply ask the agent to `list_call_logs`. It will compile the history of recent outbound activities, including status and duration.

Does the integration allow starting an active call from the agent?

No. For security and operational safety, the current toolset focuses on management and auditing (listing campaigns, managing leads, checking logs). Initiating live calls must be done through the BatchDialer interface.

BatchDialer MCP Server for LlamaIndex 10 tools — connect in under 2 minutes

Name: BatchDialer
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add BatchDialer as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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 BatchDialer. "
            "You have 10 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in BatchDialer?"
    )
    print(response)

asyncio.run(main())

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* 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 BatchDialer MCP Server

Connect your BatchDialer account to any AI agent and take full control of your sales and outbound calling operations through natural conversation.

LlamaIndex agents combine BatchDialer 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

Campaign Management — List and inspect all dialing campaigns to monitor active sales operations.
Lead & Contact Control — Add, query, and manage your contacts (leads) to ensure your dialing lists are always up to date.
Call Log Analysis — Retrieve complete call histories, including durations and outcomes (dispositions).
Phone Number Management — Monitor your caller IDs and managed phone numbers directly from the agent.
Outcome Tracking — List and understand call dispositions to categorize lead interactions accurately.

The BatchDialer 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 BatchDialer to LlamaIndex via MCP

Follow these steps to integrate the BatchDialer 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 BatchDialer

Why Use LlamaIndex with the BatchDialer MCP Server

LlamaIndex provides unique advantages when paired with BatchDialer through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine BatchDialer tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain BatchDialer tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query BatchDialer, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what BatchDialer tools were called, what data was returned, and how it influenced the final answer

BatchDialer + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the BatchDialer MCP Server delivers measurable value.

Hybrid search: combine BatchDialer real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query BatchDialer 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 BatchDialer for fresh data

Analytical workflows: chain BatchDialer queries with LlamaIndex's data connectors to build multi-source analytical reports

BatchDialer MCP Tools for LlamaIndex (10)

These 10 tools become available when you connect BatchDialer to LlamaIndex via MCP:

add_lead

Add a new lead/contact

get_call_details

Get details of a specific call

get_campaign

Get specific campaign details

get_lead

Get specific lead details

get_user_profile

Get authenticated user profile

list_call_logs

List call logs/history

list_campaigns

List all BatchDialer campaigns

list_dispositions

List call outcomes/dispositions

list_leads

List contacts/leads

list_phone_numbers

List managed phone numbers

Example Prompts for BatchDialer in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with BatchDialer immediately.

"List all our active dialing campaigns on BatchDialer."

"Add a new lead: John Doe, phone 555-0199, email john@example.com."

"Show the recent call logs from today."

Troubleshooting BatchDialer MCP Server with LlamaIndex

Common issues when connecting BatchDialer to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

BatchDialer + LlamaIndex FAQ

Common questions about integrating BatchDialer MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query BatchDialer tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.