How do I securely obtain ConnectAndSell API credentials?

You typically need to contact your organization's ConnectAndSell technical administrator or reach out directly to the official support channel to provision API access. Once authorized, secure the credentials supplied and enter them safely in this integration's configuration context below.

Can the AI place active phone calls on behalf of the sales reps?

No. This integration operates primarily in a reporting, querying, and monitoring capacity. It manages system metrics to retrieve data on usage, calling statistics, performance overviews and campaign metrics, rather than taking direct voice or real-time call control roles which structurally belong strictly within the dialer platform interface natively.

What exact statistics can be reviewed with this AI integration?

You can effectively retrieve summary counts of dials made, connection and conversion ratios, active campaign performance statuses, agent-level tallies of successful meetings set, and various log insights correlating duration of talk to explicit disposition outcomes recorded internally.

ConnectAndSell MCP Server for LlamaIndex 6 tools — connect in under 2 minutes

Name: ConnectAndSell
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 6 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add ConnectAndSell 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 ConnectAndSell. "
            "You have 6 tools available."
        ),
    )

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

asyncio.run(main())

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About ConnectAndSell MCP Server

Connect your conversational agent to the established ConnectAndSell platform. Efficiently monitor calling activities, track campaign success rates, and manage high-volume B2B cold calling campaigns effortlessly via text.

LlamaIndex agents combine ConnectAndSell 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

Track Campaigns — Immediately instruct your agent to check live metrics for active dialing campaigns and list out agent statuses.
Review Activities — Audit logs for specific sales reps to review connection rates, talk time, and disposition outcomes.
Extract Insights — Identify which outreach lists are yielding the highest conversation ratios to optimize your CRM workflows.

The ConnectAndSell 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.

How to Connect ConnectAndSell to LlamaIndex via MCP

Follow these steps to integrate the ConnectAndSell 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 6 tools from ConnectAndSell

Why Use LlamaIndex with the ConnectAndSell MCP Server

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

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

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

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

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

ConnectAndSell + LlamaIndex Use Cases

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

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

Data enrichment: query ConnectAndSell 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 ConnectAndSell for fresh data

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

ConnectAndSell MCP Tools for LlamaIndex (6)

These 6 tools become available when you connect ConnectAndSell to LlamaIndex via MCP:

get_performance_summary

Supports optional date range filtering. Retrieve a summary of sales calling performance metrics

list_assigned_lists

Returns the prospect lists assigned for outbound calling sessions. Retrieve the calling lists assigned to a specific user

list_call_attempts

Supports date filtering. Retrieve history of all outbound call attempts

list_cas_users

Retrieve all users in the ConnectAndSell account

list_conversations

Supports date filtering in YYYY-MM-DD format. Retrieve history of successful connections and conversations

sync_to_crm

g. Salesforce, HubSpot). Requires the call ID and CRM type. Manually trigger a sync of call data to your connected CRM

Example Prompts for ConnectAndSell in LlamaIndex

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

"Can you check the current statistics for our 'Q3 Outreach' ConnectAndSell dialer campaign?"

"Which SDR had the highest talk time ratio across outbound operations yesterday?"

"How many total connections were established today among all sales reps?"

Troubleshooting ConnectAndSell MCP Server with LlamaIndex

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

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

ConnectAndSell + LlamaIndex FAQ

Common questions about integrating ConnectAndSell 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 ConnectAndSell tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.