How to Use the ConnectAndSell MCP in LangChain

Q: Can I run parallel calling list checks with this setup?

Your LangChain agent can call listassignedlists across multiple users simultaneously using parallel tool execution. The framework aggregates the active lists before running its next analytical step.

Run multi-step outbound sales analysis chains in LangChain using direct data from your ConnectAndSell dialer.

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Connect ConnectAndSell MCP to LangChain

Create your Vinkius account to connect ConnectAndSell to LangChain 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 ConnectAndSell with LangChain

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Chain ConnectAndSell Metrics into LangChain Pipelines

The `get_performance_summary` tool fetches raw outbound dialer metrics directly into your LangChain runnables. Your agent uses this data to decide whether to fetch the active calling lists via `list_assigned_lists` or pull user performance stats. By feeding these outputs sequentially through your chain, the agent builds a complete picture of rep activity. LangSmith traces every step of this ConnectAndSell analysis so you see exactly how the agent evaluates your dialing performance.

Run Multi-Step Call History Audits with LangChain

The `list_call_attempts` tool retrieves every outbound dial attempt so your LangChain agent can analyze reach rates. The agent takes these raw logs and feeds them into subsequent chain steps to isolate cold list performance. You get a transparent reasoning path where the agent cross-references attempt frequencies with active lists. This workflow uses the MCP Server to let your chain dynamically adjust its queries based on call volume metrics.

Automated CRM Syncing Inside Your LangChain Agents

The `sync_to_crm` tool pushes specific call outcomes directly to your CRM when your LangChain agent detects a successful conversation. The agent checks `list_conversations` first to find positive connections before triggering the sync. Running this as a unified chain means your agent handles the lookup and the CRM update in a single pass. You bypass manual data entry entirely because the LangChain framework drives the ConnectAndSell API calls based on live conversation records.

Setup guide

Set up ConnectAndSell MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes ConnectAndSell tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "connectandsell-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent ConnectAndSell transactions"
    })
    print(result["messages"][-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by ConnectAndSell. 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 ConnectAndSell MCP in LangChain

Use the MultiServerMCPClient from your adapter package to point to the Vinkius MCP endpoint. Pass the retrieved tools to your agent creator, allowing your LangChain chain to call tools like `list_cas_users` instantly.

Yes, the LangChain agent passes date arguments directly to tools like `list_conversations` and `list_call_attempts`. The agent parses the YYYY-MM-DD format to filter calling history during its chain execution.

LangSmith traces the exact inputs and outputs of tools like `get_performance_summary` during your run. You see the latency, raw dialer metrics, and how your LangChain agent uses that data in the next step.

Your LangChain agent can call `list_assigned_lists` across multiple users simultaneously using parallel tool execution. The framework aggregates the active lists before running its next analytical step.

Vinkius runs the MCP Server in an isolated V8 sandbox, ensuring your sales call logs and CRM tokens remain private. No call histories or user lists are stored on the host between your LangChain runs.

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