How to Use the LeadSquared MCP in LangChain

Q: How do I search for leads in LeadSquared using LangChain?

Use the searchleads tool within your agent definition. It allows your chain to query the CRM for specific prospects based on your criteria. You'll get the lead data back as a JSON object ready for further processing.

Q: Can LangChain update LeadSquared records automatically?

Yes, you can use the createorupdatelead tool. It takes your input data and checks for existing entries using email or phone numbers. If a match is found, it updates the record; otherwise, it creates a new one.

Q: How do I list activities for a LeadSquared user in LangChain?

Call listleadactivities by passing the unique lead identifier. Your chain will then receive the full activity history. This allows the model to analyze past interactions before drafting a response.

Chain together LeadSquared actions within your LangChain pipelines to automate lead qualification and sales tracking.

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Connect LeadSquared MCP to LangChain

Create your Vinkius account to connect LeadSquared 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 LeadSquared with LangChain

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Automate lead ingestion in LangChain

Pipe incoming data directly into your CRM using `capture_lead`. This ensures that every touchpoint from your agents is recorded without manual intervention. Your chains handle the heavy lifting by mapping incoming fields to `create_or_update_lead`. It keeps your database clean by matching records via email or phone.

Track sales activities with MCP Server

Monitor every interaction by chaining `list_lead_activities` into your reasoning loop. You see exactly what happened with a prospect before making your next move. Use `create_prospect_activity` to log calls or meetings as they happen. It keeps your CRM history current without you needing to switch tabs.

Manage opportunities in LangChain

Feed `list_opportunities` into your agent to prioritize accounts based on current CRM data. You get a clear view of your pipeline performance in real-time. Execute `create_opportunity` when your agent flags a lead as qualified. It connects your automated prospecting directly to your sales pipeline.

Setup guide

Set up LeadSquared 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 LeadSquared 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({
    "leadsquared-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 LeadSquared transactions"
    })
    print(result["messages"][-1].content)

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Common questions about LeadSquared MCP in LangChain

Use the `search_leads` tool within your agent definition. It allows your chain to query the CRM for specific prospects based on your criteria. You'll get the lead data back as a JSON object ready for further processing.

Yes, you can use the `create_or_update_lead` tool. It takes your input data and checks for existing entries using email or phone numbers. If a match is found, it updates the record; otherwise, it creates a new one.

Call `list_lead_activities` by passing the unique lead identifier. Your chain will then receive the full activity history. This allows the model to analyze past interactions before drafting a response.

Absolutely. You can initialize the server using the standard HTTP transport and register the tools directly with your agent. It integrates into your workflow just like any other toolset.

Data is transmitted directly between your local client and the API endpoint. We only touch lead contact information and activity logs during requested tool execution. Your credentials remain local to your environment.

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