How to Use the Contractor+ MCP in LangChain

Q: Can LangChain agents handle Contractor+ estimate creation?

Yes, you map the agent output to the createestimate tool. The agent generates the data and the server commits it to your account.

Q: Does Contractor+ work with LangChain for invoice tracking?

You can pull listinvoices into your agent at any time. It lets your agent summarize billing status within your specific workflow.

Chain Contractor+ tools directly into your LangChain pipelines to automate estimates and client management.

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Connect Contractor+ MCP to LangChain

Create your Vinkius account to connect Contractor+ 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 Contractor+ with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Build reasoning chains for Contractor+ jobs

Connect `list_jobs` and `list_estimates` directly into your agent flow. Your chain takes the output from one tool and feeds it into the next without you intervening. LangChain handles the state, so the agent knows exactly which job it's looking at. You get full visibility in LangSmith whenever the agent triggers a tool.

Automate client intake with LangChain

Use `create_client` to push lead data straight from your pipeline. It turns raw input into a structured record in your database instantly. This keeps your agent loop moving. The agent decides when to create a lead based on the criteria you define in the chain.

Refine service requests in LangChain

Pass `list_service_requests` to your agent to filter incoming tasks. It sorts the queue based on the logic you wire up in the graph. Once it identifies a priority request, the agent follows up. You control the logic while the MCP server handles the dirty work.

Setup guide

Set up Contractor+ 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 Contractor+ 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({
    "contractor-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 Contractor+ 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 Contractor+. 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.

Why Choose Vinkius

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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

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Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Contractor+ MCP in LangChain

Install the adapters and define your client instance. You pass the tools directly into the agent constructor to start building your logic chains.

Yes, you map the agent output to the `create_estimate` tool. The agent generates the data and the server commits it to your account.

You can pull `list_invoices` into your agent at any time. It lets your agent summarize billing status within your specific workflow.

The client aggregates tools from different sources. You just point it to the endpoint and your agent treats them as a single pool.

Only the specific invoice data requested by your agent is processed. We keep your credentials isolated and ephemeral during the session.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript

Mastra AI sdk-typescript

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