How to Use the MakePlans MCP in LangChain

Chain MakePlans tool calls directly into your LangChain agents for automated scheduling workflows.

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Connect MakePlans MCP to LangChain

Create your Vinkius account to connect MakePlans 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 MakePlans with LangChain

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Build automated booking chains with LangChain

Connect `find_available_slots` to `create_new_appointment` within your agentic pipelines. You define the logic flow where the output of your initial availability check dictates the parameters for the subsequent booking action. Your agents evaluate the tool responses in real-time to handle complex scheduling logic. Since every call is traceable in LangSmith, you see exactly how the agent navigated the `list_available_services` results before committing to a final time.

Manage customer data in your agent loops

Trigger `create_new_customer` automatically when your agent identifies a new lead. By chaining this with `list_customers`, you prevent duplicate profiles from bloating your internal records. Maintain state across your conversational threads by using the MCP client session. This ensures your agent remembers the context of previous `get_appointment_details` calls without needing manual input from the user.

Aggregate multi-server booking systems

Combine the MakePlans MCP server with other data sources using the MultiServerMCPClient. Your agents decide which tool to pull from based on the task requirements. Process multiple `list_booking_resources` requests alongside external database queries to build a unified view of your operations. This framework allows for granular control over how your agent interacts with the booking API.

Setup guide

Set up MakePlans 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 MakePlans 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({
    "makeplans-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 MakePlans 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 MakePlans. 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 MakePlans MCP in LangChain

Install the necessary adapters and pass the server tools into your agent constructor. Your agent will then use the tools to query availability and process bookings based on the logic you set in your chain.

Yes. You can build ReAct agents that perform multi-step reasoning, calling different tools in sequence to ensure all booking constraints are met before finalizing an appointment.

Use LangSmith tracing to inspect the inputs and outputs of every tool call. This allows you to see exactly where the agent might be failing to interpret the API response.

The server remains stateless, but you can manage persistent state within your client sessions. Use the client session to track ongoing conversations and booking contexts.

Vinkius handles authentication with a single endpoint token. Your customer contact details are transmitted over encrypted channels directly to the API, ensuring no sensitive data is stored in the agent's memory.

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