How to Use the ConnectWise MCP in LangChain

Q: How do I connect ConnectWise to LangChain?

Install the adapter package using pip install langchain-mcp-adapters langgraph to get started. Next, initialize the MultiServerMCPClient pointing to your Vinkius endpoint and pass the retrieved tools to your agent.

Q: Can a LangChain agent search ConnectWise tickets by keyword?

Yes, the agent calls searchticketsbysummary to scan your existing queue for specific terms. It then uses the output to decide if it should update an existing issue or create a new one.

Q: Can I use other tools alongside the ConnectWise MCP Server in LangChain?

Yes, you can. The MultiServerMCPClient aggregates tools from several sources, allowing your agent to query a local database and update ConnectWise in one chain.

Run complex, multi-step support workflows in LangChain using your live ConnectWise data.

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Connect ConnectWise MCP to LangChain

Create your Vinkius account to connect ConnectWise 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 ConnectWise with LangChain

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Claude

Perplexity

Build multi-step support chains in LangChain

The `list_service_tickets` tool lets your agent fetch active issues directly from your PSA. Once the agent gets this list, it feeds the ticket IDs to `get_ticket` to inspect specific priorities and notes without you writing glue code. LangSmith traces every step of this execution so you see the latency and exact token usage. This visibility ensures your support agent makes reliable decisions when transitioning from gathering data to updating records.

Discover contacts and companies dynamically

Your agent uses `list_companies` to find the correct company identifier before touching any ticket data. If the matching company isn't obvious, the agent triggers `list_contacts` to cross-reference external email addresses. This multi-turn discovery process runs inside a single LangGraph run. You get clean, verified company profiles instead of guessing database IDs or hardcoding mappings.

Automated ticket creation with guardrails

The `create_ticket` tool allows your agent to open new service issues based on raw customer emails or chat transcripts. It queries `list_members` first to find an available internal staff member to assign. By combining these steps in a ReAct loop, the agent verifies the target company exists via `get_company` before creating anything. You avoid duplicate tickets and empty assignments completely.

Setup guide

Set up ConnectWise 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 ConnectWise 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({
    "connectwise-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 ConnectWise 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 ConnectWise Manage. 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 ConnectWise MCP in LangChain

Install the adapter package using `pip install langchain-mcp-adapters langgraph` to get started. Next, initialize the `MultiServerMCPClient` pointing to your Vinkius endpoint and pass the retrieved tools to your agent.

Yes, the agent calls `search_tickets_by_summary` to scan your existing queue for specific terms. It then uses the output to decide if it should update an existing issue or create a new one.

Every tool call is tracked natively through LangSmith when you integrate this MCP Server. You monitor the exact payloads sent to tools like `list_sales_activities` in real time.

Yes, you can. The `MultiServerMCPClient` aggregates tools from several sources, allowing your agent to query a local database and update ConnectWise in one chain.

Your ticket details, company records, and contact lists remain private. Vinkius runs the server in an isolated sandbox, meaning your PSA credentials and data payloads are never stored or used for training.

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