How to Use the Dubsado MCP in LangChain

Q: Is it possible to list all Dubsado projects in my LangChain chain?

Certainly. You invoke listprojects to pull your current data into the agent's context window. This allows the agent to reason about existing client relationships.

Chain your Dubsado tasks directly into LangChain pipelines to automate project onboarding without writing custom glue code.

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Connect Dubsado MCP to LangChain

Create your Vinkius account to connect Dubsado 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 Dubsado with LangChain

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Claude

Perplexity

Automate project lifecycles in LangChain

Trigger `create_project` and `apply_workflow` as nodes within your agentic chains. You define the logic, and the agent executes the sequence based on your specific business requirements. This removes the manual overhead of moving a lead from a contact to an active project. The agent handles the handoff, ensuring every step happens in the correct order.

Dynamic invoice generation within chains

Pass data from your databases directly into `create_invoice` using LangChain's flexible input mapping. Your agent generates professional invoices the moment a project reaches the right stage. It eliminates the gap between contract signing and payment requests. You get a direct line from project approval to revenue collection without human intervention.

Observe your Dubsado operations

Track every tool call through LangSmith to see exactly how your agent handles project data. You see the input for `update_project` and the resulting status changes in real time. Debugging becomes a matter of checking the trace logs instead of guessing what went wrong. You maintain full control over the agent's decision-making process.

Setup guide

Set up Dubsado 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 Dubsado 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({
    "dubsado-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 Dubsado 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 Dubsado. 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 Dubsado MCP in LangChain

Yes. You connect the server to your LangChain agent and call `create_project` whenever your pipeline detects a new lead. It is a direct way to initialize your workspace.

You initialize the client via the MultiServerMCPClient and pass the tool definitions into your agent constructor. The agent then treats each operation as a native tool.

Your client interacts with the server through a secure endpoint token. The integration handles your project records and contract details within the scope you define.

Certainly. You invoke `list_projects` to pull your current data into the agent's context window. This allows the agent to reason about existing client relationships.

The server provides immediate access to your account data. You can run `update_project` or `get_invoice` whenever your agent needs to refresh its state.

Use it with your favorite AI tools

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

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