How to Use the Dokku MCP in LangChain

Q: Can LangChain debug my Dokku apps?

Yes, by using the getlogs tool. Your agent will read the stdout and stderr streams to find errors in real-time.

Manage your production Dokku instances directly from LangChain agents. Build automated deployment chains without leaving your flow.

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Connect Dokku MCP to LangChain

Create your Vinkius account to connect Dokku 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 Dokku with LangChain

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Full-stack Dokku control in LangChain

Integrate your server infrastructure into reasoning pipelines. Use `create_app` to provision new environments and `ps_scale` to adjust capacity based on agent-detected traffic patterns. Chain these operations to build self-healing infrastructure agents. When a service fails, the agent uses `get_logs` to diagnose the issue, then triggers `ps_restart` to recover automatically.

Configuration management via LangChain

Sync your application runtime inputs directly from your agent's decision logic. Use `set_config` to inject updated credentials and `list_config` to verify current settings across your fleet. This keeps your environment variables in lockstep with your deployment state. Any changes trigger immediate updates, ensuring your production runtime always matches your intended configuration.

Resource lifecycle automation

Clean up your infrastructure by automating app removal. Use `destroy_app` to decommission stale services once your agent confirms they are no longer needed. This keeps your host clean and prevents resource creep. You gain total visibility into what is running using `list_apps`, allowing for precise orchestration of your microservices.

Setup guide

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

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Common questions about Dokku MCP in LangChain

Install the necessary MCP adapters and initialize the client with your host URL. You can then pull the tool definitions into your agent's toolset.

Yes, by using the `get_logs` tool. Your agent will read the stdout and stderr streams to find errors in real-time.

The server uses a zero-trust architecture. Data stays local to your session and is only accessed when the agent executes a specific tool command.

You can aggregate multiple instances by defining separate MCP server endpoints. Your agent will route commands to the correct host based on the task.

Certainly. You can write a chain that monitors performance metrics and calls `ps_scale` to add or remove worker containers as needed.

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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