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How to Use the Laravel Forge MCP in LangChain

Run multi-step LangChain pipelines to deploy code and query Laravel Forge server states directly from your agent.

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LangChain

Connect Laravel Forge MCP to LangChain

Create your Vinkius account to connect Laravel Forge 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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Chain deployments with real-time LangChain telemetry

The `deploy_site` tool triggers a deployment script queue to run on a specific repository site. When you wire this into a LangChain run, your agent kicks off a build and immediately checks the progress in subsequent chain steps. Using LangSmith, you trace the exact latency of the deployment call and inspect the API payload. This setup prevents silent failures because each tool execution is recorded as a trace link.

Inspect server environments in LangChain agent loops

The `list_servers` tool returns the master list of all connected Forge servers in your account. Your agent uses this output to decide which droplet to query next in the execution path. By feeding this server list into a second step using `get_server`, the chain automatically gathers droplet configurations. No manual scripting is required to pass server IDs between API calls.

Manage database states through LangChain MCP Server

The `list_databases` tool lists active databases mounted on a specific Forge server. Your agent inspects this list to verify database names before running migrations or setting up new environments. Integrating this MCP Server with LangChain lets you combine database checks with other tools in your pipeline. You easily construct a chain that checks database existence before executing code updates.

Setup guide

Set up Laravel Forge MCP in LangChain

Prerequisites

  • Python 3.10+ installed
  • langchain-mcp-adapters + langgraph packages
  • Active Vinkius subscription with a valid endpoint token
  1. 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. 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. 3

    Create a ReAct agent

    Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Laravel Forge tool calls through the MCP protocol.

  4. 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({
    "laravel-forge-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 Laravel Forge transactions"
    })
    print(result["messages"][-1].content)

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Laravel Forge. 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 Laravel Forge MCP in LangChain

You use the MultiServerMCPClient from the langchain-mcp-adapters package to aggregate multiple MCP Server endpoints. This allows your LangChain agent to query Laravel Forge alongside other development tools in a single session.
Yes, every time LangChain invokes a tool like `deploy_site`, the input parameters and response payloads are logged as a node in your trace. You monitor execution speed and pinpoint issues when deployments fail.
You call client.get_tools() on your MCP adapter and pass the resulting tool list directly to create_agent. The agent then dynamically decides whether to list servers, check sites, or run deployments based on your prompt.
The error is returned directly to the agent as a tool output, allowing the chain to handle the failure. Your agent then reads the error message and executes a fallback tool, like checking server logs.
The server processes your API token inside a secure V8 Isolate Sandbox on Vinkius, meaning your credentials and server metadata never persist. Only the raw JSON responses, such as database lists and site configurations, are exposed to your local agent.

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