How to Use the Zuplo MCP in LangChain

Q: Can I check multiple Zuplo environments with LangChain?

Yes. You can use listenvironments to see all defined contexts (like 'staging' or 'production'). Your agent logic handles selecting which environment is relevant for the deployment task.

Q: What data does Zuplo expose regarding API consumers for LangChain?

The listconsumers tool returns details about your API key consumers. This includes identifying who currently holds credentials and what resources they are linked to, helping you manage access control within your chain.

Q: What kind of deployments can Zuplo support with LangChain?

You can manage multiple deployment states using listdeployments and createdeployment. This allows your agent to validate the current infrastructure setup before executing any changes.

Q: Does Zuplo help track configuration data for LangChain?

Yes. You can use listfiles to review specific project configurations and settings, ensuring that the code or rules your agent is acting upon are correctly defined before execution.

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Setup Zuplo with LangChain

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Manage Zuplo projects across multiple environments.

You can build chains that check project status before making changes. Start by listing available infrastructure using `list_projects` to get a full view of your API landscape. Then, validate the correct deployment context with `list_environments`. This ensures your multi-step agent only targets 'production' or 'working' environments when calling other Zuplo tools.

Create and manage API key consumers programmatically.

The ReAct pattern works great for credential management. First, check who already has access by running `list_consumers`. If a new service needs credentials, the agent can then call `create_consumer` to provision it. If that consumer is retired or compromised, you'll know how to clean up fast with `delete_consumer`, all within one continuous workflow.

Monitor real-time performance metrics for Zuplo.

When an agent needs to decide if a deployment is healthy before proceeding, it can grab live data. Use `get_metrics` to pull edge metrics directly into the chain's memory. This output allows your multi-step reasoning to branch: if latency is high, the next step might be calling `list_deployments` rather than continuing with a critical operation.

Setup guide

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

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Common questions about Zuplo MCP in LangChain

Zuplo provides a sequence of actions that your agent can follow. For example, you'll first list projects and then use the resulting project ID to create an API consumer. The output of one tool call is immediately available as input for the next.

Yes. You can use `list_environments` to see all defined contexts (like 'staging' or 'production'). Your agent logic handles selecting which environment is relevant for the deployment task.

The `list_consumers` tool returns details about your API key consumers. This includes identifying who currently holds credentials and what resources they are linked to, helping you manage access control within your chain.

You can manage multiple deployment states using `list_deployments` and `create_deployment`. This allows your agent to validate the current infrastructure setup before executing any changes.

Yes. You can use `list_files` to review specific project configurations and settings, ensuring that the code or rules your agent is acting upon are correctly defined before execution.

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