How to Use the Zeplo (Queue & Background Job API) MCP in LangChain

Q: Can I use Zeplo (Queue & Background Job API) for complex task management in LangChain?

Yep. You can set up recurring jobs using createschedule and manage them over time. This lets your agent orchestrate multi-day workflows that aren't instant.

Q: Is it easy to monitor job history using Zeplo (Queue & Background Job API) in LangChain?

It's straightforward. You use listqueuelogs to get paginated request history for any given queue, letting your agent debug why a process failed.

Q: Does MCP Server support multiple job types with Zeplo (Queue & Background Job API) and LangChain?

Absolutely. You can manage both one-time queued requests (enqueuerequest) and recurring schedules, giving you two primary mechanisms for background work.

Build multi-step workflows with LangChain using Zeplo (Queue & Background Job API).

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Connect Zeplo (Queue & Background Job API) MCP to LangChain

Create your Vinkius account to connect Zeplo (Queue & Background Job API) 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 Zeplo (Queue & Background Job API) with LangChain

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Perplexity

Schedule Complex Tasks via MCP Server

You can't wait for a job to finish before your agent moves on. Use `create_schedule` and `list_schedules` to set up background tasks that run at specific times, like cron jobs. This lets you build multi-step reasoning pipelines where the final step is triggering an external event later. The output of one tool call can kick off a delayed process managed by Zeplo.

Track and Manage Jobs in LangChain

Need to see if that background job actually ran? You can check the status using `get_request` or get a full history with `list_queue_logs`. This gives your agent full observability over queue activity. Furthermore, you manage the queues themselves. Use `update_queue` to adjust settings or even pause and resume jobs via `update_schedule`, giving granular control right in your LangChain chain.

Control Worker Tokens with LangChain

When your agent needs to talk to the Zeplo API, it needs a token. Use `create_token` to generate one for the workspace, and then use `list_tokens` to keep track of them. It's crucial that your multi-server aggregation handles auth correctly. The unique token value is only returned once, so make sure LangChain captures it immediately when setting up a chain.

Setup guide

Set up Zeplo (Queue & Background Job API) 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 Zeplo (Queue & Background Job API) 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({
    "zeplo-queue-background-job-api-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 Zeplo (Queue & Background Job API) transactions"
    })
    print(result["messages"][-1].content)

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Common questions about Zeplo (Queue & Background Job API) MCP in LangChain

You call the MCP tool to interact directly. Your agent decides if it needs to enqueue a job, create a schedule, or cancel an existing request before continuing its reasoning.

Yep. You can set up recurring jobs using `create_schedule` and manage them over time. This lets your agent orchestrate multi-day workflows that aren't instant.

It primarily handles authentication tokens and structured job payloads for HTTP requests. The core data type managed is the workspace token value, which is sensitive.

It's straightforward. You use `list_queue_logs` to get paginated request history for any given queue, letting your agent debug why a process failed.

Absolutely. You can manage both one-time queued requests (`enqueue_request`) and recurring schedules, giving you two primary mechanisms for background work.

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