How to Use the Zeev MCP in LangChain

Q: How does LangChain use Zeev to manage task delegation?

Your agent calls listtasks to identify pending items. It then uses the specific task ID with gettask and can execute delegatetask immediately, routing ownership to another user.

Q: Can I use LangChain to check Zeev process definitions?

Absolutely. You call listprocesses first to see all available workflows. Then you pass a definition ID into getprocess to pull out the full details necessary for your chain logic.

Q: When using Zeev with LangChain, how do I check if a process is still active?

You can query the status by calling listrequests. If you get a list of IDs, passing one to getrequest tells your agent exactly what stage the request is in.

Q: Does the LangChain agent need permissions to cancel requests in Zeev?

Yes. To use cancelrequest or createrequest, your agent needs appropriate endpoint tokens that grant it permission to modify running workflow instances within Zeev.

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Create your Vinkius account to connect Zeev 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 Zeev with LangChain

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Orchestrate Workflow Status Checks

You build agents that figure out the state of a process. First, your agent calls `list_processes` to find available workflows; then it uses `get_process` to map out exactly what steps are involved. The output is critical for chain logic. Once you have a workflow ID, you pass it to `list_requests`, and the next step can call `get_request` using those results to get specific instance details.

Manage Task Lifecycle

Agents need to handle task progression. You let your agent check pending work via `list_tasks`. If a task is ready, the agent can call `get_task` for specifics or use `delegate_task` if ownership needs changing. This chain allows for automated routing: Check status -> Delegate -> Wait -> Call `finish_task` when criteria are met.

Handle Process Modifications

Need to stop or restart a workflow? You use the MCP Server's tools within your LangChain agent logic. An initial step might be calling `get_request` to verify the ID, followed by using `cancel_request` if the process is obsolete. Alternatively, you can kick off new work immediately by having the agent execute `create_request`, starting a fresh cycle.

Setup guide

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

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Common questions about Zeev MCP in LangChain

Your agent calls `list_tasks` to identify pending items. It then uses the specific task ID with `get_task` and can execute `delegate_task` immediately, routing ownership to another user.

Absolutely. You call `list_processes` first to see all available workflows. Then you pass a definition ID into `get_process` to pull out the full details necessary for your chain logic.

You can query the status by calling `list_requests`. If you get a list of IDs, passing one to `get_request` tells your agent exactly what stage the request is in.

This server touches process definition details and specific task/request instances. It handles state management, including who owns a task and which workflows are available.

Yes. To use `cancel_request` or `create_request`, your agent needs appropriate endpoint tokens that grant it permission to modify running workflow instances within Zeev.

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