How to Use the UnifyApps MCP in LangChain

Q: How do I track flow history using UnifyApps and LangChain?

You simply call listflowexecutions. This tool immediately returns a list of recent runs, letting your agent know the exact timing and outcomes of past automation jobs.

Q: What details about my integrations can UnifyApps and LangChain provide?

The getintegrationdetails function pulls specific information on any single integration. This is key when your chain needs to verify parameters before executing a step.

Q: Can I list all configured AI agents with UnifyApps and LangChain?

Yes, the listaiagents tool provides an immediate inventory of every agent set up within your environment. Your agent uses this to decide which resource it needs to interact with next.

Q: Does UnifyApps and LangChain help audit connections?

Absolutely. The listactiveconnections tool lets you quickly see a list of all accounts that are currently connected and available for the chain to use.

Build Multi-Step Reasoning Pipelines with LangChain and UnifyApps MCP Server

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect UnifyApps MCP to LangChain

Create your Vinkius account to connect UnifyApps 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.

GDPR Free for Subscribers

Setup UnifyApps with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Track Automation Flows

You can call `list_automation_flows` to get a full list of every flow defined in the platform. This gives you a clear map of what's running and how the system is configured. The agent then uses `list_flow_executions` to check recent history for those flows. It tells you exactly when they ran, if they succeeded, or where they failed.

Audit Connections and Integrations

Need to know what's connected? Use `list_active_connections` to see all the accounts that are currently linked up. This tool is great for checking scope when building a complex chain. Don't forget about core services; `list_integrations` shows every single integration setup in UnifyApps. Your agent uses this data to verify inputs before continuing.

Manage AI Agents and Details

The system keeps track of its own intelligence, too. Calling `list_ai_agents` gives you a manifest of all the configured agents operating in your environment. This helps the chain decide which 'worker' to activate next. If you need granular info on any piece of equipment, `get_integration_details` pulls up specific details for one integration. It's essential context when designing multi-server chains.

Setup guide

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by UnifyApps. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect UnifyApps now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about UnifyApps MCP in LangChain

You simply call `list_flow_executions`. This tool immediately returns a list of recent runs, letting your agent know the exact timing and outcomes of past automation jobs.

The `get_integration_details` function pulls specific information on any single integration. This is key when your chain needs to verify parameters before executing a step.

Yes, the `list_ai_agents` tool provides an immediate inventory of every agent set up within your environment. Your agent uses this to decide which resource it needs to interact with next.

Absolutely. The `list_active_connections` tool lets you quickly see a list of all accounts that are currently connected and available for the chain to use.

This server interacts with connection metadata, specifically listing active account connections. You can track who is linked up using `list_active_connections`.

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