How to Use the Tray.io MCP in LangChain
Build multi-step automations with LangChain: Orchestrate complex actions using Tray.io's data.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Tray.io MCP to LangChain
Create your Vinkius account to connect Tray.io 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.
Discovering available workflows and integrations.
The `list_workflows` tool lets your agent see every automation running in the account. You can quickly check what automations exist before trying to modify them. The `list_integration_solutions` tool gives a rundown of all pre-built integration templates. This is useful for understanding which connection types are ready to go.
Monitoring data execution flows.
Need to know if a workflow actually ran? Use `list_workflow_executions` to pull recent history for any specific process. You get details on when it started and what the results were. The agent can also check the status of an entire operation using `get_workflow_details`. This lets your AI client track down exactly where a run got stuck.
Identifying connected services.
The `list_available_connectors` tool shows every service that can plug into Tray.io, like Salesforce or Slack. Your agent uses this to validate which systems are actually available for the job. Furthermore, `get_authenticated_user` retrieves details about the current user. This lets your agent know who's running the automation and what their permissions are.
Set up Tray.io MCP in LangChain
Prerequisites
- Python 3.10+ installed
-
langchain-mcp-adapters+langgraphpackages - 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 LangChainBaseToolobjects. - 2
Connect via HTTP transport
Use
MultiServerMCPClientwith"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 Tray.io tool calls through the MCP protocol. - 4
Run with any LLM
Swap
ChatOpenAIforChatAnthropic,ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.
from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI
async with MultiServerMCPClient({
"trayio-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 Tray.io 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 Tray.io. 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.
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 Tray.io MCP in LangChain
Use it with your favorite AI tools
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