How to Use the Mode (Collaborative Data Platform) MCP in LangChain

Q: How do I connect Mode (Collaborative Data Platform) to LangChain?

You install langchain-mcp-adapters and initialize the client with your Vinkius endpoint. From there, you call gettools() to pass the Mode tools directly to your agent executor.

Run multi-step analytical workflows across your Mode reports using LangChain agents to trace every single tool call.

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Connect Mode (Collaborative Data Platform) MCP to LangChain

Create your Vinkius account to connect Mode (Collaborative Data Platform) 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 Mode (Collaborative Data Platform) with LangChain

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Chain Mode reports directly into LangChain pipelines

The `list_reports` tool lets your agent pull active reports directly into a LangChain conversational chain. You get raw metadata from your workspace, allowing the model to decide which specific report token needs deeper inspection. Once the agent identifies the correct report, it feeds that token straight into `get_report` to analyze the underlying parameters. LangSmith traces the entire handoff, so you see exactly how one tool's output feeds the next.

Map internal workspaces and data connections

This MCP server exposes `list_spaces` and `list_data_sources` to help your agent map out your entire analytics environment. The agent crawls these endpoints to locate where specific datasets live and which database connectors feed them. Developers can build chains that verify database origins before running sensitive queries. If a source looks wrong, the agent stops the run and alerts a user in the LangSmith trace log.

Search and audit workspace members

Running `search_reports` via the MCP server allows your LangChain agent to find specific business metrics across thousands of saved queries. It matches keywords against live Mode API endpoints to find the exact report you need. By combining this with `list_members`, the agent can attribute report ownership and verify which analyst created a specific dashboard. This keeps your workspace clean without manual audits.

Setup guide

Set up Mode (Collaborative Data Platform) 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 Mode (Collaborative Data Platform) 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({
    "mode-collaborative-data-platform-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 Mode (Collaborative Data Platform) transactions"
    })
    print(result["messages"][-1].content)

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

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Common questions about Mode (Collaborative Data Platform) MCP in LangChain

You install `langchain-mcp-adapters` and initialize the client with your Vinkius endpoint. From there, you call `get_tools()` to pass the Mode tools directly to your agent executor.

Yes, if your Vinkius credentials have the right permissions. The agent uses `list_spaces` and `get_space` to crawl any collection your Mode API key can access.

You turn on LangSmith tracing. It automatically logs latency, parameters, and outputs for every call to `get_report` or `list_reports` triggered by your chain.

Your LangChain agent receives the list as a structured JSON array. You can configure the next link in your chain to filter these sources based on the report parameters you retrieved.

Vinkius handles authentication through a single secure endpoint token, so your LangChain code never exposes raw Mode API keys. Your analytical parameters and report tokens are processed in an ephemeral sandbox.

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