How do I find my API Token and Secret?

In Mode, click on your name in the top left, go to **My Account** > **API Tokens**. There you can create and manage your API keys.

What is the Workspace slug?

The Workspace slug is the unique identifier for your organization in the Mode URL (e.g., `app.mode.com/org_name`). The `org_name` part is your workspace slug.

Can I provide parameters when running a report?

Yes! The `run_mode_report` action accepts an optional `parameters` field where you can provide a JSON string of keys and values used by the report.

Mode Analytics MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: Mode Analytics
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Mode Analytics through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "mode-analytics": {
            "transport": "streamable_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,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Mode Analytics, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Mode Analytics MCP Server

Connect your Mode Analytics workspace to any AI agent and take full control of your data science and business intelligence workflows through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Mode Analytics through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

What you can do

Workspace Oversight — List all spaces and members to maintain visibility over your analytical environment.
Report Discovery — List and retrieve detailed metadata for reports across different spaces.
Live Execution — Trigger new report runs directly through the agent, including support for custom parameters.
Query Auditing — List the underlying SQL queries for any report to understand data lineage and logic.
Definition Tracking — List calculated field definitions to ensure consistency in your metrics.

The Mode Analytics MCP Server exposes 10 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Mode Analytics to LangChain via MCP

Follow these steps to integrate the Mode Analytics MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 10 tools from Mode Analytics via MCP

Why Use LangChain with the Mode Analytics MCP Server

LangChain provides unique advantages when paired with Mode Analytics through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Mode Analytics MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Mode Analytics queries for multi-turn workflows

Mode Analytics + LangChain Use Cases

Practical scenarios where LangChain combined with the Mode Analytics MCP Server delivers measurable value.

RAG with live data: combine Mode Analytics tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Mode Analytics, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Mode Analytics tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Mode Analytics tool call, measure latency, and optimize your agent's performance

Mode Analytics MCP Tools for LangChain (10)

These 10 tools become available when you connect Mode Analytics to LangChain via MCP:

get_mode_account

Get authenticated account details

get_mode_report

Get details for a specific report

get_mode_report_run

Get details for a report run

list_mode_definitions

List calculated field definitions

list_mode_members

List workspace members

list_mode_queries

List SQL queries in a report

list_mode_report_runs

List runs for a report

list_mode_reports

List reports in a space

list_mode_spaces

List Mode Analytics spaces

run_mode_report

Trigger a new run for a report

Example Prompts for Mode Analytics in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Mode Analytics immediately.

"List all reports in the 'Marketing Analytics' space."

"Run the report with token 'rep_12345' and check its latest status."

"Show me the SQL query used in the 'Churn Analysis' report."

Troubleshooting Mode Analytics MCP Server with LangChain

Common issues when connecting Mode Analytics to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Mode Analytics + LangChain FAQ

Common questions about integrating Mode Analytics MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.