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 Pydantic AI 10 tools — connect in under 2 minutes

Name: Mode Analytics
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Mode Analytics through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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 pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Mode Analytics "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Mode Analytics?"
    )
    print(result.data)

asyncio.run(main())

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* 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.

Pydantic AI validates every Mode Analytics tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

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 Pydantic AI 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 Pydantic AI via MCP

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

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from Mode Analytics with type-safe schemas

Why Use Pydantic AI with the Mode Analytics MCP Server

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

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Mode Analytics integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Mode Analytics connection logic from agent behavior for testable, maintainable code

Mode Analytics + Pydantic AI Use Cases

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

Type-safe data pipelines: query Mode Analytics with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Mode Analytics tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Mode Analytics and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Mode Analytics responses and write comprehensive agent tests

Mode Analytics MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Mode Analytics to Pydantic AI 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 Pydantic AI

Ready-to-use prompts you can give your Pydantic AI 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 Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Mode Analytics + Pydantic AI FAQ

Common questions about integrating Mode Analytics MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Mode Analytics MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.