How to Use the Mode Analytics MCP in Pydantic AI

Q: Does Pydantic AI work with large Mode Analytics reports?

It does. You can fetch specific report runs using getmodereportrun to keep memory usage low while processing the validated result.

Validate every Mode Analytics data point with Pydantic AI for type-safe, error-free agent execution.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Mode Analytics MCP to Pydantic AI

Create your Vinkius account to connect Mode Analytics to Pydantic AI 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 Mode Analytics with Pydantic AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Type-safe interaction with Pydantic AI

Your agent uses `list_mode_definitions` to pull calculated fields into your type-safe model. If the schema shifts, the agent catches it immediately. Avoid silent failures by using `get_mode_report` to verify the structure of your reports. Every response is validated against your Pydantic definitions at runtime.

Execute and validate Mode Analytics runs

Trigger data refreshes with `run_mode_report`. The tool returns a predictable payload that your agent parses into strict Python objects. Use `get_mode_report_run` to check the execution status. If the API returns unexpected data, your agent raises a clear validation error.

Query management via Pydantic AI

Access SQL definitions using `list_mode_queries`. Your agent inspects the code to ensure it aligns with your internal data quality standards. List all report runs with `list_mode_report_runs`. This provides a complete audit trail that your agent can process for performance tracking.

Setup guide

Set up Mode Analytics MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "mode-analytics-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Mode Analytics tools.",
)

result = await agent.run("List recent Mode Analytics transactions")
print(result.output)

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 Mode Analytics. 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 Mode Analytics 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 Mode Analytics MCP in Pydantic AI

Every tool output is mapped to a Pydantic model. If the response from `list_mode_reports` doesn't match the expected schema, the agent fails immediately.

Yes. Since the agent gets the raw error message from the tool, you can model that error and have the agent explain the failure.

The server manages your credentials securely outside of the agent logic. Only the required, validated data points are passed back to your Pydantic models.

It does. You can fetch specific report runs using `get_mode_report_run` to keep memory usage low while processing the validated result.

We enforce type constraints on all incoming data. Only the specific fields you define in your Pydantic models are ever processed by the agent.

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