How to Use the Contentsquare MCP in Pydantic AI

Q: Can Pydantic AI run Contentsquare export jobs?

Yes, use createexportjob and getexportjob to manage your pipeline state. Pydantic AI confirms the job status matches your model requirements.

Integrate Contentsquare with Pydantic AI to enforce type-safe UX data validation and session enrichment for your agents.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Contentsquare MCP to Pydantic AI

Create your Vinkius account to connect Contentsquare 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 Contentsquare with Pydantic AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Validate Contentsquare exports in Pydantic AI

The `create_export_job` tool triggers your pipeline. Pydantic AI validates the response against your models, catching errors before they hit your logic. This prevents silent corruption when dealing with raw export chunks. You define the schema, and the tool ensures the incoming data matches.

Enrich sessions using Pydantic AI types

Bind your sales and contact logs using `enrich_session`. The agent checks the returned JSON payload against your defined Pydantic structures. It forces the agent to handle data correctly or fail immediately. This ensures your session arrays contain exactly what your application expects.

Audit URL mappings with Pydantic AI

List your routing trees via `list_mappings`. The server provides the path structure, and your agent validates the output against your expected URL formats. This keeps your domain tracking accurate. If the API returns unexpected fields, Pydantic AI catches it, maintaining the integrity of your agent's state.

Setup guide

Set up Contentsquare 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": {
        "contentsquare-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent Contentsquare 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 Contentsquare. 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 Contentsquare 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 Contentsquare MCP in Pydantic AI

Define your Pydantic models for the tool outputs. The framework automatically validates every JSON response from the server against those schemas.

Yes, use `create_export_job` and `get_export_job` to manage your pipeline state. Pydantic AI confirms the job status matches your model requirements.

They connect via SSE or Streamable HTTP. Your agent uses these transports to request data from the server while maintaining strict type safety.

Vinkius handles authentication through a secure, per-user endpoint token. Your agent processes data in a sandboxed environment, keeping your credentials out of the agent code.

The server processes demographic segments and session interaction logs. By using type-strict validation, you ensure that only authorized, correctly-formatted data enters your Pydantic AI pipelines.

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

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript