How to Use the Gainsight PX MCP in Pydantic AI

Q: How do I register the Gainsight PX server in Pydantic AI?

Use the MCPToolset constructor with your Vinkius HTTP endpoint URL. Pass this toolset directly into your Agent definition to make all 12 MCP tools available to your model.

Run type-safe product analytics operations in your Pydantic AI agent workflows.

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Connect Gainsight PX MCP to Pydantic AI

Create your Vinkius account to connect Gainsight PX 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.

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Setup Gainsight PX with Pydantic AI

Ask AI about this MCP

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Claude

Perplexity

Validate user profile syncs at runtime

`identify_px_user` updates user details with strict schema enforcement. Pydantic AI validates the incoming payload against your defined Python models before passing it to the server. If the API returns unexpected fields, the agent raises a validation error instead of corrupting your analytics. This strict typing ensures your Gainsight PX user database remains clean and structured.

Track events with structured type safety

`track_server_event` logs custom events using validated properties. Your agent uses this tool to register user milestones, guaranteeing that event names and attributes match your exact Pydantic schemas. This setup avoids the silent failures common in dynamically typed tracking setups. The MCP Server acts as a type-safe bridge between your Python backend and Gainsight PX.

Query products and active onboarding guides

`list_px_products` retrieves the list of active applications configured in your account. The agent parses this list to ensure it only tracks events against valid product IDs. To inspect the user experience, the agent calls `list_px_engagements` to fetch active surveys and guides. This MCP integration allows your agent to coordinate its responses with the active UI overlays on the client side.

Setup guide

Set up Gainsight PX 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": {
        "gainsight-px-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent Gainsight PX transactions")
print(result.output)

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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 Gainsight PX. 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 Gainsight PX MCP in Pydantic AI

Use the `MCPToolset` constructor with your Vinkius HTTP endpoint URL. Pass this toolset directly into your `Agent` definition to make all 12 MCP tools available to your model.

If a tool like the user details query returns data that deviates from your Pydantic models, the framework raises a validation error. This prevents your agent from making decisions based on malformed or incomplete user profiles.

Yes, your agent can call the connection verification tool during startup to check the API status. This returns a validated boolean status, allowing your Pydantic AI application to fail gracefully if the service is down.

The agent uses the user query tool to search for specific cohorts based on custom filters. The returned list is automatically parsed into type-safe Python objects for immediate use in your agent logic.

All event payloads transmitted via the tracking tool are processed inside isolated, ephemeral V8 sandboxes on Vinkius. Your keys are injected securely at the MCP Server level, keeping sensitive connection details out of your application logs.

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