How do I identify a person in Kissmetrics?

You can use an email address or any unique string as the identity (`person` parameter) in the tracking tools. Use the `alias_identities` tool to link multiple IDs to the same person.

Can I query report data through this agent?

Yes, you can use the `query_metric_data` or `query_people_count` tools to retrieve aggregated values and counts based on your collected behavioral data.

Is it possible to see all my custom events?

Absolutely. Use the `list_event_types` tool to retrieve a comprehensive list of all events that have been defined or recorded in your account.

Kissmetrics MCP Server for Pydantic AI 7 tools — connect in under 2 minutes

Name: Kissmetrics
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 7 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Kissmetrics 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 Kissmetrics "
            "(7 tools)."
        ),
    )

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

asyncio.run(main())

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<40msKill switch

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 Kissmetrics MCP Server

Connect your Kissmetrics account to any AI agent to automate your user behavioral analytics and tracking workflows. This MCP server enables your agent to record events, manage user properties, and query complex metric data directly from natural language interfaces.

Pydantic AI validates every Kissmetrics tool response against typed schemas, catching data inconsistencies at build time. Connect 7 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

Behavior Tracking — Record custom events for specific users to monitor their journey and interactions
Profile Management — Set and update user properties and metadata to maintain rich customer profiles
Identity Resolution — Alias multiple identities to maintain a single, unified view of a user across sessions
Data Discovery — List all defined event types and property names currently in your account
Analytical Querying — Retrieve people counts and metric values over time to track business performance

The Kissmetrics MCP Server exposes 7 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 Kissmetrics to Pydantic AI via MCP

Follow these steps to integrate the Kissmetrics 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 7 tools from Kissmetrics with type-safe schemas

Why Use Pydantic AI with the Kissmetrics MCP Server

Pydantic AI provides unique advantages when paired with Kissmetrics 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 Kissmetrics integration code

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

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

Kissmetrics + Pydantic AI Use Cases

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

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

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

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

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

Kissmetrics MCP Tools for Pydantic AI (7)

These 7 tools become available when you connect Kissmetrics to Pydantic AI via MCP:

alias_identities

g., linking a browser ID to an email). Link two identities together

list_event_types

List all event types defined in the account

list_property_names

List all property names used in the account

query_metric_data

Requires a metric ID and query parameters. Get data for a specific metric

query_people_count

Get the count of people matching specific criteria

record_event

Requires a person identity (email/ID) and an event name. Record a behavior event for a person

set_person_properties

Set properties for a specific person

Example Prompts for Kissmetrics in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Kissmetrics immediately.

"Record a 'Purchased' event for 'user@example.com' with price 49.99."

"Set the property 'Plan Tier' to 'Enterprise' for 'customer_123'."

"Show me all event types defined in my account."

Troubleshooting Kissmetrics MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Kissmetrics + Pydantic AI FAQ

Common questions about integrating Kissmetrics 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 Kissmetrics MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.