How to Use the MoEngage MCP in Pydantic AI

Q: How do I configure MoEngage for Pydantic AI?

Install the necessary packages and use MCPToolset with your server URL. Pass it to the agent to start executing validated calls.

Q: Can I update device info using MoEngage in Pydantic AI?

Use updatedevice. The tool schema ensures your device tokens and metadata are formatted correctly before the update is sent.

Type-safe MoEngage interactions for your Pydantic AI agents.

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Connect MoEngage MCP to Pydantic AI

Create your Vinkius account to connect MoEngage 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 MoEngage with Pydantic AI

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Perplexity

Strictly validated event tracking

Use `track_event` with full schema validation. Pydantic AI ensures every field in your event payload matches the API requirements before it leaves your agent. This prevents malformed data from hitting your growth engine. If the data structure is wrong, the agent stops before the call happens.

Reliable customer data access

Retrieve user details with `get_customer` and trust the return type. Pydantic models validate the response, so you know exactly what attributes you're working with. It eliminates silent errors. You'll never deal with unexpected nulls or missing fields in your agent logic.

Safe campaign execution

Control your messaging with `list_campaigns` and `send_push`. The framework validates your inputs against the tool schema, ensuring every request is properly formed. This provides a safety layer for your growth operations. You get predictable, type-safe interactions every time.

Setup guide

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

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

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

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Common questions about MoEngage MCP in Pydantic AI

Install the necessary packages and use `MCPToolset` with your server URL. Pass it to the agent to start executing validated calls.

The agent throws a validation error immediately. You get a clear log of what failed, preventing corrupted state from propagating.

Security is built into the transport layer. We ensure your API key is handled securely and that all communication is encrypted.

Use `update_device`. The tool schema ensures your device tokens and metadata are formatted correctly before the update is sent.

We enforce strict schema checking on all PII fields. This ensures that only authorized data types are transmitted to the API, keeping your records clean.

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