How to Use the PushEngage MCP in Pydantic AI

Use Pydantic AI with PushEngage to ensure your notification logic is type-safe and validated at every step. No more silent errors.

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…and any MCP-compatible client

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Connect PushEngage MCP to Pydantic AI

Create your Vinkius account to connect PushEngage to Pydantic AI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup PushEngage with Pydantic AI

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Type-safe broadcasts in Pydantic AI

Trigger `send_pushengage_broadcast` with validated inputs. Pydantic AI checks your data types against the schema before the API call fires. This stops malformed data from reaching the server. If your payload is invalid, the agent errors out immediately, keeping your logs clean.

Validate subscriber lists in Pydantic AI

Run `list_pushengage_subscribers` and parse the output directly into your Pydantic models. You get structured, type-checked data every time. Your agent relies on this strict validation to make decisions. It eliminates the risk of field mismatches or unexpected null values.

Check status with Pydantic AI

Use `check_pushengage_status` to verify the connection health as a pre-flight check. Your agent won't proceed unless the API responds correctly. This ensures your automation flows only run when the system is ready. It adds a layer of reliability to your agent's operation.

Setup guide

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

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

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

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