How to Use the ESPHome MCP in Pydantic AI

Q: Does Pydantic AI support all ESPHome tools?

It supports every tool listed, including coveraction and alarmaction. You just add the MCPToolset to your agent, and the types are inferred automatically.

Q: How do I monitor ESPHome devices in Pydantic AI?

Call getmetrics through the MCP toolset. The framework will validate the returned metrics against your defined Pydantic models.

Bring type-safety to IoT with Pydantic AI. Validated ESPHome tool execution for your most critical automation tasks.

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Connect ESPHome MCP to Pydantic AI

Create your Vinkius account to connect ESPHome 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 ESPHome with Pydantic AI

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Perplexity

Type-safe ESPHome control in Pydantic AI

Stop worrying about malformed tool calls. Every output from the server is validated against your Pydantic models before the agent processes it. If the `light_action` or `fan_action` returns unexpected data, the agent fails immediately. This prevents bad state from propagating through your logic.

Monitoring devices with Pydantic AI

Retrieve sensor data and validate it against your schemas using `get_entity_state`. You define the expected structure, and the framework enforces it. This is ideal for monitoring critical infrastructure. You get clean, typed data that your agent can trust for every decision it makes.

Reliable action execution

Trigger `button_press` or `number_set` with confidence. The server provides the tools, and Pydantic AI ensures the inputs are perfect. This setup is built for correctness. By using the MCPToolset, you integrate your hardware into a system that values data integrity above all else.

Setup guide

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

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

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

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Common questions about ESPHome MCP in Pydantic AI

It enforces runtime validation for all tool responses. If your device returns a weird state, the framework catches it, ensuring your agent never acts on corrupted data.

It supports every tool listed, including `cover_action` and `alarm_action`. You just add the MCPToolset to your agent, and the types are inferred automatically.

Call `get_metrics` through the MCP toolset. The framework will validate the returned metrics against your defined Pydantic models.

It is designed for production use. The server runs externally, and Pydantic AI maintains the connection via the MCP protocol for reliable communication.

The framework processes sensor data in memory. Sensitive state information is never stored or transmitted outside your local execution environment.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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