How to Use the Firebase (REST & Admin APIs) MCP in Pydantic AI

Get type-safe control over Firebase (REST & Admin APIs) using Pydantic AI for reliable data handling.

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Connect Firebase (REST & Admin APIs) MCP to Pydantic AI

Create your Vinkius account to connect Firebase (REST & Admin APIs) 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 Firebase (REST & Admin APIs) with Pydantic AI

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Claude

Perplexity

Type-safe Firestore with Pydantic AI

Every response from `firestore_get_doc` or `firestore_create_doc` is validated against your Pydantic models. If the database returns malformed data, your agent stops immediately. This prevents silent corruption and ensures your application state remains consistent throughout every transaction.

Realtime Database precision in Pydantic AI

Use `rtdb_put` and `rtdb_delete` with full validation. Pydantic AI ensures that your agent's write operations conform to the expected schema before they ever hit the database. It provides a strict boundary that forces the agent to handle errors explicitly, rather than hallucinating field names or data types.

Auth and messaging validation for Pydantic AI

Validate your `auth_lookup` responses to ensure user data matches your internal requirements. Use `fcm_send_message` to push notifications with verified payloads. Your agent maintains a high degree of correctness by verifying every interaction with the Firebase backend at runtime.

Setup guide

Set up Firebase (REST & Admin APIs) 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": {
        "firebase-rest-admin-apis-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent Firebase (REST & Admin APIs) transactions")
print(result.output)

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Common questions about Firebase (REST & Admin APIs) MCP in Pydantic AI

Install the pydantic-ai-slim package, then instantiate the MCPToolset with your server URL. Pass this object to your agent to enable type-safe tool execution.

Yes. The server supports SSE transports, which Pydantic AI handles natively. This ensures a persistent connection for your agent workflows.

The agent throws a validation error immediately. This stops the workflow before bad data can propagate, keeping your system integrity intact.

It is an ideal pairing if you prioritize correctness. The strict schema enforcement of Pydantic AI complements the direct nature of these REST tools.

All authentication tokens are handled server-side by Vinkius. Your agent never touches raw credentials, ensuring your Auth data and Firestore records remain secure.

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