Gotify MCP Server for Pydantic AIGive Pydantic AI instant access to 22 tools to Change Password, Create Application, Create Client, and more

Name: Gotify
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Gotify through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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The Gotify MCP Server for Pydantic AI is a standout in the Communication Messaging category — giving your AI agent 22 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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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 Gotify "
            "(22 tools)."
        ),
    )

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

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<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 Gotify MCP Server

Connect your Gotify instance to any AI agent to streamline your notification workflows. Gotify is a self-hosted notification server, and this MCP server allows you to interact with its API using natural language.

Pydantic AI validates every Gotify tool response against typed schemas, catching data inconsistencies at build time. Connect 22 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

Messaging — Send push notifications with custom priorities and titles, or retrieve and delete existing messages from your stream.
Application Management — Create, list, update, or delete Gotify applications to organize your notification sources and tokens.
Client Control — Manage clients and tokens to authorize different devices or services to receive messages.
User Administration — (Admin only) List or create users to manage access to your private Gotify instance.

update

Update application on Gotify

Update an application

update

Update client on Gotify

Update a client

update

Update plugin config on Gotify

Update plugin configuration

Connect Gotify to Pydantic AI via MCP

Follow these steps to wire Gotify into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 22 tools from Gotify with type-safe schemas

Why Use Pydantic AI with the Gotify MCP Server

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

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

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

Gotify + Pydantic AI Use Cases

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

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

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

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

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

Example Prompts for Gotify in Pydantic AI

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

"Send a high-priority Gotify message titled 'System Alert' saying 'Disk space is low on Server A'."

"List all my current Gotify applications and their descriptions."

"Get the last 5 messages from my Gotify server."

Troubleshooting Gotify MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Gotify + Pydantic AI FAQ

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