How to Use the Applitools MCP in Pydantic AI

Q: Can Pydantic AI validate the Applitools API key at runtime?

Yes, the agent calls validatekey to check your credentials. The response is validated against a strict Pydantic model to confirm the connection is active.

Q: How does Pydantic AI handle Applitools batch statistics?

The agent invokes getbatchstats to get passed, failed, and unresolved counts. Pydantic AI parses this payload into a type-safe object so your agent can make reliable routing decisions.

Q: What happens if a visual baseline is not found?

When listbaselines returns an empty set or an unexpected schema, Pydantic AI raises a validation error. This prevents the agent from attempting operations on non-existent visual states.

Build type-safe visual testing workflows with Pydantic AI and the Applitools MCP Server.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Applitools MCP to Pydantic AI

Create your Vinkius account to connect Applitools 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.

GDPR Free for Subscribers

Setup Applitools with Pydantic AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Type-safe visual batch validation

Stop worrying about malformed visual test responses. Your Pydantic AI agent uses `get_batch` to fetch visual test run details, validating every field against strict schemas. If the Applitools API returns unexpected test data, the framework fails instantly. You catch API mismatches immediately instead of letting corrupted visual data pass through.

Clean up baselines safely with Pydantic AI

Deleting visual states requires absolute precision. Your agent calls `list_baselines` to find the correct visual baseline IDs, ensuring the data matches your Pydantic schemas. Once validated, the agent uses `delete_baseline` to remove the outdated visual target. This type-safe execution guarantees you never delete the wrong baseline due to a string parsing error.

Direct session debugging via MCP Server

Debugging UI diffs shouldn't be a guessing game. Your agent calls `get_session` to pull structured visual testing data for failed runs. This MCP Server tool feeds clean, type-validated session data to your local or cloud LLM. Your agent can confidently pinpoint which UI elements failed without hallucinating fields.

Setup guide

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

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

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Applitools. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Applitools now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Applitools MCP in Pydantic AI

Use the MCPToolset class with your Vinkius HTTP endpoint. Pass this toolset directly to your Pydantic AI Agent to expose the visual testing tools.

Yes, the agent calls `validate_key` to check your credentials. The response is validated against a strict Pydantic model to confirm the connection is active.

The agent invokes `get_batch_stats` to get passed, failed, and unresolved counts. Pydantic AI parses this payload into a type-safe object so your agent can make reliable routing decisions.

When `list_baselines` returns an empty set or an unexpected schema, Pydantic AI raises a validation error. This prevents the agent from attempting operations on non-existent visual states.

All visual baseline IDs and test results are validated locally within your Python runtime. The server operates in a zero-trust environment, ensuring your visual test data remains private.

Use it with your favorite AI tools

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

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript