Applitools MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Applitools through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 Applitools "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Applitools?"
)
print(result.data)
asyncio.run(main())
* 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 Applitools MCP Server
Connect your Applitools Eyes testing suite to your AI agent and manage your entire visual regression pipeline without opening the dashboard. Allow your agent to spot UI changes, validate baselines, and assess testing health dynamically.
Pydantic AI validates every Applitools tool response against typed schemas, catching data inconsistencies at build time. Connect 10 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
- Batch Observability — Query active test batches to view aggregated statuses (Passed, Failed, Unresolved) and completion rates
- Session & Results analysis — Drill down into specific test sessions to examine failed step images, match levels, and browser differences
- Baseline Management — List your "golden" graphical baselines bound to applications or specific Git branches
- Actionable Maintenance — Authorize the agent to delete outdated baselines or discard legacy batches to keep your workspace clean
- Key Validation — Ensure connectivity against your visual AI engine before pipeline triggers
The Applitools MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Applitools to Pydantic AI via MCP
Follow these steps to integrate the Applitools MCP Server with Pydantic AI.
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 10 tools from Applitools with type-safe schemas
Why Use Pydantic AI with the Applitools MCP Server
Pydantic AI provides unique advantages when paired with Applitools 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 Applitools integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Applitools connection logic from agent behavior for testable, maintainable code
Applitools + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Applitools MCP Server delivers measurable value.
Type-safe data pipelines: query Applitools with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Applitools tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Applitools and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Applitools responses and write comprehensive agent tests
Applitools MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Applitools to Pydantic AI via MCP:
delete_baseline
Use when a baseline is outdated or a page has been redesigned. Delete an Applitools test baseline
delete_batch
Does NOT affect baselines. Use with caution — this is irreversible. Delete an Applitools test batch
get_batch
Use batch ID from list_batches. Get full details of an Applitools batch
get_batch_stats
Returns passed/failed/unresolved/new counts without full test data. Get summary statistics for an Applitools batch
get_session
Provide batch ID and session ID. Get details of a test session within an Applitools batch
list_baselines
Returns baseline IDs, names, and env configs. Filter by app name. List visual baselines for an app on Applitools
list_batches
Batches group related test sessions. Returns batch IDs, names, statuses (Passed/Unresolved/Failed), and test counts. Each batch has a unique ID used to query its results. List all test batches on Applitools Eyes
list_branch_baselines
Use to inspect branch-specific visual states. List baselines for a specific branch on Applitools
list_results
List all test results in an Applitools batch
validate_key
Use to verify connectivity before running tests. Validate the Applitools API key
Example Prompts for Applitools in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Applitools immediately.
"List the most recent visual test batches in Applitools."
"Get me the exact session results for our unresolved batch ID b_991x."
"List the baselines assigned specifically to fixing the 'feature/dark-mode-header' branch."
Troubleshooting Applitools MCP Server with Pydantic AI
Common issues when connecting Applitools to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiApplitools + Pydantic AI FAQ
Common questions about integrating Applitools MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
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?
Can I switch LLM providers without changing MCP code?
Connect Applitools with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Applitools to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.