Perfecto 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 Perfecto 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 Perfecto "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Perfecto?"
)
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 Perfecto MCP Server
Control quality testing automation instances seamlessly connecting LLM parameters directly bounding your Perfecto Cloud. Retrieve precise matrix tracking devices explicitly parsing metadata, lookup explicitly bounded execution logs driving advanced tracking boundaries securely seamlessly efficiently. Automate evaluation boundaries querying Smart Reporting natively natively analyzing testing matrices confidently bypassing manual legacy UI navigation.
Pydantic AI validates every Perfecto 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
- Device State Discovery — Explore testing grids tracking device topologies fetching available Android/iOS instances tracking native limits gracefully
- Execution Diagnostics — Evaluate structural loops mapping testing histories checking bounds isolating failed loops parsing native status parameters perfectly
- Repository Traceability — Read explicit bounds searching exact artifacts tracking storage buckets safely seamlessly verifying native dependencies natively
- Smart Reporting Audits — Extract logical limits processing advanced JSON outputs mapping comprehensive test validations checking explicit step counts confidently
The Perfecto 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 Perfecto to Pydantic AI via MCP
Follow these steps to integrate the Perfecto 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 Perfecto with type-safe schemas
Why Use Pydantic AI with the Perfecto MCP Server
Pydantic AI provides unique advantages when paired with Perfecto 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 Perfecto integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Perfecto connection logic from agent behavior for testable, maintainable code
Perfecto + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Perfecto MCP Server delivers measurable value.
Type-safe data pipelines: query Perfecto with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Perfecto tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Perfecto and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Perfecto responses and write comprehensive agent tests
Perfecto MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Perfecto to Pydantic AI via MCP:
get_device_details
Get full details of a Perfecto device including model, OS, firmware, manufacturer, resolution, location, and current status
get_execution_details
Get status of a Perfecto execution by ID. Returns status, progress, device assignments, and timestamps
get_license_info
Get Perfecto license information. Returns license type, device limits, concurrent executions, and expiration
get_report_summary
Get Smart Reporting summary for a Perfecto execution. Returns test results, pass/fail counts, video/screenshot links, and detailed step data
list_artifacts
List artifacts in Perfecto repository at a given path. Includes apps, scripts, images, and data files
list_device_groups
List device groups on Perfecto. Groups organize devices by type/OS/team. Returns group names and member devices
list_devices
List all available devices on Perfecto Cloud. Perfecto (by Perforce) is an enterprise mobile and web testing cloud with real devices and browsers. Returns device IDs, models, OS versions, manufacturers, locations, and availability statuses
list_executions
List current/recent executions on Perfecto. Returns execution IDs, statuses, script names, devices used, and timestamps
list_reservations
List device reservations on Perfecto. Returns reservation IDs, devices, users, start/end times
list_users
List all users on the Perfecto cloud. Returns usernames, roles, emails, and access levels
Example Prompts for Perfecto in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Perfecto immediately.
"Check matrices explicitly parsing structural targets querying `list_devices` globally discovering bounded limits seamlessly tracking iPhones safely."
"Execute validation tracking executions fetching deeply the report natively checking explicit execution ID 'exe_909' bounds accurately gracefully carefully natively."
Troubleshooting Perfecto MCP Server with Pydantic AI
Common issues when connecting Perfecto to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiPerfecto + Pydantic AI FAQ
Common questions about integrating Perfecto 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 Perfecto 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 Perfecto to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.