Browse AI 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 Browse AI 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 Browse AI "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Browse AI?"
)
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 Browse AI MCP Server
Connect your Browse AI account to any AI agent and take full control of your no-code web scraping operations through natural conversation.
Pydantic AI validates every Browse AI 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
- Robot Discovery — List all your trained extraction and monitoring robots along with their configuration details
- Execute Scrapes — Trigger specific robots to run tasks on target URLs without lifting a finger
- Data Retrieval — Instantly download the final extracted JSON data from any successfully completed task
- Bulk Operations — Initiate multi-URL concurrent extractions and download the unified bulk datasets
- Monitor Sync — Check the status of your active web change monitors
- Quota Management — Retrieve your current API credits usage and monthly plan limits
The Browse AI 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 Browse AI to Pydantic AI via MCP
Follow these steps to integrate the Browse AI 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 Browse AI with type-safe schemas
Why Use Pydantic AI with the Browse AI MCP Server
Pydantic AI provides unique advantages when paired with Browse AI 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 Browse AI integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Browse AI connection logic from agent behavior for testable, maintainable code
Browse AI + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Browse AI MCP Server delivers measurable value.
Type-safe data pipelines: query Browse AI with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Browse AI tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Browse AI and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Browse AI responses and write comprehensive agent tests
Browse AI MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Browse AI to Pydantic AI via MCP:
download_bulk_data
Returns a JSON array where each element contains the capturedData from one task. Download all extracted results from a completed Browse AI bulk run
get_bulk_task
Get bulk task execution status from Browse AI
get_robot
Get detailed configuration of a specific Browse AI robot
get_task
Check the status of a specific Browse AI extraction task
get_task_data
Only meaningful when the task status is "successful". Fields match the column names configured in the Browse AI robot builder hitting internal task references. Retrieve the final extracted JSON data from a successful Browse AI task
list_credits
Check Browse AI quota limits and credit usage
list_monitors
Monitors run on scheduled intervals to detect changes on target web pages and trigger notifications or data captures automatically via `/monitors`. List all active Browse AI web monitoring robots
list_robots
Each robot represents a no-code AI scraping workflow targeting a specific website or data pattern via `GET /robots`. List all Browse AI extraction and monitoring robots
run_bulk_task
Each set typically contains a different "originUrl". All extractions run concurrently on Browse AI infrastructure. Run a Browse AI robot in bulk mode across multiple URLs
run_robot
Pass a JSON string of input parameters (typically including "originUrl" for the target page and any variable fields the robot expects). Returns a taskId. Trigger a Browse AI robot to extract data from a target URL
Example Prompts for Browse AI in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Browse AI immediately.
"List all my robots. Which ones are built for monitoring?"
"Run my HackerNews Scraper robot on the main page."
"Retrieve the JSON data for task t-78ab31."
Troubleshooting Browse AI MCP Server with Pydantic AI
Common issues when connecting Browse AI to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiBrowse AI + Pydantic AI FAQ
Common questions about integrating Browse AI 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 Browse AI 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 Browse AI to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.