Scale AI MCP Server for Pydantic AIGive Pydantic AI instant access to 11 tools to Cancel Task, Create Batch, Create Image Annotation Task, and more

Name: Scale AI
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 Scale AI through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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The Scale AI MCP Server for Pydantic AI is a standout in the Ai Frontier category — giving your AI agent 11 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 Scale AI "
            "(11 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Scale AI?"
    )
    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 Scale AI MCP Server

Connect your Scale AI account to any AI agent to orchestrate large-scale data labeling and fine-tuning pipelines through natural conversation.

Pydantic AI validates every Scale AI tool response against typed schemas, catching data inconsistencies at build time. Connect 11 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

Project Management — Create and configure projects for specific labeling types like image annotation or semantic segmentation.
Batch Operations — Organize high-volume work into batches and finalize them to trigger the labeling process.
Multi-Modal Tasks — Submit tasks for Image Annotation, Semantic Segmentation, and Video Playback directly via API.
Task Lifecycle — Retrieve detailed status of individual tasks or cancel pending ones to manage your budget and throughput.
Parameter Tuning — Update project-level instructions and parameters dynamically to refine labeling quality.

The Scale AI MCP Server exposes 11 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 11 Scale AI tools available for Pydantic AI

When Pydantic AI connects to Scale AI through Vinkius, your AI agent gets direct access to every tool listed below — spanning data-labeling, rlhf, machine-learning, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

cancel

Cancel task on Scale AI

Optionally clears the unique_id to reuse it. Cancel a pending task

create

Create batch on Scale AI

Create a new batch

create

Create image annotation task on Scale AI

Create an Image Annotation task

create

Create named entity recognition task on Scale AI

Create a Named Entity Recognition task

create

Create project on Scale AI

Create a new Scale project

create

Create segment annotation task on Scale AI

Create a Semantic Segmentation task

create

Create text collection task on Scale AI

Create a Text Collection task

create

Create video playback annotation task on Scale AI

Create a Video Annotation task

finalize

Finalize batch on Scale AI

Finalize a batch

get

Get task on Scale AI

Retrieve a specific task

update

Update project params on Scale AI

Update project parameters

Connect Scale AI to Pydantic AI via MCP

Follow these steps to wire Scale AI 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 11 tools from Scale AI with type-safe schemas

Why Use Pydantic AI with the Scale AI MCP Server

Pydantic AI provides unique advantages when paired with Scale 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 Scale 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 Scale AI connection logic from agent behavior for testable, maintainable code

Scale AI + Pydantic AI Use Cases

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

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

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

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

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

Example Prompts for Scale AI in Pydantic AI

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

"Create a new image annotation project called 'Lidar-Obstacles' for imageannotation."

"Submit an image annotation task to project 'Lidar-Obstacles' with the image URL 'https://example.com/car.jpg'."

"Finalize the batch named 'sprint-01-batch'."

Troubleshooting Scale AI MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Scale AI + Pydantic AI FAQ

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

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