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What is Model Context Protocol (MCP)?

The Model Context Protocol (MCP) serves as a versatile and open-source framework designed to enhance the interaction between artificial intelligence models and various external data sources. By facilitating the creation of intricate workflows, it allows developers to connect large language models (LLMs) with databases, files, and web services, thereby providing a standardized methodology for AI application development. With its client-server architecture, MCP guarantees smooth integration, and its continually expanding array of integrations simplifies the process of linking to different LLM providers. This protocol is particularly advantageous for developers aiming to construct scalable AI agents while prioritizing robust data security measures. Additionally, MCP's flexibility caters to a wide range of use cases across different industries, making it a valuable tool in the evolving landscape of AI technologies.

What is Amazon SageMaker?

Amazon SageMaker is a robust platform designed to help developers efficiently build, train, and deploy machine learning models. It unites a wide range of tools in a single, integrated environment that accelerates the creation and deployment of both traditional machine learning models and generative AI applications. SageMaker enables seamless data access from diverse sources like Amazon S3 data lakes, Redshift data warehouses, and third-party databases, while offering secure, real-time data processing. The platform provides specialized features for AI use cases, including generative AI, and tools for model training, fine-tuning, and deployment at scale. It also supports enterprise-level security with fine-grained access controls, ensuring compliance and transparency throughout the AI lifecycle. By offering a unified studio for collaboration, SageMaker improves teamwork and productivity. Its comprehensive approach to governance, data management, and model monitoring gives users full confidence in their AI projects.

Media

Media

Integrations Supported

AWS Clean Rooms
AWS Deep Learning Containers
AWS IoT Core
Amazon Augmented AI (A2I)
Amazon EC2 Capacity Blocks for ML
Amazon Linux 2
Amazon SageMaker Autopilot
Amazon Web Services (AWS)
Claude
Claude 3 Opus
CognitiveScale Cortex AI
Deep Lake
GrimoAI
Lemma
New Relic
Okera
Qlik Staige
TruEra
Windsurf Editor
neptune.ai

Integrations Supported

AWS Clean Rooms
AWS Deep Learning Containers
AWS IoT Core
Amazon Augmented AI (A2I)
Amazon EC2 Capacity Blocks for ML
Amazon Linux 2
Amazon SageMaker Autopilot
Amazon Web Services (AWS)
Claude
Claude 3 Opus
CognitiveScale Cortex AI
Deep Lake
GrimoAI
Lemma
New Relic
Okera
Qlik Staige
TruEra
Windsurf Editor
neptune.ai

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Anthropic

Date Founded

2021

Company Location

United States

Company Website

modelcontextprotocol.io

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/sagemaker/

Categories and Features

Categories and Features

Data Labeling

Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
SDK
Supports Audio Files
Task Management
Team Collaboration
Training Data Management

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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