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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Gate22 serves as a robust AI governance and Model Context Protocol (MCP) control platform designed for enterprises, centralizing the security and oversight of how AI tools and agents interact with MCP servers within an organization. It empowers administrators to onboard, configure, and regulate both internal and external MCP servers, offering detailed permissions at the functional level, team-based access control, and role-specific policies to ensure that only sanctioned tools and functionalities are accessible to designated teams or users. By providing a cohesive MCP endpoint, Gate22 aggregates multiple MCP servers into an intuitive interface featuring just two primary functions, leading to reduced token consumption for developers and AI clients, while effectively minimizing context overload and ensuring both precision and security. The administrative interface includes a governance dashboard that allows for the monitoring of usage trends, compliance maintenance, and enforcement of least-privilege access, while the member interface facilitates streamlined and secure access to authorized MCP bundles. This dual-view approach not only enhances operational efficiency but also strengthens overall security within the organizational framework.

Description

Model Garden serves as a catalog for AI and machine-learning models within the Google Cloud AI platform. It assists teams in discovering, assessing, tailoring, and implementing Google models alongside selected offerings from partners and open-source creators. Each model page offers tailored guidance and deployment alternatives; based on the specific model, users may have the opportunity to test, use a managed API, adjust settings, or deploy the model to a cloud endpoint. Developers can navigate through the Google Cloud console, utilizing supported APIs, SDKs, and command-line tools for their tasks. This resource is specifically designed for developers, data scientists, and machine-learning teams focused on creating generative AI and various applications powered by models. The availability of models, choices for deployment, and related usage costs can differ based on the model and its configuration. Therefore, users should review the specifics of each model to ensure optimal implementation.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Gemini No 
Gemini Enterprise Agent Platform No 
Google Cloud CLI No 
Google Cloud Platform No 
Hugging Face No 
Model Context Protocol (MCP) Yes 

Integrations

Gemini Yes 
Gemini Enterprise Agent Platform Yes 
Google Cloud CLI Yes 
Google Cloud Platform Yes 
Hugging Face Yes 
Model Context Protocol (MCP) No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

Costs depend on the selected model and its usage, plus any managed endpoint or compute resources used; applicable model and infrastructure rates vary by configuration.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

ACI.dev

Country

United States

Website

gate22-docs.aci.dev/introduction/overview

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

cloud.google.com/model-garden

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