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What is Peta?

Peta acts as a sophisticated control plane for the Model Context Protocol (MCP), facilitating, securing, regulating, and supervising the interactions between AI clients and agents with external resources, data, and APIs. The platform incorporates a zero-trust MCP gateway, a secure vault, a managed runtime environment, a policy engine, human-in-the-loop approvals, and extensive audit logging into a unified solution, allowing organizations to enforce detailed access controls, protect sensitive credentials, and track all interactions performed by AI systems. Central to Peta is Peta Core, which serves as both a secure vault and gateway, responsible for encrypting credentials, generating ephemeral service tokens, ensuring identity verification and policy compliance for each request, managing the lifecycle of the MCP server through lazy loading and auto-recovery, and injecting credentials at runtime without exposing them to agents. Furthermore, the Peta Console enables teams to determine which users or agents can access specific MCP tools within defined environments, set up approval processes, manage tokens, and analyze usage data along with associated costs. This comprehensive strategy not only bolsters security but also promotes effective resource management and accountability across AI operations, ultimately leading to improved operational efficiency and enhanced oversight. By integrating these functionalities, Peta establishes a robust foundation for organizations seeking to optimize their AI-driven initiatives.

What is Docker MCP Gateway?

The Docker MCP Gateway serves as a crucial open source component within the Docker MCP Catalog and Toolkit, specifically crafted to operate Model Context Protocol (MCP) servers inside isolated Docker containers that maintain limited privileges, restricted network access, and specific resource constraints, thus ensuring secure and reliable environments for AI applications. This component manages the entire lifecycle of MCP servers by initiating containers whenever an AI application demands a particular tool, injecting required credentials, implementing security protocols, and routing requests so that servers can efficiently handle them and provide results through a single, integrated gateway interface. By consolidating all operational MCP containers behind a single access point, the Gateway simplifies the process for AI clients to find and utilize various MCP services, reducing redundancy, enhancing performance, and centralizing configuration and authentication aspects. Ultimately, it simplifies the interactions between AI applications and a variety of services, promoting a more streamlined development process while significantly improving overall system security. Additionally, this integrated approach allows developers to focus on innovation rather than managing complex service interactions, further enhancing productivity and effectiveness in AI deployment.

Media

Media

Integrations Supported

Model Context Protocol (MCP)
AutoGen
ChatGPT
Claude
Claude Duet
Claude for Legal
CrewAI
Cursor
LangChain
Microsoft Teams
Slack
n8n

Integrations Supported

Model Context Protocol (MCP)
Docker
ZizkaDB

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Version

Pricing Information

Free
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Peta

Company Location

United States

Company Website

peta.io

Company Facts

Organization Name

Docker

Date Founded

2013

Company Location

United States

Company Website

docs.docker.com/ai/mcp-catalog-and-toolkit/mcp-gateway/

Categories and Features

AI Control Planes

Not specified

MCP Gateways

Not specified

Categories and Features

MCP Gateways

Not specified

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