"Octopus Deploy" matching MCP servers:

Wraps the Claude Agent SDK as MCP servers, letting you spawn multiple specialized Claude Code agents — each with its own model, tools, system prompt, and personality — from any MCP client.

An MCP server that wraps the OpenAI Codex SDK to deploy multiple specialized AI agents with individual configurations for models, sandboxing, and behavior. It enables users to manage dedicated tools for tasks like code review and test writing through a customizable agent factory.

Connects AI assistants to the ADAS platform, enabling them to build, validate, and deploy multi-agent systems through natural language commands without manual configuration.

Enables AI agents to deploy applications to AWS with DevOps capabilities by automatically inferring infrastructure needs from code and generating inspectable Infrastructure as Code specifications.

Coordinates specialized agents (Architecture, Quality, Cloud, Prompt) to plan, build, test, and deploy applications with self-healing capabilities, authentication, and analytics for autonomous software engineering workflows.

Enables defenders to deploy a decoy MCP tool server that records and fingerprints how LLM agents probe, escalate, and persist, without exposing real systems.

Zero-Ops deploy of a private AI coding workspace to your own VPS, straight from your AI chat. Registers the user, recommends a VPS, and runs and monitors the full deployment.

Coordinates specialized agents (Architecture, Quality, Cloud, Prompt) to autonomously plan, build, test, and deploy applications with self-healing capabilities, authentication via Descope, and analytics through Cequence.

A shared memory and coordination layer for AI coding agents that provides a tamper-evident timeline, conflict awareness, and attribution for multi-agent coding workflows.

Enables users to deploy a production-grade control plane for agents, providing a spec-compliant MCP server, scoped tool grants, failure-mode detection, and cost governance.

A TypeScript implementation of a Model Context Protocol server that provides a frictionless framework for developers to build and deploy AI tools and prompts, focusing on developer experience with zero boilerplate and automatic tool registration.

Provides a chat interface with natural language processing to deploy and manage AWS resources through an integrated Model Context Protocol (MCP) server.

An MCP server that provides jokes to Microsoft Copilot Studio, demonstrating how to deploy a Model Context Protocol server that delivers Chuck Norris and Dad jokes upon request.

Enable AI agents to autonomously build and deploy full-stack mobile applications.

A basic example of developing and running serverless Model Context Protocol (MCP) using Netlify Functions, demonstrating how to deploy and access serverless functions with customized URLs.

Enables AI models to generate, validate, and deploy network topologies directly into Cisco Packet Tracer from natural-language prompts.

A containerized MCP server deployed on Amazon EKS that provides a simple calculator tool for adding two numbers. Demonstrates how to deploy and scale MCP servers in a Kubernetes environment with proper session management and HTTP endpoints.

Enables AI agents to gate real-world side effects through a durable decision record, ensuring at-most-once initiation, deduplication, budget enforcement, and auditable outcomes across retries and failures.

The accountability layer for AI agents — a named human's signed yes before an agent does anything irreversible (payment, record change, deploy), then an offline-verifiable Trust Receipt. Apache-2.0, formally verified.

Hand a human a rich interactive UI by URL from any MCP client and get structured data back: forms, approvals, surveys, pickers, editable lists. Round-trip human-in-the-loop for agents.