
Apache Karaf
Docker
Google App Engine
Amazon S3
AWS Elastic Beanstalk
Apache ServiceMix
Cisco CloudCenter
GlusterFS
MCPForge.tech
Composio.dev
Mintlify
Speakeasy
Fern
Pipedream
Zapier
KlavisAI
MCPForge helps developers turn OpenAPI specifications into production-ready MCP servers.
Import an OpenAPI or Swagger specification, generate tools automatically, deploy a hosted MCP server, and manage security, permissions, approvals, and audit logs from a single platform.
Designed for teams building AI agents, internal tooling, and production MCP deployments.
Apache Karaf
MCPForge.techNo MCPForge.tech videos yet. You could help us improve this page by suggesting one.
MCPForge.tech's answer:
Most MCP tools focus on generating servers.
MCPForge focuses on production deployment.
Beyond OpenAPI-to-MCP generation, MCPForge helps teams manage permissions, approvals, audit logs, security reviews, and governance controls required for real-world MCP deployments.
The goal is not just to create MCP servers, but to make them safe and manageable in production environments.
MCPForge.tech's answer:
MCPForge combines MCP generation, hosting, security, and governance in a single platform.
Instead of manually building, deploying, securing, and maintaining MCP servers, teams can import an OpenAPI specification and manage the entire lifecycle from one place.
It is designed for developers who want to move quickly without sacrificing visibility, permissions, and operational control.
MCPForge.tech's answer:
MCPForge is built for AI developers, agent builders, SaaS companies, API providers, automation engineers, and platform teams that want to expose APIs to AI agents through MCP.
It is particularly useful for organizations that already maintain OpenAPI specifications and want a faster path to production-ready MCP deployments.
MCPForge.tech's answer:
Next.js, React, TypeScript, Node.js, PostgreSQL, Prisma, Stripe, OpenAPI, MCP (Model Context Protocol)
MCPForge.tech's answer:
MCPForge started from a simple frustration. While experimenting with MCP, I noticed that most APIs already had OpenAPI specifications, yet exposing them to AI agents still required building and maintaining MCP servers manually. After repeating the same process multiple times, I decided to build a platform that could automate the process and eventually solve the operational challenges around security, permissions, approvals, and governance.
MCPForge.tech's answer:
No public customers yet. MCPForge is currently in its early stages and working with early adopters and developers, evaluating the MCP infrastructure.
Based on our record, Apache Karaf seems to be more popular. It has been mentiond 1 time since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Apache Karaf with OSGi works pretty nice using annotation based dependency injection with the declarative services, removing the need to mess with those hopefully archaic XML blueprints. Too bad it's not as trendy as spring and the developers so many of the tutorials can be a bit dated and hard to find. Karaf also supports many other frameworks and programming models as well and there's even Red Hat supported... Source: over 5 years ago
Docker - Docker is an open platform that enables developers and system administrators to create distributed applications.
Composio.dev - Make Agents Actually Useful!
Google App Engine - A powerful platform to build web and mobile apps that scale automatically.
Mintlify - The AI-powered documentation writer. It's documentation that just appears as you build
Amazon S3 - Amazon S3 is an object storage where users can store data from their business on a safe, cloud-based platform. Amazon S3 operates in 54 availability zones within 18 graphic regions and 1 local region.
Speakeasy - Create great integration experiences for your APIs: native-language SDKs, Terraform providers, and friction-free docs.