Webrix's answer

Webrix is the only enterprise MCP Gateway built specifically for AI adoption at scale. Unlike generic API management or agent platforms, we provide purpose-built infrastructure that connects any MCP-compatible AI agent to internal systems through a single secure gateway. Our architecture is built on the open Model Context Protocol standard (avoiding vendor lock-in), provides enterprise-grade security controls from day one (SSO, RBAC, audit trails), and enables self-service tool access without IT bottlenecks. We solve the last-mile problem that blocks AI adoption: giving employees instant, secure access to the internal tools their AI agents need.

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.

Webrix's answer

• Flexible Deployment: Choose on-premise, dedicated cloud, or SaaS based on your security requirements
• Real Enterprise Usage: Already deployed at 5,000+ employee organizations with complex security needs
• Security-First Architecture: Enterprise security controls aren't bolted on later - they're foundational
• Universal Agent Support: Works with Claude, ChatGPT, Cursor, n8n, and any MCP-compatible agent
• Developer Experience: Built by developers for developers - fast setup, clear documentation, minimal friction

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.

Webrix's answer

AI adoption leaders, VPs of Engineering, CTOs, and technical decision-makers at mid-to-large enterprises (500-5,000+ employees) that build software in-house. These organizations have strong technical capabilities, existing internal tools that need AI integration, and security/compliance requirements that prevent ad-hoc AI tool adoption. Secondary audiences include security teams evaluating POCs, engineering teams wanting faster AI tool access, and IT leaders needing visibility into AI usage and ROI.

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.

Webrix's answer

Webrix was founded by developers who saw the same pattern repeating across enterprises: employees wanted to use AI tools like Claude, Cursor, and ChatGPT with their internal systems, but security teams had to block access because there was no safe way to connect AI agents to Jira, GitHub, databases, and internal APIs. IT teams were drowning in access requests while developers worked around restrictions. We built Webrix to solve this fundamental infrastructure gap - providing the secure gateway layer that enterprises need to actually adopt AI at scale without compromising security, compliance, or control.

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.

Webrix's answer

Kubernetes for container orchestration, Helm for deployment management, Docker for containerization, and the Model Context Protocol (MCP) as the core standard for agent-tool communication. Our gateway runs on cloud-native infrastructure with support for PostgreSQL for session management, integrates with standard identity providers (Okta, Azure AD, Google Workspace) for SSO, and uses industry-standard security practices including secrets management, and audit logging.

MCPForge.tech's answer:

Next.js, React, TypeScript, Node.js, PostgreSQL, Prisma, Stripe, OpenAPI, MCP (Model Context Protocol)

Webrix's answer

• Wix.com (5,000+ employees)
• Leading tech companies in fintech and SaaS sectors
• Enterprise organizations with complex security and compliance requirements

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.