AppXen

AppXen is a Managed MCP Infrastructure for AI Agents The Model Context Protocol (MCP) is becoming the standard way AI models connect to external tools, data sources, and APIs. But running MCP infrastructure in production is complex, you need proxying, authentication, rate limiting, multi-agent coordination, knowledge retrieval, and safety controls. AppXen provides all of it, fully managed, so your team can build AI-powered workflows without building or operating the infrastructure underneath them.

MCP Gateway The foundation of the AppXen platform. MCP Gateway is a fully managed MCP proxy that connects AI models, including Claude, GPT, and any MCP-compatible client, to your tools and APIs through a single, authenticated endpoint. Add MCP servers in the AppXen console and they become immediately available to your AI models, your orchestrated workflows, and Claude Desktop. No JSON config files. No credential management across environments. No self-hosted infrastructure to maintain.

Built-in capabilities include: API key and JWT authentication Per-tenant rate limiting and usage metering REST-to-MCP bridging, expose any existing REST API as an MCP tool in minutes Structured logging and CloudWatch observability Multi-tenant architecture with isolated routing per customer

Supported integrations: GitHub, Neon Postgres, Supabase, Zapier, AWS CloudWatch, and any REST API endpoint.

RAG Engine AI agents are only as useful as the context they have access to. RAG Engine is AppXen's managed knowledge layer, upload documents, technical specs, runbooks, or any text-based content, and it becomes instantly searchable by your agents and workflows. Content is chunked, embedded, and indexed automatically. No vector database to provision. No embedding pipeline to build. Agents query the knowledge base as a native MCP tool, grounded responses, not hallucinations. Use RAG Engine to give your agents access to internal documentation, product requirements, compliance policies, or any proprietary knowledge that shouldn't leave your control.

Orchestrator Multi-agent workflows, defined in plain markdown. Orchestrator lets you compose sequences of specialized agents, each with access to your connected MCP tools and RAG knowledge base, without writing orchestration code. Define what each agent should do in natural language, chain them together, and run the workflow on demand or on a schedule.

Example workflows teams run today: Code review pipelines that analyze a repo, flag security issues, and write findings to a database Document analysis workflows that search the knowledge base, cross-reference live data, and produce structured reports Incident response workflows that pull CloudWatch logs, identify error patterns, and summarize findings for on-call engineers

Outputs can be written to Postgres, surfaced in Claude Desktop, forwarded via webhook, or fed into the next agent in the sequence. Every run is logged and auditable.

How AppXen fits into your stack AppXen works alongside the tools your team already uses. Connect your existing APIs, databases, and services as MCP tools. Run workflows from Claude Desktop, from your CI/CD pipeline, or on a schedule. Subscribe through AWS Marketplace and usage is metered and billed directly through your AWS account, no separate procurement, no new vendor relationships. Pricing is pay-as-you-go:

MCP Gateway: per request and per server-hour RAG Engine: per query and per compute-hour Orchestrator: per agent-hour and per base-hour

No upfront commitments. No minimum spend. Scale from a single developer to an enterprise team on the same platform.

Built for production from day one AppXen infrastructure runs on AWS with multi-AZ deployment, 99.9% uptime SLA, end-to-end encryption, and structured audit logging on every request. RTO under 15 minutes. RPO under 5 minutes. The platform is designed for teams who want the capabilities of a full AI agent infrastructure stack, without the engineering overhead of building and maintaining it themselves.