MCP Facade

MCP Facade serves as a single, unified gateway for AI assistants that need to interact with multiple MCP (Machine Conversation Protocol) servers. Instead of configuring each assistant or agent separately for every backend, developers can register all their MCP servers in one place and let the facade route requests transparently. This simplifies architecture, reduces duplication of configuration code, and centralizes access control, making it easier to enforce consistent security policies across a fleet of services.

The core value lies in its unified access point. Agents can query a single API to discover available tools, call them, and receive results without worrying about the underlying server URLs or authentication details. The facade automatically forwards JSON‑RPC calls to the appropriate backend, aggregates responses, and exposes a consistent tool list that reflects all registered servers. For developers building complex workflows—such as chaining multiple tools from different domains—the ability to treat disparate services as a cohesive toolbox is a significant productivity boost.

Key capabilities include:

• Server Management – Register, update, and delete MCP servers through RESTful endpoints. Each server is identified by a friendly name and its endpoint URL, allowing quick onboarding of new services.
• Tool Discovery – A consolidated view of all tools across servers is exposed, enabling agents to list and filter by name or category without manual aggregation.
• Fine‑grained Access Control – JWT authentication combined with configurable access rules at the tool level ensures that only authorized agents can invoke specific capabilities, protecting sensitive operations.
• Health Monitoring – Built‑in health check endpoints provide visibility into the operational status of each registered server, aiding observability and automated fail‑over strategies.
• Persistent Configuration – PostgreSQL stores server metadata and access policies, ensuring durability and ease of migration or scaling.

Typical use cases span from enterprise chatbots that need to access a mix of internal data services (e.g., HR, finance) and external APIs (e.g., weather, stock quotes), to research assistants that combine simulation tools with natural language interfaces. In a multi‑tenant environment, the facade can enforce tenant‑specific tool permissions, making it ideal for SaaS platforms that expose a shared MCP infrastructure to customers.

Integration into AI workflows is straightforward: an assistant’s configuration points to the facade’s base URL, and all subsequent tool calls are routed through it. The agent remains agnostic to the number or location of backends, allowing developers to evolve their tool ecosystem without touching the agent code. This decoupling not only speeds iteration but also provides a clear audit trail for compliance, as every request passes through the single authenticated gateway.