Application MCP

Overview

When you build and deploy a Mindbricks project, each service automatically exposes its Business APIs as MCP tools. This means every CRUD operation, custom query, workflow action, or integration endpoint you define in your project configuration becomes available as a structured MCP tool — no additional coding required.

External AI agents connect through the MCP-BFF (Backend-for-Frontend) service, which aggregates tools from all services into a single unified MCP endpoint.

What Generated Projects Provide

Each generated service runs an MCP endpoint at:

{serviceUrl}/mcp

The tools include:

• Data CRUD operations — Create, read, update, delete, and list records
• Custom Business APIs — Any API you define in your business logic (filtered queries, aggregations, batch operations)
• File operations — Upload, download, and manage attachments (if S3 is configured)
• Payment flows — Payment intents, subscription management (if Stripe is configured)
• Auth operations — User management, API key management, permission assignments

Controlling MCP Tool Visibility

By default, all Business APIs are exposed as MCP tools. You can exclude specific APIs from MCP exposure by setting blockMcp: true on a Business API. This is useful for internal APIs that should only be accessed via REST.

The MCP-BFF Aggregation Layer

External AI agents don't connect to individual services. Instead, the MCP-BFF (Backend-for-Frontend) service aggregates tools from all services into a single unified MCP endpoint.

Two transports are supported:

Where {appUrl} follows the standard Mindbricks URL pattern:

• Preview: https://{codename}.prw.mindbricks.com
• Staging: https://{codename}-stage.mindbricks.co
• Production: https://{codename}.mindbricks.co

The MCP-BFF:

• Discovers tools from all registered services
• Presents a unified tool catalog to connecting clients
• Routes tool calls to the correct service
• Propagates authentication context (JWT or API key sessions)
• Supports tenant-aware routing in multi-tenant projects

When MCP Is Useful in Generated Projects

MCP integration makes generated projects immediately consumable by AI agents. Common use cases include:

• AI-powered frontends — Tools like Lovable, Bolt, or Cursor can use MCP tools to interact with your backend while building the frontend
• Automated workflows — AI agents can execute multi-step business operations by composing MCP tool calls
• Data exploration — AI agents can query, filter, and aggregate your application data through natural language
• Admin dashboards — AI chat interfaces can provide admin users with natural language access to management operations
• Integration scripts — Automated pipelines can use MCP tools to read or write data across services

Frontend Prompts

Each generated project produces frontend prompt documents — detailed markdown guides that describe how to build the frontend for each part of the application. These prompts are served through the MCP-BFF's documentation endpoints:

• GET /api/docs/prompts — Lists all available prompts with metadata
• GET /api/docs/prompts/:promptName — Returns a specific prompt as markdown

Prompts cover:

• Authentication pages (login, register, forgot password)
• Profile management (user settings, avatar, API key management)
• User administration (user list, role assignment)
• Verification flows (email, mobile, 2FA)
• Service-specific CRUD pages (one per business service)
• Payment flows (if configured)

Authentication for MCP Clients

MCP clients must authenticate when connecting. Two methods are supported:

1. JWT Token — Pass a valid JWT in the Authorization: Bearer {token} header
2. API Key (recommended for AI agents) — Pass an API key in the Authorization: Bearer sk_mbx_... header

API keys are preferred for AI agents because they don't expire like JWT access tokens. The system detects API keys by their sk_mbx_ prefix and validates them through Redis cache or the auth service.

Related Pages

• MCP-BFF Service — MCP-BFF behavior and configuration
• Genesis MCP — Use the Mindbricks Genesis MCP server to design and manage projects with AI agents
• Auth Service Assets — Auth service generated assets including API key management
• Authentication and Authorization — Authentication configuration including API key setup
• Build Your API — Business API configuration and MCP tool exposure