@mastra/ai-sdk

Provides a bridge layer that allows developers to register custom API endpoints that conform to the AI SDK's expected request/response contract, enabling seamless integration between Mastra's backend services and AI SDK's UI components. Routes are registered through a declarative configuration system that handles serialization, validation, and protocol translation between the custom logic and the AI SDK's HTTP interface.

Automatically validates incoming requests against expected schemas and transforms outgoing responses to match AI SDK's contract format. Uses a schema-based validation layer that intercepts requests before they reach handler logic and normalizes responses before sending them to the client, preventing protocol mismatches and type errors.

Captures the execution context of Mastra agents (state, memory, tool results, conversation history) and marshals it into HTTP-serializable format for transmission to AI SDK clients. Handles serialization of non-JSON-native types (functions, buffers, circular references) and provides deserialization hooks on the client side to reconstruct agent state.

Enables multiple Mastra agents to be exposed through a single set of HTTP endpoints with routing logic that directs requests to the appropriate agent based on request parameters or headers. Implements agent selection, load balancing, and state isolation to ensure agents don't interfere with each other while sharing the same API surface.

Implements HTTP streaming (Server-Sent Events or chunked transfer encoding) to send agent execution updates in real-time as tasks progress, rather than waiting for complete execution. Buffers intermediate results (tool calls, reasoning steps, token generation) and flushes them to the client incrementally, enabling responsive UIs that show agent progress.

Provides data binding layer that connects Mastra backend state to AI SDK's pre-built UI components (chat interfaces, tool panels, memory visualizers) through a declarative mapping system. Automatically synchronizes state changes between backend and frontend, handles UI-triggered actions that invoke backend logic, and manages bidirectional data flow.

Implements centralized error handling that catches exceptions during agent execution and routes them to fallback handlers, error logging, or alternative agents based on error type and severity. Provides structured error responses that AI SDK UI can display gracefully, and allows recovery strategies like retry with backoff or escalation to human handlers.

Provides authentication and authorization layer that validates incoming requests to agent endpoints using API keys, JWT tokens, or other credential schemes, and enforces fine-grained access control based on user identity, agent type, or operation. Integrates with Mastra's identity system and allows custom authorization rules per endpoint.

Implements rate limiting and quota enforcement at the agent level, allowing different rate limits for different agents or users. Tracks usage metrics (requests per minute, tokens consumed, execution time) and enforces limits through token bucket or sliding window algorithms, returning appropriate HTTP 429 responses when limits are exceeded.