Connector SDK

The core library includes pre-built client implementations for standard protocols like REST, gRPC, and GraphQL. These handlers manage the low-level network communication, serialization/deserialization of data (e.g., JSON, Protocol Buffers), connection pooling, and HTTP/2 streaming. They abstract away protocol-specific complexities, allowing developers to focus on business logic.

This component provides secure abstractions for various API authentication flows. It includes:

• Credential vaults for storing API keys, OAuth tokens, and certificates.
• Built-in handlers for OAuth 2.0, API key injection, and mutual TLS (mTLS).
• Token refresh logic to automatically manage session lifecycles.
• Integration with enterprise secret management systems, ensuring credentials are never exposed in application code.

This subsystem ingests and utilizes formal API specifications to enable type-safe tool calling. Key functions include:

• Parsing OpenAPI (Swagger) or AsyncAPI specifications.
• Generating internal data models and function signatures from the schema.
• Runtime validation of request parameters and response payloads against the defined schema using tools like JSON Schema or Pydantic.
• This ensures the AI agent constructs syntactically correct and semantically valid API calls.

To ensure robust operation in production, the SDK implements standard resilience patterns:

• Automatic retry logic with configurable exponential backoff and jitter.
• Circuit breaker implementation to stop calling a failing service.
• Timeout and deadline management.
• Structured error classification (e.g., network errors, 4xx/5xx HTTP statuses, quota limits) and provides actionable error context to the calling agent for recursive error correction.

Built-in instrumentation provides visibility into connector performance and behavior for agentic observability. This includes:

• Audit logging of all tool invocations, parameters (sanitized), and outcomes.
• Distributed tracing spans for tracking calls across services.
• Metrics for latency, success/error rates, and throughput.
• This data is essential for debugging, compliance, and optimizing orchestration layer design.

A mechanism for dynamically exposing the connector's capabilities to the AI agent runtime. This involves:

• A registration API that advertises available functions, their descriptions, and parameter schemas.
• Compatibility with frameworks like the Model Context Protocol (MCP) for standardized tool discovery.
• Permission and scope management hooks to declare what actions the connector can perform.
• This turns the connector into a discoverable "tool" the agent can reason about and invoke.

A software component that translates requests and responses between different API protocols or data formats. While a Connector SDK provides the tools to build such adapters, the adapter itself is the runtime component that enables interoperability between disparate systems.

• Key Function: Protocol/format translation (e.g., REST to gRPC, XML to JSON).
• Relationship to SDK: An adapter is a common output artifact built using a Connector SDK.

A vendor-neutral, open standard (formerly Swagger) for describing RESTful APIs using JSON or YAML. A Connector SDK often uses OpenAPI specs as a primary input to automatically generate client code, documentation, and validation logic.

• Core Use: Machine-readable API description for discovery and integration.
• SDK Integration: Enables code generation features within the SDK, reducing manual boilerplate.

Google's language-neutral, platform-neutral mechanism for serializing structured data. It is the default interface definition language (IDL) for gRPC. A Connector SDK for gRPC services will heavily utilize Protobuf .proto files.

• Key Feature: Efficient binary serialization and strongly-typed contracts.
• SDK Role: The SDK's code generation tools parse .proto files to produce type-safe client stubs.

A software library that facilitates communication with a GraphQL server. A Connector SDK for GraphQL would provide utilities for query construction, variable binding, network transport, and response caching, abstracting the raw HTTP details.

• Core Capabilities: Manages query documents, network layers, and normalized caches.
• SDK Value: Provides a consistent, high-level abstraction over the GraphQL protocol for developers.

A resilience design pattern that detects failures and prevents an application from repeatedly attempting an operation that is likely to fail. A robust Connector SDK should integrate or facilitate this pattern for the clients it generates.

• Purpose: Prevents cascading failures and allows downstream services time to recover.
• SDK Implementation: SDKs may provide configurable circuit breaker implementations as part of their client libraries.

A software library that implements a database-specific protocol, allowing an application to connect to and query a DBMS (e.g., PostgreSQL, MySQL). A Connector SDK for databases builds upon or abstracts these low-level drivers.

• Low-Level Role: Handles wire protocol, connection lifecycle, and basic data type mapping.
• SDK Abstraction: The SDK adds higher-level features like connection pooling, ORM integrations, and query builders on top of the raw driver.