@elementor/angie-sdk
MCP ServerFreeTypeScript SDK for Angie AI assistant
Capabilities6 decomposed
model context protocol (mcp) server implementation for angie ai
Medium confidenceImplements the Model Context Protocol specification as a TypeScript SDK, enabling bidirectional communication between client applications and the Angie AI assistant through standardized message schemas. The SDK handles protocol negotiation, request/response routing, and capability advertisement using MCP's resource and tool definition patterns, allowing clients to expose capabilities to Angie while receiving AI-driven instructions in return.
Purpose-built TypeScript SDK specifically designed for Angie AI's MCP implementation, providing first-party abstractions over the raw protocol rather than generic MCP libraries, with Elementor ecosystem integration patterns baked in
Tighter integration with Angie AI than generic MCP libraries, with Elementor-specific patterns and likely better documentation for the Angie use case, though less flexible for non-Angie MCP scenarios
tool capability registration and schema definition
Medium confidenceProvides TypeScript interfaces and builder patterns for declaring tools that Angie can invoke, including parameter schemas, return types, and execution handlers. The SDK likely uses JSON Schema or similar for parameter validation and type safety, allowing developers to define tools declaratively with automatic schema generation and validation before Angie receives the capability advertisement.
Likely provides TypeScript-first tool definition with automatic schema inference from type annotations, reducing boilerplate compared to manually writing JSON schemas, with Angie-specific execution context and error handling patterns
More ergonomic than raw MCP schema definition for TypeScript developers, with likely better IDE autocomplete and compile-time type checking than generic tool registration systems
resource exposure and context management
Medium confidenceEnables applications to expose resources (documents, pages, settings, etc.) to Angie through MCP's resource protocol, allowing Angie to read and reference application state without direct database access. The SDK handles resource URI schemes, content serialization, and likely implements caching or lazy-loading patterns to efficiently serve large resource collections to the AI without overwhelming context windows.
Provides MCP resource protocol implementation tailored for Elementor's page builder context, likely with built-in serialization for page elements, styles, and settings rather than generic document resources
More specialized for page builder data than generic MCP resource implementations, with likely better handling of hierarchical page/element structures and Elementor-specific metadata
async request-response handling with timeout and error management
Medium confidenceImplements MCP's asynchronous request-response pattern with built-in timeout handling, error serialization, and retry logic. The SDK manages the message queue, correlates requests with responses using message IDs, and provides structured error handling that converts application exceptions into MCP-compliant error responses, enabling robust communication even with unreliable or slow network conditions.
Likely provides Angie-specific timeout and retry defaults optimized for the Elementor page builder workflow, with error serialization patterns that preserve actionable context for Angie's decision-making
More opinionated about error handling and timeouts than generic MCP libraries, with Angie-specific defaults that reduce configuration burden for typical use cases
client initialization and connection management
Medium confidenceHandles the setup and lifecycle management of the MCP connection to Angie, including protocol version negotiation, capability advertisement, and graceful shutdown. The SDK likely provides a fluent builder API for configuration, manages the underlying transport (WebSocket, stdio, or HTTP), and handles reconnection logic for transient failures.
Provides Elementor-specific initialization patterns and likely includes sensible defaults for Angie's protocol version and capability requirements, reducing setup friction for plugin developers
Simpler initialization than generic MCP client libraries, with Angie-specific defaults and likely better documentation for the Elementor use case
typescript type definitions and ide support
Medium confidenceExports comprehensive TypeScript interfaces and type definitions for all MCP protocol messages, tool schemas, resource definitions, and SDK APIs, enabling full IDE autocomplete, compile-time type checking, and inline documentation. The SDK likely uses discriminated unions for message types and generic types for parameterized tool/resource definitions, providing strong type safety throughout the integration.
Provides first-party TypeScript definitions specifically for Angie's MCP implementation, likely with Elementor-specific types for page elements, styles, and settings that generic MCP libraries don't include
Better IDE support and type safety than generic MCP libraries or JavaScript-only implementations, with Angie-specific types that reduce the need for manual type casting
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
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Best For
- ✓Elementor plugin developers extending the Angie AI assistant
- ✓Teams building AI-native applications that need standardized tool integration
- ✓Developers migrating from REST-based AI integrations to protocol-based communication
- ✓Elementor plugin developers exposing page builder actions to Angie
- ✓Backend developers creating AI-orchestrated workflows with typed tool definitions
- ✓Teams needing runtime validation of AI-generated tool invocations
- ✓Elementor plugin developers exposing page and site data to Angie
- ✓SaaS applications providing AI assistants with read-only access to user data
Known Limitations
- ⚠TypeScript/JavaScript only — no native Python, Go, or Rust bindings provided
- ⚠Requires understanding of MCP specification and async message handling patterns
- ⚠Limited to Angie AI ecosystem — not a general-purpose MCP implementation for other AI systems
- ⚠No built-in persistence or state management — requires external storage for session context
- ⚠Schema generation may not support all TypeScript type patterns — complex union types or recursive schemas may require manual definition
- ⚠No built-in rate limiting or quota management for tool invocations
Requirements
Input / Output
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TypeScript SDK for Angie AI assistant
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