Overview

The Ldoce MCP Server is a lightweight Node.js and TypeScript service that bridges the Longman Dictionary of Contemporary English (LDOCE) with AI assistants through the Model Context Protocol. By scraping and normalizing dictionary entries into a consistent JSON schema, it enables agents such as Claude to retrieve authoritative lexical data on demand without hard‑coding dictionary logic or relying on external APIs that may impose rate limits.

Problem Solved

Most AI assistants lack built‑in access to specialized linguistic resources. Developers who want their agents to provide precise definitions, pronunciation guides, or usage examples must either embed large static datasets—which can become outdated—or depend on third‑party dictionary APIs that may charge per request or restrict usage. The Ldoce MCP Server eliminates these hurdles by providing an on‑premises, open‑source endpoint that mirrors the structure of LDOCE’s online pages. It delivers up‑to‑date information directly from the source, ensuring that agents can answer vocabulary queries with confidence and without external dependencies.

Core Functionality

When an MCP client sends a request containing a target word, the server constructs a URL in the form . It then performs an HTTP GET request, parses the returned HTML with Cheerio, and extracts key sections:

• Introduction & Related Topics – contextual background and thematic links.
• Entries (Verb/Noun) – phonetic transcriptions, part‑of‑speech tags, definitions, example sentences.
• Corpus Examples – real‑world usage snippets from authentic texts.
• Word Origin – etymology and historical notes.

All extracted data are assembled into a clean JSON object that adheres to the MCP schema, making it immediately consumable by any MCP‑compliant client.

Key Features & Advantages

• Zero External Dependencies – the server runs locally, so there are no API keys or billing concerns.
• TypeScript Robustness – static typing reduces runtime errors and improves developer ergonomics.
• MCP SDK Integration – exposes a single tool endpoint that can be invoked from any MCP client, such as Claude Desktop or custom agents.
• Extensible Architecture – the parsing logic is modular, allowing future extensions to other dictionary services or additional data fields.
• Compliance with MCP Standards – ensures seamless interoperability across the growing ecosystem of AI assistants and tooling.

Use Cases

• Educational Platforms – embed accurate, up‑to‑date word explanations into language learning apps.
• Chatbot Enhancement – let conversational agents offer detailed definitions and usage examples on the fly.
• Content Creation Tools – writers can query word nuances directly from their editor or IDE.
• Research Assistants – linguists and lexicographers can programmatically fetch corpus evidence for analysis.

By delivering structured dictionary data through a simple MCP interface, the Ldoce MCP Server empowers developers to enrich AI workflows with reliable lexical knowledge, all while keeping control over performance and privacy.