Peacock MCP Server

Overview

The Peacock MCP Server turns the popular Peacock VS Code extension into a first‑class AI data source. By exposing the extension’s official documentation through an MCP endpoint, Claude and other AI assistants can ask precise questions about Peacock’s features—such as theme management, color palettes, and API usage—and receive instant, context‑aware answers. This solves the common developer pain point of hunting through docs or GitHub issues for quick guidance, enabling a smoother workflow where code and documentation are co‑located in the same AI conversation.

At its core, the server implements a single tool, , which retrieves Peacock’s documentation from its GitHub repository and parses it into a searchable knowledge base. When a user submits a prompt, the tool returns a concise response that references the relevant sections of the docs. Because the data is pulled directly from the official source, the information remains up‑to‑date with each new release of Peacock. Developers can thus rely on accurate, version‑specific guidance without manually updating reference material.

Key capabilities include:

• Real‑time documentation lookup: Fetch the latest Peacock API details on demand.
• Contextual Q&A: Answer natural‑language queries about theme configuration, color picker usage, or extension settings.
• Easy integration: The MCP server is packaged as an NPM module and can be added to any VS Code workspace via the built‑in MCP installer or Docker, making it accessible from both local and cloud environments.
• Extensibility: The tool’s design allows additional commands to be added in the future, such as querying release notes or providing code snippets that demonstrate Peacock usage.

Typical use cases include:

• Rapid onboarding: New team members can ask “How do I set a custom color palette in Peacock?” and receive an instant, step‑by‑step answer without leaving the editor.
• Debugging assistance: While troubleshooting theme conflicts, a developer can query “Why is my Peacock palette not applying?” and get documentation‑backed explanations.
• Documentation generation: AI assistants can pull Peacock API references into larger project docs or README files automatically.

By integrating seamlessly with existing AI workflows—whether through Claude Desktop, VS Code’s MCP client, or any other compliant tool—the Peacock MCP Server demonstrates how an external extension can be exposed as a dynamic knowledge source. Its unique advantage lies in providing authoritative, up‑to‑date documentation directly within the AI’s conversational context, eliminating friction and reducing the time spent searching for answers.