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JSer.info MCP Server

MCP Server

Centralized API for JSer.info data and search

Active(70)
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Updated Jul 31, 2025

About

Provides Model Context Protocol endpoints to query, search, and retrieve JSer.info items, posts, product names, and weekly archives via a single MCP server.

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

Overview

The @jser/mcp server brings the rich, curated content of JSer.info into AI‑driven workflows through the Model Context Protocol. It solves a common pain point for developers who want to tap into up‑to‑date JavaScript and web‑development insights without building their own data pipelines. By exposing a consistent set of tools—search, lookup, and aggregation functions—this MCP allows Claude or any other compliant assistant to retrieve contextual information about items, posts, and weekly archives directly from JSer’s well‑structured dataset.

For developers, the server is a ready‑made bridge between an AI assistant and a high‑quality knowledge base. Instead of writing custom API clients or scraping the site, they can simply add the MCP to VS Code (or any other supported environment) and call tools such as or . The assistant can then answer questions like “Show me the latest JavaScript libraries tagged React” or “What was discussed in JSer week 123?” with authoritative data from the source, all while keeping latency low thanks to built‑in caching that refreshes every minute.

Key capabilities include:

  • Full‑text search over items and posts with keyword OR logic, pagination, and sorting by relevance or date.
  • Product lookup that extracts a product name from any URL, along with release‑note metadata when available.
  • Weekly aggregation tools that return all items or posts for a specific week, a range of weeks, or the week containing a given item.
  • Direct item retrieval by URL for instant access to title, description, tags, and related links.

Real‑world use cases span automated knowledge bases, educational chatbots, and internal tooling. For example, a team could build an AI assistant that surfaces the latest library announcements during stand‑ups, or a documentation generator that pulls JSer posts into release notes. Because the MCP follows the official Model Context Protocol, it integrates seamlessly with any client that supports MCP, ensuring portability across IDEs, chat platforms, and custom applications.

In summary, @jser/mcp delivers a lightweight, cache‑efficient, and richly featured interface to JSer.info’s curated JavaScript ecosystem. It empowers developers to embed up‑to‑date, searchable knowledge into AI workflows without the overhead of custom data ingestion or maintenance.