"A search engine for OECD statistics and data" matching MCP servers:

Provides AI assistants access to over 5,000 OECD economic and statistical datasets via the SDMX API for search, analysis, and comparison across 38 countries.

Enables searching documentation from GitHub repositories and web pages via MCP tools, with in-memory indexing and caching for fast retrieval.

A read-only MCP server that provides access to public statistics and publications from the Maldives Bureau of Statistics, enabling search, listing, and retrieval of reports, yearbook tables, census releases, and PDF attachments.

Provides AI-native access to Swiss Federal Statistical Office datasets through 9 tools for querying education, population, and cross-cantonal comparisons without authentication.

Enables MCP clients to perform intelligent web searches via Traylinx's Agentic Search API, returning text summaries and structured data like HTML, images, and news.

A Model Context Protocol server that provides web search capabilities using Google Custom Search API and webpage content extraction functionality.

Exposes self-owned AI agent plugins as tools to Claude Code via a stdio MCP server, allowing Claude to call system info, calculator, or scribe transcriber directly.

Enables grounded, dated research from a curated AI-knowledge repository, offering free BM25 retrieval and a research loop that combines the knowledge base, curated sources, and the open web with tiered citations.

attendance-engine-mcp is a Model Context Protocol server that gives AI agents deterministic, fixture-backed tools for workforce attendance and wage-and-hour compliance. Built on @attendance-engine/core — a pure-function, zero-deps, 100%-covered TypeScript engine — it lets Claude, Cursor, Windsurf, or any MCP host correctly answer the questions HR/payroll teams actually ask: did this person clock i

Provides OECD statistical data (employment, wages, etc.) through SDMX API, supporting Korean-language queries. Enables listing indicators, retrieving stats, trends, comparisons, and rankings among OECD countries.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Enables MCP clients like Claude to query Chinese A-share market data, including K-line charts with forward/backward adjustment, limit-up and limit-down pools, per-stock fund flows, index quotes, and stock news, with automatic symbol normalization and retry handling for throttled data sources.

MCP server (stdio, official Python SDK) exposing a single tool: quantity_execute. Performs dimensional calculation and unit conversion with evidence. Solves silent unit errors in LLM agent chains: 20 m/s × 3 h returns 216 km.

Provides A-share (Chinese stock market) quantitative analysis through tools for stock screening, northbound capital flow tracking, dragon-tiger list analysis, margin trading, sector analysis, technical indicators, IPO info, and limit-up/down statistics using akshare data.

MCP server for answering questions about official statistics from a single publication URL, with tools to check query scope, retrieve overview, text, data files, and search.

Enables programming agents to capture errors and conversation signals, reflect on root causes, consolidate reusable skills, and retrieve relevant context for future tasks, providing a self-learning memory loop.

The only MCP server providing structured Chinese fashion supply chain intelligence for AI platforms. No equivalent data source exists in the MCP ecosystem. Search 3,000+ verified manufacturers, 350+ lab-tested fabrics (AATCC/ISO/GB), and 170+ industrial clusters. Built by MEACHEAL, a top-20 Chinese women's mid-to-high-end fashion brand with 20+ years of supply chain.

Provides AI agents with tools for structuring and auditing cold outreach messages, building follow-up sequences, handling replies, and detecting red flags.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

Eyes for AI coding agents: deterministic MCP server that tells the LLM which CSS rule wins, in which file, on which line — and why. Cascade verdicts, blast radius, interaction timelines, pixel-perfect audits.