Structured Data

A powerful Model Context Protocol (MCP) server that provides an all-in-one solution for public web access.

Can AI engines cite your site, and do they? Free 0–100 readiness score on an open GEO rubric, plus ask and weekly citation tracking via OpenAI, Perplexity, Gemini, Anthropic and OpenRouter with your own keys. Zero dependencies; CLI, GitHub Action and MCP server.

Claude Code skill for improving website AEO (AI Engine Optimization) and GEO (Generative Engine Optimization) scores — 16 foundational checks, 6 intelligence dimensions, framework-specific fixes

Conversion from Excel to structured JSON (tables, shapes, charts) for LLM/RAG pipelines, and autonomous Excel reading/writing by AI agents via CLI and MCP integration.

The World's Most Comprehensive, Authoritative, and Structured Open Source Data Source Knowledge Base

When the user wants to audit, review, or diagnose SEO issues on their site. Also use when the user mentions "SEO audit," "technical SEO," "why am I not ranking," "SEO issues," "on-page SEO," "meta tags review," "SEO health check," "my traffic dropped," "lost rankings," "not showing up in Google," "site isn't ranking," "Google update hit me," "page speed," "core web vitals," "crawl errors," "indexing issues," "stuck on page 2," "striking distance keywords," "title tag rewrite," "low CTR," "local SEO," "Google Business Profile," or "map pack." Use this even if the user just says something vague like "my SEO is bad" or "help with SEO" — start with an audit. For building pages at scale to target keywords, see programmatic-seo. For adding structured data, see schema. For AI search optimization, see ai-seo.

Fast, local-first web content extraction for LLMs. Scrape, crawl, extract structured data — all from Rust. CLI, REST API, and MCP server.

花叔开源的全球鸟类贴纸库 · AI-generated stickers for all 11,011 bird species in AviList v2026, CC BY 4.0, with names in 43 languages and structured data

Enable AI agents to work reliably - giving them secure access to structured data, tools to take action, and the context needed to make smart decisions.

LLM-Driven Extraction of Unstructured Data — Built for API Deployments & ETL Pipeline Workflows

AI Agent skills to access structured datasets for startup founders

AI can draw UI directly on the Figma canvas via JavaScript, and read existing designs back as structured data. Works with Claude Code, Cursor, VS Code, and Windsurf. No API KEY required.

The Context Layer for unstructured data: typed, versioned datasets over S3, GCS, Azure

Universal SEO skill for Claude Code. 26 sub-skills + 19 sub-agents covering technical SEO, E-E-A-T, schema, GEO/AEO, agent readiness (Lighthouse Agentic Browsing, WebMCP, llms.txt), backlinks, local SEO, e-commerce, international SEO, Google APIs, and PDF/Excel reporting. 9 optional extensions for live SEO data.

A curated collection of DESIGN.md rule systems and design tokens for vibe-coding agents to instantly generate production brand UIs.

Never stop coding. Free MIT AI gateway: one endpoint, 375 providers (150+ free), 1,400+ models Kimi, Claude, GPT, Gemini, GLM, DeepSeek, MiniMax. Works with Claude Code, Codex, Cursor, OpenCode, Cline & Copilot. Quota-aware auto-fallback, RTK+Caveman compression saves 15-95% tokens, MCP/A2A, Desktop/PWA. Built by 900+ contributors

Knowhere extracts, parses, and outputs structured chunks ready for AI Agents and RAG.

Memori is agent-native memory infrastructure. A LLM-agnostic layer that turns agent execution and conversation into structured, persistent state for production systems. Built for enterprise, Memori works with the data infrastructure you already run, no rip-and-replace, and deploys across managed cloud, single-tenant cloud, VPC, and on-premises.

Turn plain English queries into structured web data, featuring automated markdown extraction and full JavaScript rendering for dynamic websites.

Local code search combining BM25, vector similarity, and cross-encoder reranking. Parses 60+ languages with tree-sitter, runs entirely offline, and returns structured results with file paths, line ranges, and symbol metadata. Built in Rust.

Local code search combining BM25, vector similarity, and cross-encoder reranking. Parses 60+ languages with tree-sitter, runs entirely offline, and returns structured results with file paths, line ranges, and symbol metadata. Built in Rust.

An MCP server for public & prediction markets research. Ask natural-language questions and get structured, source-backed answers across SEC filings, earnings transcripts, company financials, stock & crypto market data, and prediction markets news & research. Built for investors, analysts, and researchers who need fast, cited intelligence.

A Claude Project skill system for disciplined, data-driven sports betting. One prompt → structured bet recommendation with EV%, unit sizing, and reasoning.

MCPSDK.dev(ToolSDK.ai)'s Awesome MCP Servers and Packages Registry and Database with Structured JSON configurations. Supports OAuth2.1, DCR...

An agentic extractor for messaging platforms. Noria receives messages & URLs via chat; scrapes web data to evaluate the content against custom scoring matrices (e.g., jobs, scholarships); and sends a structured summary with a calculated match score directly to the assigned messenger number.

Research pipelines as semantic execution units: each skill declares inputs/outputs, acceptance criteria, and guardrails. Evidence-first methodology prevents hollow writing through structured intermediate artifacts.

Intelligent Python system that extracts real estate property data as structured JSON using AI agents, Nebius Qwen LLM, and Bright Data MCP.