"Resources for Building a Website" matching MCP servers:

Enables AI agents to provide e-commerce customer service with product search, RAG-based FAQ answers, human handoff, and automated security auditing with a review workflow.

Provides versioned, structured memory for AI agents, allowing them to store facts, detect conflicts, and track knowledge history via a hosted SaaS platform. It enables efficient hierarchical information retrieval and semantic search while keeping token usage constant as memory scales.

An Operit-compatible adapter of the Exa MCP server, enabling web search, code search, and company research capabilities in AI assistants. It fixes MCP handshake compatibility issues, allowing tools like web_search_exa and web_fetch_exa to load and run reliably.

Stop paying for your agent to rediscover what other agents already figured out. Prior is a shared knowledge base where agents exchange proven solutions — one search can save 10 minutes of trial-and-error and thousands of tokens. Your Sonnet gets access to solutions that Opus spent 20 tool calls discovering. Search is free with feedback, and contributing earns credits.

Codebase intelligence and context engine for AI coding agents: search, symbol lookup, impact analysis, and context building via MCP.

Enables building a local, searchable knowledge base from YouTube videos, with research, transcript retrieval, and timestamped citations.

ake any website queryable by AI agents. Index a site then ask questions and get cited answers grounded in its content via RAG. Two tools: list_sites and ask_site.

Enables AI agents to scrape, crawl, clean, chunk, and index website content into Azure AI Search for full-text retrieval.

Give your AI agents access to 8,500+ community curated awesome lists with over 1 million curated resources.

Enables AI assistants to search a curated database of 200+ AI tool cards with pricing, platforms, use cases, and source links, so users can ask which tool to use for a task and get grounded recommendations.

Provides a read-only interface to audit and continue coding agent sessions by extracting plans, intents, and edit authorship from history across multiple agents (Claude, Codex, OpenCode, Antigravity, Pi) via MCP, CLI, and Python SDK.

A persistent, project-scoped memory layer for AI agents, supporting hybrid retrieval (vector, keyword, and tag matching) and sharing across different MCP clients like Claude Code, Qoder, or Cursor.

Persistent memory for AI agents as a single Go binary: hybrid recall, self-building knowledge graph, and a live TUI dashboard. Zero infra, offline-first — works with Claude Code, Cursor, Codex, OpenCode, and any MCP client.

Interact with WebScraping.AI API for web data extraction and scraping

Turn Any Website Into Clean Fit-Markdown for AI Extract clean, structured Markdown from any static or dynamic website at enterprise scale. Reduce token costs by 90% and feed pure signal into your RAG pipelines and AI agents.

Ingests pdf and epub documents for LLM-retrieval (RAG)

Enables AI agents to fetch one or many web pages concurrently and receive clean, LLM-ready Markdown with navigation, ads and boilerplate stripped away, plus extracted metadata such as title, description, author, Open Graph tags and canonical URL. It runs locally over stdio with no API key or account, requiring only a single command.

Provides a compiled knowledge substrate, extracting atomic claims from an append-only capture log and querying a bitemporal claim graph over MCP. Read-only by default, with opt-in writes for trusted sources.

Enables AI coding agents to intelligently index and search codebases with sub-20ms retrieval, 8x memory compression, and cross-encoder reranking via MCP stdio.

A remote MCP server providing a tool for searching and querying ATprotocol documentation, helping developers easily access information while building on the protocol.