"A server for finding information about antigravity technology and concepts" matching MCP servers:

Enables agents to search and retrieve past workspace conversations, dialogue transcripts, and markdown artifacts through local BM25 retrieval, providing cross-conversation architectural recall with low-latency, offline operation.

Enables Google Antigravity agents to persist, retrieve, and evolve cross-session cognitive memories through native tools and skills, backed by lifecycle hooks and resilient two-phase commit state tracking.

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

An MCP server that implements Retrieval-Augmented Generation to efficiently retrieve and process important information from various sources, providing accurate and contextually relevant responses.

Enables intelligent ingestion and querying of PDF, Markdown, and text files using hybrid search that combines keyword matching and semantic embeddings with citations.

MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.

A proof of concept MCP server for Apache OFBiz

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

Enables asking questions and performing semantic searches against an Inkeep knowledge base. Deployable to Vercel with Next.js.

Provides AI assistants with access to 102 curated UK Government technology standards, enabling context-aware recommendations for accessibility, APIs, security, cloud strategy, and more.

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.

Enables AI agents to maintain persistent, searchable two-layer memory with 37 tools, hybrid search, knowledge graphs, and enterprise features like authentication and backups.

Enables scoped project discovery, deterministic rule and profile management, and durable automation with trigger/pause/resume/cancel and audit history for approved project contexts.

DocPull v6 is a local-first MCP server that turns public web sources into cited, versioned context packs for AI agents, RAG systems, and developer workflows. It can fetch and sync public static and server-rendered sources such as changelogs, standards, API references, OpenAPI specs, feeds, repo/package metadata, papers, filings, pricing pages, blogs, and other web sources.

Enables AI agents to drive Google NotebookLM notebooks as a deep-research workspace: ingesting local PDFs and YouTube videos, cross-checking sources for contradictions, identifying knowledge gaps, generating audio overviews, and exporting Markdown dossiers with BibTeX and APA bibliographies. It operates over the Model Context Protocol inside Google Antigravity IDE, with browser-session authentication handled automatically.

Enables querying PDF documents using natural language with grounded answers and source citations via a local RAG pipeline.

A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.

Enables document-based question answering using OpenAI's GPT-4 with semantic search and embeddings. Upload PDF, TXT, or Markdown files and get answers strictly based on document content with source attribution and confidence scores.

WordPress plugin that runs an MCP server on your own site: search and read published posts and pages, look up WooCommerce products, describe the site as schema.org types and query site figures, with drafts only when the site enables them. Signed-in access by default; anonymous access and OAuth are optional and off.

Gives Google Antigravity persistent memory by automatically recalling profile and project context before model calls and saving new conversation turns at turn boundaries. Exposes MCP tools to add, search, list, profile, and forget memories, with privacy filtering and per-repository scoping.

This MCP server provides a cost-optimized personal-knowledge brain, enabling AI agents to query imported documents via hybrid search and synthesis at minimal monthly spend.

Turns any static website into an MCP-searchable knowledge base by deploying a Cloudflare Worker that provides full-text search tools, enabling AI assistants to search and retrieve content from your site.

A multi-tool AI assistant system that uses Model Context Protocol to connect language models with various tools, including math calculations and weather information.

A local-first RAG system that indexes personal documents and enables querying them via an MCP tool, keeping data private with local embeddings.

Enables users to ingest PDF/DOCX/TXT/MD documents and ask natural language questions about them, using local embeddings and Groq-powered retrieval-augmented generation.

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.

Hebbian learning MCP server with neural memory graphs, eligibility traces, and three-factor reward signals. Associative memory that strengthens through use.

A TypeScript-based server to interact with ArangoDB using the Model Context Protocol, enabling database operations and integration with tools like Claude and VSCode extensions for streamlined data management.

An MCP server that exposes unified tools for HTTP requests, web search and fetching, weather/time/currency, file and SQLite sandboxes, GitHub, email, calendars, and a self-learning SQLite FTS5 knowledge base. It supports stdio, SSE, and streamable-HTTP transports with Bearer-token auth and SSRF protection so AstrBot agents can call these capabilities directly.