"A server for finding information about Artificial Intelligence (AI)" matching MCP servers:

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

Persistent memory for AI agents. Store, recall, and share knowledge across sessions with five MCP tools: remember, recall, context, forget, and share. Includes semantic search and agent/user/org scoping.

Enables AI agents to persist, recall, expand, trace, and inspect durable memories with provenance through MCP tools.

Obsidian Intelligence turns your vault into a Model Context Protocol server. Any MCP-enabled AI client (Claude Desktop, Claude Code, Cursor, OpenWebUI, Cline, Continue.dev, ChatGPT Desktop) can then search, analyze, and reason over your vault — without your notes ever leaving your machine.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

Enables users to ask questions about their Salesforce org in plain language, with answers grounded in offline metadata vault and read-only live org access.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

A personal monitoring and trend synthesis system that collects signals from multiple sources, processes them through LangChain/GigaChat, stores them in vector and knowledge graphs, and delivers insights via MCP to Codex/Claude projects with workspace isolation.

Enables Claude Desktop to query a local Zendesk Help Center knowledge graph for semantic search, article retrieval, content gap analysis, and editorial intelligence tasks.

5,000 years of military strategy, philosophy, and decision science — as AI-accessible tools.

Provides durable project context for coding agents, including project maps, session history, and explicit memories, all stored locally.

Provides AI coding agents with fast, deterministic access to code graphs, knowledge lifecycle state, and cross-document symbol links, enabling compact context retrieval and seamless session handoffs.

Provides LLMs with persistent memory and reusable skills via MCP, enabling semantic storage and retrieval of user preferences, project context, and step-by-step procedures across conversations.

Enables AI clients to record research-process artifacts (agents, sources, claims, uncertainty, disagreement, tool usage) and compile a hosted process X-Ray report to inspect what a polished final answer may hide.

Enables AI agents to log, evaluate, and ground consequential decisions against an organization's authority graph, creating a traceable audit trail for governance.

Persists Claude Code sessions to Notion as team memory, enabling queryable recall of decisions, work state, and project architecture.

A local-first MCP server that gives AI coding agents durable project memory, dependency graphs, and impact analysis to answer team knowledge and cross-file change questions before editing.

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.

Provides read-only Arknights intelligence over MCP, enabling structured queries about stages, enemies, operators, and modules with region tagging and evidence-backed analysis. It uses versioned SQLite snapshots and never fetches upstream data at query time.

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.

Provides a compressed knowledge graph of the NVIDIA AI developer stack for deterministic traversal, enabling agents to answer questions about dependencies and prerequisites with minimal tokens.

Gives agents a stable interface for durable memory, combining exact, lexical, semantic, and graph search results.

Provides a shared, persistent memory layer for AI assistants, letting them read and write to a local Obsidian vault through MCP with validation, secret rejection, and deduplication.

An MCP server for managing work logs, research results, and task checkpoints to enable seamless collaboration and state recovery between AI agents. It provides a persistent memory layer for tracking project history and resuming workflows across different sessions or tools.

A read-only MCP server that provides document awareness for agents by parsing local files into structured profiles, blocks, chunks, and search results, enabling agents to understand and cite document content without dealing with raw file formats.

A productivity coaching assistant designed for ADHD support that provides intelligent task management, goal tracking, and personalized recommendations. It utilizes a persistent memory system to learn user patterns and preferences, helping to reduce decision paralysis through actionable suggestions.

Manages .ai/ workspace folder, syncs assets with a cloud service, and generates environment-specific bootstrap files for AI context management.

Personal multi-LLM memory repository using Markdown as source of truth, SQLite FTS5 for retrieval, and MCP tools for search, context, and write proposals.

AI development assistant with 36 specialized tools for memory management, code analysis, project planning, and problem-solving through natural language interactions in Korean and English.

Enables AI assistants to search, create, and manage knowledge graphs in Aiqbee brains for architecture, portfolio, and digital strategy.