"A simple test or quiz" matching MCP servers:

Enables persistent, auditable business operations state by storing knowledge, evidence, decisions, tasks, execution receipts, and review results in a local SQLite database, so different sessions can continue the same project.

Enables an LLM to act as a quiz master by generating and saving quiz questions, then issuing tests and recording results for long-term tracking and analysis. This lets users identify weak points and monitor progress over time.

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.

Read-only MCP access to the p-e relay store: an append-only corpus of provenance-bearing coordination records, with tools to fetch a record by id, list records and replies, and check existence. This image serves a snapshot frozen at build time; append_relay is listed but refused, and deposits to the live store require an HMAC-signed request.

An MCP server for managing contextual data as markdown files with metadata, enabling agents to save, retrieve, search, and delete contexts using simple CRUD operations.

Simple, fast, long-term memory for your AI chatbots, agents, and MCP tools. Give your LLM a persistent memory using a local SQLite file. No complex database servers, no heavy cloud setup, and zero C++ compilation errors. Works everywhere.

Free Industry 4.0 / IIoT tools, no API key or account: lint MQTT Sparkplug B topics, check a Unified Namespace (UNS) for naming and hierarchy problems, and run an industrial AI-readiness diagnostic for manufacturing digital transformation and smart-factory projects. Works in Claude Code, Codex and any MCP client.

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.

Author rules from policy docs, then decide: a Rete engine gives the verdict, an LLM explains why.

Gives every AI agent working in a repository a shared, persistent knowledge graph stored in a plain JSONL file, with each entity, relation, and observation tagged with the date and agent that added it. Provides tools and prompts for searching, editing, renaming, merging, cleaning up, and exporting that memory, and keeps it locked to the repository that owns it.

Enables persistent, project-scoped memory for OpenAI Codex Desktop and CLI on Windows, capturing prompts and responses through managed hooks, with federated recall across projects and optional local graph extraction.

Memory vaults on your own machine, one per life domain, retrieved with a local BM25 index fused with vector search, where the human decides which vaults a model may answer from. Requires the Mnemosyne OS desktop app running locally; it also reports what other coding agents on the same machine are doing.

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 hybrid memory architecture with a thin SQLite index and Markdown cold storage, enabling AI agents to write, query, link, and rebuild long-term memories via MCP tools, model-agnostic and zero third-party dependencies.

Local-first memory engine for AI-agent teams: private/team/project ACL, associative recall, and federated sync across nodes. One SQLite file, no LLM required.

A simple MCP server for tracking a home bar's inventory and cocktail recipes, with tools to manage shelf items and recipe details.

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.

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.

Enables personal knowledge management through Claude Desktop, allowing users to capture thoughts, connect ideas, and reflect on thinking changes via natural conversation.

Serves organizational context to MCP-capable AI agents from a local folder or GitHub repository, and lets agents propose changes that require human approval.

Provides a SQLite-backed MCP server that records agent memory as history, enabling explicit consolidation, source checks, revisions, narrative versions, and accountable forgetting.

Universal session & handoff layer for AI coding agents: shared task, decision, blocker and test state, checkpoints, and deterministic handoff between Claude Code, Codex, OpenCode, Cursor, Cline, pi and omp. Local SQLite, git-aware, 25 tools + 7 resources over stdio or streamable-http.

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

Enables Codex, ChatGPT, and Aside to share project work memory by reading private GitHub-backed checkpoints and searching or re-reading allowed local/SSD documents through read-only MCP tools.

MCP server for foldkit that exposes the 7-prime spine, 7 κ-bands, and 6 fold operations as native tools and resources in any MCP client.

Enables MCP clients to draw Chinese idioms, look up meanings and examples, search a built-in dictionary, and track learning progress and notes in local SQLite. Lets client AI explain idioms, quiz users, and update mastery status based on conversation.

A personal digital twin MCP server that manages professional context, including skills, experience, and project learnings. It allows AI assistants to retrieve and update user preferences and career interests across different development environments.

Provides AI coding agents with a local, Markdown-first shared memory, enabling them to record decisions, failures, progress, and handoffs and retrieve them across sessions via MCP tools.

Provides AI agents with a memory layer that stores, retrieves, and manages memories with biological properties like forgetting, reinforcement, and contradiction detection, using two simple tools.

A simple memory system that allows LLMs to store and retrieve information via the Model Context Protocol.

A lightweight, local-first MCP server and CLI that helps developers and AI coding agents store and retrieve lessons learned during development, using SQLite and context-aware filtering.

Enables MCP clients to search a Zotero library, read items, take notes, organize collections, and perform semantic search over PDFs.

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.

Local-first memory for AI coding agents using SQLite, enabling persistent recall of decisions, lessons, and project context without cloud or API keys.

A Model Context Protocol server that enables AI models to perform real-time internet and knowledge searches through Higress, enhancing model responses with up-to-date information from Google, Bing, Arxiv, and internal knowledge bases.

A multimodal local memory MCP server that lets AI agents search across text, PDFs, images, audio, and video using Gemini Embedding 2 and a local ChromaDB.

Enables querying a compressed knowledge graph of the NVIDIA AI developer stack, allowing users to traverse declared dependencies, prerequisites, and relationships across 20 domains via read-only MCP tools like query_ckg, get_prerequisites, and search_concepts.

Enables running OpenAI conversations through MCP with durable local sessions, persistent instructions, and safe request replay using caller-supplied request IDs. Supports inspecting, recovering, or abandoning unresolved requests and configuring session metadata without silently resetting context.

A lightweight MCP server that provides persistent knowledge graph storage for AI assistants, enabling memory across sessions through entity-relationship storage with JSON file persistence.

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.