"A search for information about memory" matching MCP servers:

Persistent memory system for AI agents that records episodic memories with care-weighting and emotional valence, and provides full-text search with temporal chaining and automatic consolidation.

Enables AI assistants to maintain a persistent, local memory using SQLite with ranked full-text search, German morphological matching, and two-axis filing, all without external services.

Embedded, local-first agent memory: facts extracted into a per-namespace SQLite file (vec0 + FTS5) with hybrid retrieval and point-in-time (time-travel) queries. ADD-only history over stdio — no server process, no cloud dependency.

A local MCP server that gives AI assistants persistent long-term memory using a biological neural architecture with cortex, synapses, and hippocampus.

Local-first personal memory for AI agents. Ships its own SQLite memory store, so it runs standalone: agents propose and recall confirmed memory, while only the human can confirm, from a separate CLI. Optionally uses the macOS Hive app for encrypted vaults. Also provides a shared board for coordinating several agents.

MCP server that exposes agent-memory-daemon to any MCP-compatible client — Kiro (CLI & IDE), Claude Desktop, Cursor, and others. The daemon does the thinking (consolidation + extraction); this server is a thin filesystem bridge so agents can read, append, and search memory through the Model Context Protocol.

Long-term memory for AI coding agents, stored as a tree of plain local files. Agents search it before answering and save what lasts; changed facts are kept as history and flagged as outdated.

Provides persistent local memory for any MCP-compatible AI agent, enabling agents to store, search, recall, forget, export, and manage preferences, rules, and facts with zero dependencies, no cloud, and no API keys.

A different approach from typical persistent-memory MCPs. Instead of a local SQLite + embeddings store, the memory lives as plain files in a .ai-memory/ directory you commit to your repo (facts.jsonl, decisions/\*.md, gotchas.md). Git is the sync layer — what one Claude/Cursor/Cline learns about a repo, the next session (or a teammate's agent) picks up automatically. 5 MCP tools: get_rep

MARM MCP provides persistent memory and structured session context beneath any AI tool, so your agents learn, remember, and collaborate across all your workflows.

Hand a project over — to your next session, to Cursor/Codex/Gemini, to your successor — with the reasons attached. Local-first memory MCP for coding agents: decisions re-injected before the agent acts, drift detection across every project you run. One SQLite file, nothing leaves your machine.

A stateless MCP server that gives coding agents a curated entry point to shared memory, orchestrating Hindsight (facts) and LightRAG (corpora) for automatic routing, URL ingestion, and consistency tooling.

Local-first persistent memory MCP: shared SQLite key/value store, searchable, TTL-aware and secret-safe.

A portable, self-hosted semantic memory layer for LLM agents, enabling them to search and add memories by meaning over the Model Context Protocol.

Two-layer memory for AI agents. Episodes compress into identity. The only MCP memory server with an immune system. Patterns earn permanence through evidence, false knowledge gets caught and demoted, and stale information fades — so your agent's memory gets smarter over time, not just bigger. Zero dependencies. 5 tools. Works with any MCP client.

Google Search Console for Claude and other MCP clients. Sign in with Google in one click, then ask about clicks, queries, rankings and indexing, export every GSC report as CSV (beyond the 1,000-row UI limit), inspect URLs, submit sitemaps and verify sites. Includes a local SEO dashboard. Free, open source, runs on your computer.

Provides AI agents with persistent, long-term memory via OKF-formatted markdown and SQLite indexing, enabling stateful storage, retrieval, and search across sessions.

Persistent memory and automatic git snapshots for Claude Code, capturing decisions, patterns, and architecture across sessions.

Persistent project memory for coding agents, kept in a local SQLite store with FTS5 search: search and list memories by topic, read one with its history, add a fact, show the store's statistics, and read or regenerate the PROGRESS.md handoff. Pure standard-library Python; no network.

AI memory server with 53 tools. Knowledge Graph, semantic search, session tracking, multi-agent support.

Provides a shared local memory MCP server so multiple coding agents can store, retrieve, and attribute memories across sessions. It enables agents to recall project knowledge and past fixes with provenance.

A persistent, project-scoped memory layer for AI coding agents, providing 39 tools for capturing, searching, deduplicating, relating, and maintaining memory records across long-running coding sessions.

Persistent long-term memory for MCP clients. Store and recall semantic facts, episodic events, and task state with vector-based relevance search. Write what matters, retrieve what's needed — memory that persists across sessions and agents, backed by a local SQLite store with optional embeddings for meaning-based lookup. Simple file-based storage, no external services required.

Cross-chain cryptocurrency swaps via Chainflip. Get quotes, execute swaps, and track progress. No API key required to get started.

An MCP server providing semantic vector search, dual memory engines, and Git version control for AI clients, enabling persistent memory with recall, forget, and rollback capabilities.

Enables AI assistants to remember and retrieve user information across conversations using vector search technology. Built on Cloudflare infrastructure with isolated user namespaces for secure, persistent memory storage.

Enables finding information online, reading web pages, finding images, capturing screenshots, and performing multi-source research with per-answer confidence.

Domain search that returns only .com names verified available to register, checked live against the Verisign RDAP registry, not AI guess lists.

Enables AI agents and their users to retrieve scored news sentiment, narratives, historical readings, and cited sources for Bitcoin, gold, and oil, with tamper-evident, time-stamped data for trading decisions.

Local memory for coding agents that can refuse, not only recall. A rule carrying a machine-checkable proof blocks the matching command before it runs, while prose-only rules can warn but never block.

Free multi-source search for AI agents with multi-source verification, token savings, and MCP native support.

Job search mechanics for an AI assistant: search Arbeitnow/Adzuna/JSearch, fetch a single job posting, render a CV to PDF, lint it against your own configurable anti-fabrication rules, and log the outcome to your application registry. Never auto-applies.

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 web search, web-page reading as Markdown, and llms.txt documentation retrieval for MCP clients. Runs locally with Node.js over stdio using @alkasima/alka-search-mcp. Searches DuckDuckGo, Mojeek, and Brave; default providers require no API key. Website and provider availability may vary.

A notes app that becomes your second brain. Open source, private, encrypted when you want it, and every file stays yours. Mac, Windows, Linux and self host!

Hosted memory for AI agents that learns from outcomes, with shared rooms. One key across Claude, Cursor & ChatGPT.

A public, source-linked notebook for AI agents and people. Search and read without a key; publish findings, questions, and corrections with permanent IDs and linked replies using an operator-controlled posting key.

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

An MCP server for integrating with the Brave Search API, and it supports HTTP proxying.

Use Codex as a subagent inside Claude Code: async dispatch into a long-lived codex app-server, results pushed back into the Claude session automatically, steer/interrupt mid-task, and Codex's built-in code review.