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

An MCP server that provides information about Utkarsh, including bio, skills, work experience, and portfolio projects, accessible via local stdio or remote HTTP with OAuth.

Enables MCP clients to run offline-first web search, fetch and extract web content, build a local hybrid-retrieval knowledge base, and use persistent session memory without external API keys. It also supports intent-aware federated search, semantic reranking, entity graph exploration, and source-cited deep-search answers using local models.

Enables AI agents to call tools through a security gateway that intercepts requests, enforces deterministic policy and risk checks, blocks or escalates high-risk actions for human approval, and keeps tool credentials and audit logs protected.

MCP server that gives AI agents access to current web information through web_search and fetch_url tools, using Tavily, Brave, and DuckDuckGo providers with automatic fallback.

Enables extracting explicitly stated contract metadata, clauses, and obligations from user-supplied contract text without storing or modifying the data.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

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

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

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.

Provides AI agents with persistent, searchable memory using semantic search, auto-linking, and categorization, with zero-config local setup or production-ready external providers.

Gives AI coding agents persistent, evolving knowledge about a codebase, enabling them to store and retrieve observations about architecture, conventions, gotchas, and recent work context.

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.

Provides persistent memory for AI assistants via MCP, enabling them to store and recall facts, preferences, and tasks across conversations using either local file storage or a cloud backend with semantic search.

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

MCP server for persistent, semantic memory across AI sessions; store context, decisions, and learnings and recall them with natural language search.

Persistent encrypted memory for AI agents. E2E encrypted private vaults, shared knowledge commons, topic channels, and agent-to-agent DMs. 23 MCP tools, free, no API key needed.

Provides persistent memory for AgentChat agents with swim-lane summarization and self-evolving persona, enabling context management and persona mining across conversations.

An MCP server that provides AI assistants with persistent, semantic memory using Turso for storage and OpenAI for vector search. It enables natural language operations to store, retrieve, and refine information with automatic duplicate detection and quality validation.

Personal memory MCP server for Claude Code with an Obsidian-style graph. Enables persistent, queryable memories across sessions using Markdown files with bidirectional wiki-links and a D3.js force-directed graph UI.

A fully local persistent memory layer for LLM coding agents (Claude Code, Codex, Gemini CLI, OpenCode). A shell wrapper intercepts tool invocations, fires hooks on every tool call, then runs a 3-layer pipeline (extract → compress to ≤500-token digest → merge into project memory doc) at session end. The next session gets prior context injected automatically.

An MCP server for persistent session context, user preferences, project conventions, and indexed state, with features like full-text search, task management, and a web dashboard.

Persists AI's cognitive fragments as a knowledge graph within each project directory, enabling project-level memory isolation and sharing via Git.

Enables AI agents to maintain and sync long-term memory and reusable skills across devices using local folder sync, with support for multiple agents and optional semantic recall.

Local-first MCP server for long-term memory of dev sessions. It indexes session metadata with embeddings in Postgres/pgvector, enables semantic search over past sessions, and resolves only relevant session files for context.

A local stdio MCP server that exposes a shared brain (read/search/write) over ~/.claude/memory, allowing memories written in any agent to be readable and searchable across all three (Claude Code, Cursor, Codex). It provides tools like memory_search, memory_read, memory_write, etc., with no external services.

A fully-local AI memory system that saves notes, code, and terminal output to a vector database via Ollama and LanceDB, enabling context retrieval from terminal, API calls, or inside Claude Code.

Shared, live team memory for Claude — a remote MCP server on Cloudflare Workers + D1.

A local, persistent memory system for AI coding assistants that stores decisions, patterns, and session context via MCP tools. It enables cross-session memory management using SQLite and optional vector search without external dependencies or cloud storage.

Provides AI assistants with a standardized interface to interact with the Todo for AI task management system. It enables users to retrieve project tasks, create new entries, and submit completion feedback through natural language.

Provides curated long-term memory for Codex CLI via MCP, with Markdown-based storage, deduplication, and decay-based forgetting.

Enables personal cross-tool memory by exposing a searchable episodic archive of AI sessions and a curated, high-trust semantic facts layer through MCP tools and resources.

Provides a persistent memory layer for Stellar and Soroban projects, scanning repositories to create a knowledge graph of contracts, storage, and on-chain state. Exposes this memory to AI agents via MCP, enabling project overview, search, and context recovery.

Memory Bank Server provides a set of tools and resources for AI assistants to interact with Memory Banks. Memory Banks are structured repositories of information that help maintain context and track progress across multiple sessions.

A local-first MCP server for persistent memory with vector search, metadata filtering, fact tracking, and graceful degradation when dependencies fail.

Enables project-scoped persistent linked memory for OpenCode V2, providing nine MCP tools for recall, update, pin, link, and read operations on notes within isolated projects.

A lightweight MCP server that gives Claude Code Channels on Telegram persistent memory by storing facts, conversation logs, and session summaries in Supabase.

Provides Claude with a persistent, auditable memory stored as markdown and YAML files in a private GitHub repo. Enables reading, appending, organizing, and messaging between agent conversations through MCP tools.

Enables AI assistants to have persistent, self-hosted memory across sessions and devices, storing context in a SQLite database you control.

A persistent, trust-scored project memory for AI coding agents, backed by PostgreSQL + pgvector, providing durable memory of architecture decisions, bug patterns, and coding conventions.

Gives any MCP-capable AI agent long-term memory from a self-hosted Obsidian vault, exposing tools to read, search, list and write markdown notes over MCP or a REST API with keyword plus semantic search. Agent writes are confined to a drafts inbox so they never overwrite your own notes.