"Information and Communications Technology (ICT)" matching MCP servers:

Enables AI assistants to access and update personalized context data, creating persistent memory between sessions.

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

Enables AI agents to store and retrieve project context, bugs, decisions, and session logs by reading and appending markdown files in a local Obsidian vault, without requiring any cloud services.

Enables Claude and ChatGPT to share a single study-progress database for interview prep, coursework, and spaced repetition, with per-user data isolation and server-side SM-2 scheduling for due reviews and study plans.

MCP server for Ultrathink: save and search your knowledge base from Claude Desktop, Claude Code, and any MCP client.

Enables researchers to turn property-history questions into reviewable evidence dossiers by gathering sources, tracing people and places, linking conclusions to supporting or opposing passages, and exporting portable backups.

Hosted MCP gateway to the RTP global commons of neighborhood practice and relational tech knowledge. AI builders can query 275+ recipes, frameworks, and methodology docs for community organizing.

An MCP server that provides AI tools with relational tech principles, patterns, and the Studio library to guide builders in creating community-centered tools using embedded design.

TheWeave is a markdown-native memory architecture for Claude and any MCP-aware agent. Your agent's memory lives as plain .md files you own: a 5-verb MCP core over the vault, query-driven PageRank retrieval, bi-temporal facts (valid_from / valid_until), and a persona-as-vault model. No database and no embeddings server. The files are the memory, inspectable in your editor and versionable in git.

Enables local MCP clients to list, read, write, and search notes in an Obsidian vault via an HTTP server running inside Obsidian.

AutoMem MCP provides persistent memory for AI assistants, enabling them to recall information across conversations and platforms with graph-vector retrieval.

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

Provides a shared knowledge base MCP server for coding agents to read and leave one-sentence lessons, tagged by technology stack, to avoid repeated mistakes across sessions.

Enables AI assistants to maintain persistent project context across sessions by storing and retrieving structured information in markdown files organized in a memory bank directory.

This MCP server provides persistent memory integration for chat applications by utilizing a local knowledge graph to remember user information across interactions.

Enables Claude to maintain persistent memory across conversations using a local knowledge graph with fuzzy search capabilities, allowing it to remember and recall information about users, relationships, and context.

A custom Memory MCP Server that acts as a cache for Infrastructure-as-Code information, allowing users to store, summarize, and manage notes with a custom URI scheme and simple resource handling.

A persistent memory implementation using a local knowledge graph that lets Claude remember information about users across conversations.

Provides a scalable knowledge graph implementation for Model Context Protocol using Elasticsearch, enabling AI models to store and query information with advanced search capabilities, memory-like behavior, and multi-zone architecture.

A memory server for Claude that stores and retrieves knowledge graph data in DuckDB, enhancing performance and query capabilities for conversations with persistent user information.

A Model Context Protocol server that provides knowledge graph-based persistent memory for LLMs, allowing them to store, retrieve, and reason about information across multiple conversations and sessions.

Enhances user interaction through a persistent memory system that remembers information across chats and learns from past errors by utilizing a local knowledge graph and lesson management.

Enables Codex agents to save, retrieve, and manage technology bookmarks as sourced, reviewable cards, with consent-based suggestions and trial planning.

Enables AI clients and agents to turn a new idea into a structured set of clarifying questions, technology options, upward design breakdowns, reverse reasoning, and risk assessments so users can steer top-level design decisions. It also supports saving insights and building a bidirectional design tree of concepts and their implementations.

An MCP server that enables AI models to retrieve information from Ragie's knowledge base through a simple 'retrieve' tool.

Enables querying and retrieving content from Confluence through CQL searches and page content fetching, allowing Claude to seamlessly access information stored in Confluence workspaces.

A Model Context Protocol server that enables AI assistants like Cursor to directly query and retrieve information from Dify knowledge bases through natural language.

A Model Context Protocol server that reduces token consumption by efficiently caching data between language model interactions, automatically storing and retrieving information to minimize redundant token usage.

Enables seamless integration between Claude and Dry smartspaces, turning conversations into persistent, structured data by creating memories and querying information.

Provides agents with durable, provenance-aware memory through tools for remembering, recalling, answering, and maintaining information, while structurally resisting injection and confabulation.

Enables Claude to add and search personal memories through the Nowledge Mem service. Allows users to store and retrieve contextual information across conversations.

Gives Claude Desktop, Cursor, Cline, and other MCP-compatible AI tools persistent memory, enabling them to store and recall information seamlessly across sessions.

Enables AI agents to search through Memex conversation history and local project files to retrieve specific commands, code snippets, and technology overviews. It utilizes smart context management and faceted filtering to provide relevant search results without causing context overload.

Persistent AI memory server with hybrid search and embedded sync. Enables AI agents to store, retrieve, and manage information across sessions with temporal knowledge graph support.

MCP server for querying the DodaOne governance framework, enabling users to retrieve governance information and evaluate proposed actions.

CLI + MCP server that bootstraps persistent project context for any AI agent, storing structured information using hierarchical dot notation and exposing it via MCP tools for session-over-session knowledge growth.

A persistent memory layer for AI tools that decouples personal data from AI's unstable memory, enabling you to mention information once and have it remembered forever across all conversations.

Enables MCP clients to remember user information, preferences, and behaviors across conversations using vector search technology. Built on Cloudflare infrastructure with persistent storage and semantic similarity matching.

Enables MCP clients to remember user preferences and behaviors across conversations using vector search technology.

MCP Memory is an MCP Server that gives MCP Clients the ability to remember information about users across conversations. It uses vector search technology to find relevant memories based on meaning, not just keywords.