"Understanding Terminal Applications and Uses" matching MCP servers:

Saves the user's exact words as immutable, SHA-256-hashed captures before anything else, then derives events, entities, context cards, and causal hypotheses — every fact traceable to its verbatim source. Local-first personal memory for Claude Code, Codex, and any MCP client.

Enables AI agents to maintain persistent, inspectable understanding through typed, revisable updates, and to coordinate multi-agent work via shared graph-based stigmergy.

An agent-capable MCP server with terminal access, filesystem control, and persistent memory. It includes sandboxing, access control, activity logging, and a file-backed memory store for context across conversations.

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.

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.

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.

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.

Records your terminal sessions per command (PTY + OSC 133) into local SQLite, so AI agents can search, retrieve, and diff what commands actually printed. Secret redaction is applied by default to everything served over MCP.

MCP server providing persistent memory for AI applications, enabling Claude to store and recall memories with hybrid search and knowledge graph.

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.

MemOS (Memory Operating System) is a memory management operating system designed for AI applications. Its goal is: to enable your AI system to have long-term memory like a human, not only remembering what users have said but also actively invoking, updating, and scheduling these memories.

A self-contained, in-memory graph database for AI Agents. Provides semantic code understanding through the Model Context Protocol (MCP).

A Byzantine fault-tolerant MCP Memory server that uses SQLite write-ahead logging and FAISS hybrid vector search for deterministic, secure memory operations.

Provides brain-inspired long-term memory for MCP clients, enabling persistent user understanding across sessions with Chinese-optimized hybrid retrieval and evolving user profiles.

Builds a dynamic knowledge graph from your notes and uses LLM reasoning to discover blindspots, hidden cross-domain connections, track concept evolution, and spark creative inspiration.

Graph-based MCP server for persistent AI memory, session checkpointing, context compression, and cross-session context management for LLM applications.

MCP server for academic research with shared token bucket governance, evidence-based read depth, and archival inscription. Uses multiple sources with failover to avoid rate limits.

Enables AI applications to add, search, update, and delete long-term memories using the Mem0 Memory API, allowing agents to persistently remember user preferences, conversation history, and contextual information across sessions.