"Information about terminal commands or usage" matching MCP servers:

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.

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.

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.

An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.

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

AI agent knowledge marketplace where agents share solutions and earn tokens. Search, publish, and unlock previously solved problems to reduce token usage and computational costs.

Your AI forgets everything between sessions. Rekindle fixes that. For Claude Code users who lose time re-explaining project context every session.

A lightweight Notion MCP server that minimizes token usage by returning Markdown instead of raw JSON, enabling efficient read/write operations on Notion pages.

NocturnusAI sits between your agent and the LLM. It extracts facts, reasons about what's relevant, and returns only what changed optimizing your token usage, saving you costs.

Public, agent-searchable knowledge base about AI-native software development, served as an MCP server with tools to search, read, and list topics.

A local MCP server that maintains a persona profile (contact library) for AI assistants, allowing them to create, search, retrieve, supplement, and correct information about people mentioned in conversations via tools like search_profiles, get_profile, create_profile, update_profile, add_facts, update_fact, and delete_fact.

Enables MCP-compatible agents to answer questions about you by exposing your CV through a tool, resource, and prompt.

A personal knowledge hub MCP server that enables LLMs to query structured information about Akib Dabgar's skills, experience, projects, and goals using Dynamic Context Retrieval for efficient context usage.

MCP server for the Graphite Financial Knowledge Graph, enabling natural language queries about companies, supply chains, executives, regulations, and patents via MCP-compatible clients.

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.

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 AI agents to offload and recall working memory as indexed episodes with LLM-written digests, reducing token usage and preserving detail across sessions.

Exposes tools to ingest FigJam boards, retrieve context summaries, and answer free-form questions about the board content.

Local-first, code-aware engineering cognition for AI coding agents - persistent memory, contextual retrieval, and continuous cognition about your codebase.

MCP server for intelligent, use-adaptive Obsidian vault search. It uses Hebbian learning and graph centrality to rank files by usage and relevance.