"Exploring Computer Usage" matching MCP servers:

Connects AI assistants to Tacit building digital twins to query buildings, equipment, sensors, and zones using natural language. It provides tools for exploring Brick-compliant knowledge graphs, fetching historical sensor data, and accessing site documents.

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.

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

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

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

A read-only MCP server for exploring and analyzing a Secoda data catalog, enabling AI chat, semantic search, glossary browsing, and data lineage tracing.

Enables Claude Code to interact with Obsidian vaults by providing tools for multi-term searching, reading notes, and exploring tag-based relationships. It allows users to query, analyze, and manage their personal knowledge base directly through natural language.

Search your data exports from Google, Telegram, Spotify, and Instagram in one place. Everything runs on your own computer. Hybrid search and MCP, built in .NET 10

Provides intelligent context management for AI development sessions, allowing users to track token usage, manage conversation context, and seamlessly restore context when reaching token limits.

Enables AI assistants to perform structured, step-by-step reasoning by breaking down complex problems into numbered thoughts, with support for revising previous steps and exploring alternative reasoning paths.

A Model Context Protocol (MCP) server that optimizes token usage by caching data during language model interactions, compatible with any language model and MCP client.

A persistent semantic memory system for LLMs with time-based decay, automatic memory capture, and spatial navigation tools for exploring knowledge graphs.

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.

MCP server providing context usage estimation, conversation compaction, and durable semantic memory via local embeddings and SQLite.

Basic Memory is a knowledge management system that allows you to build a persistent semantic graph from conversations with AI assistants. All knowledge is stored in standard Markdown files on your computer, giving you full control and ownership of your data. Integrates directly with Obsidan.md

Enables Claude Code to query codebase knowledge graphs directly, reducing token usage 5x–71x by reading a compact graph.json instead of raw files.

An HTTP stream server for interacting with the Intuition knowledge graph, enabling users to query and manage data through tools like extracting triples, searching entities, retrieving account info, and exploring relationships.

Provides production-grade context compression for LLM agent conversations with Q-protective ranking, epistemic markers, and semantic store, reducing token usage while preserving equivalence.

MCP server for building and exploring OWL 2 ontologies using AI agents, with tools for axiom management, structural pattern matching, and persistent selections.

An MCP server that provides semantic search and vault operations for Obsidian notes, enabling agents to recall and manage notes with provenance and low token usage.