"Exploring the term 'make' and related resources" matching MCP servers:

A persistent, self-organizing memory MCP server for AI assistants, using semantic search, knowledge graphs, and reinforcement learning to automatically manage and retrieve memories.

A persistent, human-like memory system for AI companions in LM Studio, using SQLite and ChromaDB for hybrid storage, enabling seamless recall across sessions and models.

An MCP server that manages your conversation context automatically, pruning dead branches and keeping an audit trail of every cut.

Provides persistent long-term memory for AI agents with semantic search and activation-based decay. Enables AI systems to remember across sessions through layered memory architecture and automatic context-aware retrieval.

Your coding agent remembers how it solved past tasks and reuses it next time: trigger, steps, outcome, lessons. Hooks recall the right skill before a task; skills strengthen with confirmed use and unused ones decay. Local SQLite, no API key, nothing leaves your machine. 9 MCP tools, works with Claude Code, Codex and Cursor. Agent-written memory stays untrusted until you approve it.

Model-agnostic, agent-ready Obsidian MCP server with RBAC, SLSA provenance, and native search. 163 tools across 31 domains, multi-vault, pluggable embeddings.

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.

A local-first personal archive with a read-only MCP gateway that preserves files and AI conversations, derives evidence-linked memory candidates using local models, and enables bounded context retrieval for questions.

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.

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.

Canonical vocabulary server for autonomous business design. Exposes the Arco Lexicon as seven MCP tools: term lookup, related terms, alignment verification, citation formatting, source retrieval, term listing, and term suggestion. No authentication required. Streamable HTTP transport.

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.

Local-first MCP server that enables multiple Claude agents to coordinate through a shared message bus with SQLite persistence and real-time clock anchoring.

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.

Engram is a local-first memory server that lets AI agents remember things across sessions with zero cloud dependencies.

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

Local long-term memory shared by every AI coding assistant on one machine: a single SQLite file with FTS5 search and optional multilingual semantic search, no daemon and no cloud.