#memory

Mirix is a multi-agent personal assistant designed to track on-screen activities and answer user questions intelligently. By capturing real-time visual data and consolidating it into structured memories, Mirix transforms raw inputs into a rich knowledge base that adapts to your digital experiences.

OpenCode plugin for Memoir: git-versioned, taxonomy-structured memory for coding agents.

Biologically-inspired memory for AI agents. Decay, retrieval strengthening, consolidation. Zero dependencies.

Universal memory runtime for AI agents

One config for every AI coding agent — cross-tool config + a cognitive substrate (memory, blast-radius, guardrails) for Claude Code, Codex, Cursor, Gemini, Aider, and more.

Hermes-style persistent memory and learning loop for Pi coding agent

Persistent memory extension for pi with daily logs, scratchpad, and optional qmd‑powered semantic search.

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Shared, persistent memory for AI assistants, built on the Zettelkasten method

A cognition aware database engine for AI agent memory. Purpose built in Rust with WAL, HNSW, knowledge graphs, and speculative context pre assembly. Not a wrapper, a ground up storage engine that thinks.

Persistent memory for AI agents

Identity, memory, and soul for AI agents. Runs standalone or as part of a TPS office.

A trait + derive to recursively compute / print the memory usage of a data structure.

Full AI context and content layer for coding agents over one MCP server — tree-sitter code-map, document RAG, shared memory, multi-agent comms, web crawl, git history + blame. 300+ languages, 10+ agent harnesses, pure Rust.

A memory efficient string type that can store up to 24* bytes on the stack

Unbounded context. Memory that manages itself. One session, for life. The hippocampus for coding agents, part of CortexKit.

Persistent semantic memory for AI agents — 100% local on Apple Silicon (MLX) or Linux/Ubuntu (CPU). Markdown source of truth, sqlite-vec + BM25 hybrid search, a codegraph-backed knowledge graph, MCP server + CLI. No cloud, no keys.

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Context engineering for AI agents. ~80% fewer tokens. Fix tool overload. Skills and memory with in-process BM25 and semantic retrieval. Progressive Disclosure. No vector DB.

⚡ A fast, type-safe, and feature-rich caching library for modern applications.

AI partners for every person: multi-user, multi-agent memory, trusted tools, schedules, sandboxed workspaces, and chat.

Self-improving agents, governed. Areev is the substrate for adaptive agents — agents that get better from their own history, under human authority, in steps you can inspect, undo, and re-measure.

Manifest-driven 21-stage agent pipeline for Python — 5 LLM backends (Anthropic / OpenAI / Google / vLLM / Claude Code CLI), tools, skills, memory, sandboxed CLI runs, MCP. The engine behind Geny. Apache-2.0.

OpenCode plugin that gives coding agents persistent memory using local vector database

Detect and fix struct field alignment to reduce memory usage in Go programs

Reflective memory for agents

Multi-agent code review mesh — orchestrates AI agents from multiple providers to review code in parallel, cross-review each other's findings, and build accuracy profiles over time. Agents that catch real bugs get picked more often. Agents that hallucinate get deprioritized. MCP server for Claude Code, Cursor, and other IDEs.

Persistent memory & code intelligence server for AI coding agents. Deploy on VPS for shared memory across machines. Hybrid search (BM25 + pgvector), knowledge graph, impact analysis. 14 MCP tools. Works with Claude Code, OpenCode, Cursor, and any MCP client.

Agentic AI memory with Ebbinghaus forgetting curve decay. +16pp better recall than Mem0 on LoCoMo.