Gives AI coding agents persistent memory across sessions, capturing observations automatically and offering recall, session history, hybrid search, and a knowledge graph through skills, commands, and MCP tools.
Auto-invoked ships a router so the right skill fires automatically as you prompt. No remembering which skill to call.
Normal is the plain upstream plugin, installed as-is. You invoke its skills yourself.
Claude Code
The plugin> /plugin marketplace add rohitg00/agentmemory> /plugin install agentmemory@agentmemoryAuto-invocation> /plugin marketplace add flowy-sh/flowy-core> /plugin install flowy-core> /plugin install flowy-agentmemory
Codex
$ npx skills add rohitg00/agentmemory -a codex
Cursor
$ npx skills add rohitg00/agentmemory -a cursor
Gemini CLI
$ npx skills add rohitg00/agentmemory -a gemini-cli
GitHub Copilot
$ copilot plugin marketplace add rohitg00/agentmemory$ copilot plugin install agentmemory@agentmemory
OpenCode
$ npx skills add rohitg00/agentmemory -a opencode
Windsurf
$ npx skills add rohitg00/agentmemory -a windsurf
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The gist extends Karpathy's LLM Wiki pattern with confidence scoring, lifecycle, knowledge graphs, and hybrid search: agentmemory is the implementation.
Install • Quick Start • Benchmarks • vs Competitors • Agents • How It Works • MCP • Viewer • Config • API
AgentMemory captures coding sessions, makes decisions and fixes searchable, and lets your agents recall them later. Keep one memory store across tools, inspect what was saved, and choose how much context reaches the model.
Requirements:
node -v, npm -v, and npx -v).curl, a POSIX sh, and tar for automatic runtime setup.Start setup:
npx -y @agentmemory/agentmemory@latest
Choose your agents and either a provider or keyless mode. Setup writes the configuration, starts the memory server, and offers a global install for the agentmemory command. -y accepts the npm package prompt; @latest selects the current release. LLM-written observation compression is opt-in with a provider and AGENTMEMORY_AUTO_COMPRESS=true.
Keyless mode disables vector embeddings. memory_recall (the mem::search path) uses BM25, while memory_smart_search can also fuse structural graph matches when graph data already exists. For free on-device semantic recall, set EMBEDDING_PROVIDER=local in ~/.agentmemory/.env and restart. The first embedding request downloads Xenova/all-MiniLM-L6-v2; inference runs locally after that initial model download.
The API is at http://localhost:3111 and the live viewer at http://localhost:3113. Both bind to loopback by default. Configuration lives in ~/.agentmemory/.env; see data storage for memory locations and separate instances.
Then prove recall works and give your agent its skills:
npx -y @agentmemory/agentmemory@latest demo # seed sample sessions + exercise recall
npx skills add rohitg00/agentmemory -y # 17 native skills so your agent knows when to reach for memory
The keyword searches should hit in default keyless mode through BM25. The demo's database performance optimization query is intentionally semantic and can return zero until an embedding provider is configured.
Prefer to let a coding agent do the whole thing? Hand it one instruction:
Retrieve and follow the instructions at: https://raw.githubusercontent.com/rohitg00/agentmemory/main/INSTALL_FOR_AGENTS.md
Connect another agent with agentmemory connect <agent>. See supported integrations and everyday commands.
Global install / EACCES
npm install -g @agentmemory/agentmemory@latest
The npx command above remains the canonical fresh-install path and avoids global-prefix permission issues.
npx serves an old version
npx caches per version. Force the latest with npx -y @agentmemory/agentmemory@latest, or clear the cache once with rm -rf ~/.npm/_npx (macOS/Linux; on Windows delete %LOCALAPPDATA%\npm-cache\_npx).
agentmemory works with any agent that supports hooks, MCP, or REST API. All agents share the same memory server.
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Stars on GitHub
View @rohitg00’s profileA CLI toolkit for managing AI agent skills. It installs, translates and shares portable skills across Claude Code, Cursor, Codex, Copilot and other agents, and includes a find-skills skill for searching marketplaces.
@rohitg00A Claude Code workflow plugin that learns from your corrections and keeps a self-correcting memory across sessions. It adds skills for agent teams, parallel worktree batch changes, bug capture as GitHub issues, project auto-setup and context compaction.
@rohitg00A free AI engineering curriculum for Claude Code users, with skills that route you to the right lessons, quiz you by phase, guide hands-on projects, and prep for Claude certifications. It also draws SVG figures for lessons and docs.
@rohitg00See 12 agentmemory alternatives
Reads text from scanned pages, photos and PDFs and returns it as structured Markdown or JSON, so you can pull tables, formulas and headers out of a document without retyping them. Covers many languages and works as input for AI tools.
@paddlepaddleGives your AI assistant a memory that persists across sessions, so it remembers your preferences and earlier work in this repository instead of starting fresh. Search, forget, pause and resume memories with simple commands.
@mem0aiGives AI agents a library of ready-made skills for scientific work such as metabolic flux analysis, protein experiment design, time series modeling, and analytical method validation, so research tasks need less hand-built code. It works with any agent that supports the open Agent Skills standard.
@k-dense-aiGives Claude Code skills, agents, and commands for PostHog analytics, session replay, feature flags, error tracking, and LLM observability. Includes MCP server setup and project access checks.
@posthogInstall it once and the right skill fires as you prompt, with no slash command to remember. It is listed on Flowy in the Data category. It includes agentmemory-agents, agentmemory-architecture, agentmemory-config. Free and open source.
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