[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_126":127},"routes/modules.$creator.$moduleId",{"_14":15,"_16":17,"_18":19,"_20":21},"routes/modules.$creator.$moduleId.endpoints",{"_11":12,"_13":-5},"error","Module not found","tools","module",{"_20":22,"_23":24,"_25":26,"_27":28,"_29":30,"_31":32,"_33":34,"_35":26,"_36":37,"_38":-5,"_39":-5,"_40":41,"_42":43,"_44":45,"_46":47,"_48":49,"_50":51,"_52":53,"_54":55,"_56":-5,"_57":49,"_58":59,"_60":61,"_62":-5,"_63":-5,"_64":11,"_65":66,"_67":68,"_69":70,"_71":72,"_73":74,"_75":76,"_77":-5,"_78":-5,"_79":-5,"_80":49,"_81":-5,"_82":83,"_84":85,"_86":87,"_88":89,"_90":91,"_92":93},"apiUrl","https://odel.app/api","creator","verygoodplugins","moduleId","mcp-automem","@verygoodplugins/mcp-automem","displayName","MCP AutoMem","tagline","Graph-vector memory for AI assistants using FalkorDB and Qdrant","iconKey","https://avatars.githubusercontent.com/u/193913467?v=4","category","remote","status","published","visibility","public","metaDescription","deploymentType","external","workerName","bindingName","mcpConfig","{\"url\":\"https://{endpoint}/mcp\",\"transport\":\"streamable-http\",\"authType\":\"bearer\"}","pricingModel","free","creatorUserId","system:external-import","createdAt",1783399049000,"updatedAt",1788167964000,"sourceRegistry","official-mcp-registry","sourceUrl","https://registry.modelcontextprotocol.io/v0/servers?search=io.github.verygoodplugins%2Fmcp-automem","sourceVerified",true,"sourceMissingSince","importedAt","upstreamStars",64,"upstreamUpdatedAt",1787702072000,"detectedTransport","detectedAuthType","probeStatus","lastProbedAt",1787555150000,"githubRepoUrl","https://github.com/verygoodplugins/mcp-automem","githubRepoFullName","verygoodplugins/mcp-automem","releaseId","ext-verygoodplugins-mcp-automem","version","0.10.0","descriptionMarkdown","# AutoMem MCP: Give Your AI Perfect Memory\n\n

\n $\"AutoMem\"$ \n

\n\n

\n $\"Version\"$ \n $\"License\"$ \n $\"Discord\"$ \n $\"X$ \n

\n\n**One command. Infinite memory. Perfect recall across all your AI tools.**\n\n```bash\nnpx @verygoodplugins/mcp-automem setup\n```\n\nYour AI assistant now remembers everything. Forever. Across every conversation.\n\n

\n\nhttps://github.com/user-attachments/assets/fd79112b-5158-4320-a054-8c18ab1ea314\n\n

\n\n

_{The guided installer — npx @verygoodplugins/mcp-automem install walks you through local, hosted, or existing-endpoint setup.}

\n\nWorks with **Claude Desktop**, **Cursor IDE**, **Claude Code**, **GitHub Copilot (coding agent)**, **ChatGPT**, **ElevenLabs**, **OpenAI Codex**, **OpenClaw**, **Hermes**, **Grok Build**, **Google Antigravity** - any MCP-compatible AI platform.\n\n## The Problem We Solve\n\nEvery AI conversation starts from zero. Claude forgets your coding style. Cursor can't learn your patterns. Your assistant doesn't remember yesterday's decisions.\n\n**Until now.**\n\nAutoMem MCP connects your AI to persistent memory powered by **[AutoMem](https://github.com/verygoodplugins/automem)** - a graph-vector memory service.\n\n## What You Get\n\n### 🧠 Persistent Memory Across Sessions\n\n- AI remembers decisions, patterns, and context **forever**\n- Works across **all MCP platforms** - Claude Desktop, Cursor, Claude Code, OpenAI Codex, OpenClaw, Hermes, Grok Build, Google Antigravity\n- **Cross-device sync** - same memory on Mac, Windows, Linux\n\n### 🏆 Graph-Vector Architecture\n\n- **11 public authorable relationship types** between memories (recall results may also include read-only system/internal relations that are not valid `associate_memories` inputs)\n- **Research-validated** approach (HippoRAG 2: 7% better associative memory)\n- **Sub-second retrieval** even with millions of memories\n\n### 🚀 Works Everywhere You Code\n\n| Platform | Support | Setup Time |\n| ------------------ | ------- | ---------- |\n| **Claude Desktop** | ✅ Full | 30 seconds |\n| **Cursor IDE** | ✅ Full | 30 seconds |\n| **Claude Code** | ✅ Full | 30 seconds |\n| **GitHub Copilot** | ✅ Full | 2 minutes |\n| **OpenAI Codex** | ✅ Full | 30 seconds |\n| **OpenClaw** | ✅ Full | 30 seconds |\n| **Hermes Agent** | ✅ Full | 30 seconds |\n| **Grok Build** | ✅ Full | 30 seconds |\n| **Google Antigravity** | ✅ Full | 30 seconds |\n| **Any MCP client** | ✅ Full | 30 seconds |\n\n## See It In Action\n\n### Claude Desktop with Personal Preferences\n\n![Claude Desktop Using Memory](https://raw.githubusercontent.com/verygoodplugins/mcp-automem/main/screenshots/claude-desktop-with-instructions.jpg)\n_Claude automatically recalls memories using the Personal Preferences template_\n\n### Cursor IDE with Memory Rules\n\n![Cursor with Memory](https://raw.githubusercontent.com/verygoodplugins/mcp-automem/main/screenshots/cursor-2.jpg)\n_Cursor uses automem.mdc rule to automatically recall and store memories_\n\n### Claude Code with Session Memory\n\n![Claude Code Memory Capture](https://raw.githubusercontent.com/verygoodplugins/mcp-automem/main/screenshots/claude-code-1.jpg)\n_Session-start recall plus LLM-judged storage: Claude decides what's durable and stores it via the memory tools_\n\nMore platform walkthroughs (Codex, Hermes, Antigravity, remote MCP) live in the **[Installation Guide](https://github.com/verygoodplugins/mcp-automem/blob/main/INSTALLATION.md)**.\n\n## Quick Start\n\n### 1. Set Up AutoMem Service\n\nYou need a running AutoMem service (the memory backend). Choose one:\n\n**Option A: Local Development** (fastest, free)\n\n```bash\ngit clone https://github.com/verygoodplugins/automem.git\ncd automem\nmake dev\n```\n\nService runs at `http://localhost:8001` - perfect for single-machine use.\n\n**Option B: Railway Cloud** (recommended for production)\n\n[![Deploy on Railway](https://railway.com/button.svg)](https://github.com/verygoodplugins/automem/blob/main/INSTALLATION.md#railway-deployment)\n\nOne-click deploy with $5 free credits. Typical cost: ~$0.50-1/month after trial.\n\n👉 **[AutoMem Service Installation Guide](https://github.com/verygoodplugins/automem/blob/main/INSTALLATION.md)** - Complete setup instructions for local, Railway, Docker, and production deployments.\n\n---\n\n### 2. Install MCP Client\n\n#### Claude Desktop - One-Click Install\n\nDownload and double-click to install AutoMem in Claude Desktop:\n\n**[⬇️ Download AutoMem for Claude Desktop (.mcpb)](https://github.com/verygoodplugins/mcp-automem/releases/latest/download/mcp-automem.mcpb)**\n\nAfter installing:\n1. Claude Desktop will prompt you for your **AutoMem Endpoint** (`http://127.0.0.1:8001` for local)\n2. Optionally enter your **API Key** (required for Railway, skip for local)\n3. Click Enable\n\nThen add the paste-ready Personal Preferences starter from [`templates/CLAUDE_DESKTOP_INSTRUCTIONS.md`](https://github.com/verygoodplugins/mcp-automem/blob/main/templates/CLAUDE_DESKTOP_INSTRUCTIONS.md). That's it: Claude now has persistent memory and knows when to use it.\n\n#### Other Platforms\n\nConnect your AI tools to the AutoMem service you just started.\n\n```bash\n# Guided install - pick where AutoMem runs, verify it, write .env, and\n# configure your agents (Codex, Claude Code, Cursor, OpenClaw, Hermes)\nnpx @verygoodplugins/mcp-automem install\n```\n\nEvery change is shown in a review plan before anything is written, and each\nmodified file keeps a `.bak` backup. Add `--dry-run` to preview, `--yes` to\napply non-interactively. See the [Installation Guide](https://github.com/verygoodplugins/mcp-automem/blob/main/INSTALLATION.md#guided-install-fastest)\nfor all flags.\n\nJust need the `.env` + config snippets without the agent setup? Use the lighter wizard:\n\n```bash\n# Creates .env and prints config for your AI platform\nnpx @verygoodplugins/mcp-automem setup\n```\n\n**When prompted:**\n\n- **AutoMem Endpoint:** `http://localhost:8001` (or your Railway URL if deployed)\n- **API Key:** Leave blank for local development (or paste your token for Railway)\n\nThe wizard will:\n\n- ✅ Save your endpoint and API key to `.env`\n- ✅ Generate config snippets for Claude Desktop/Cursor/Code\n- ✅ Validate connection to your AutoMem service\n\n### 3. Platform-Specific Setup\n\n**For Claude Code (plugin — recommended):**\n\n```text\n# In Claude Code:\n/plugin marketplace add verygoodplugins/mcp-automem\n/plugin install automem@verygoodplugins-mcp-automem\n```\n\nClaude Code prompts for your AutoMem URL and API key at enable time, bundles the MCP server and silent recall/store-tracking hooks, and auto-updates. Prefer hooks and permissions written directly into `~/.claude/` instead? Run `npx @verygoodplugins/mcp-automem claude-code`.\n\nOn Windows, the hook payload assumes a POSIX shell environment such as Git Bash, MSYS2, or WSL — only `bash` is required (the hooks are pure bash+sed).\n\n**For Cursor IDE:**\n\n[![Install MCP Server](https://cursor.com/deeplink/mcp-install-light.svg)](cursor://anysphere.cursor-deeplink/mcp/install?name=memory&config=eyJlbnYiOnsiQVVUT01FTV9BUElfVVJMIjoiaHR0cDovLzEyNy4wLjAuMTo4MDAxIiwiQVVUT01FTV9BUElfS0VZIjoieW91ci1hcGkta2V5LWlmLXJlcXVpcmVkIn0sImNvbW1hbmQiOiJucHggLXkgQHZlcnlnb29kcGx1Z2lucy9tY3AtYXV0b21lbSJ9)\n\n```bash\n# Or use CLI to install automem.mdc rule file\nnpx @verygoodplugins/mcp-automem cursor\n```\n\n**Other platforms** — Claude Desktop (one-click `.mcpb` above, plus the [Personal Preferences template](https://github.com/verygoodplugins/mcp-automem/blob/main/templates/CLAUDE_DESKTOP_INSTRUCTIONS.md)), [OpenAI Codex](https://github.com/verygoodplugins/mcp-automem/blob/main/INSTALLATION.md#openai-codex), [Hermes Agent](https://github.com/verygoodplugins/mcp-automem/blob/main/INSTALLATION.md#hermes-agent), [Grok Build](https://github.com/verygoodplugins/mcp-automem/blob/main/INSTALLATION.md#grok-build), [OpenClaw](https://github.com/verygoodplugins/mcp-automem/blob/main/INSTALLATION.md#openclaw), [Google Antigravity](https://github.com/verygoodplugins/mcp-automem/blob/main/INSTALLATION.md#google-antigravity), and [GitHub Copilot](https://github.com/verygoodplugins/mcp-automem/blob/main/INSTALLATION.md#github-copilot-coding-agent-githubcom):\n\n👉 **[Full Installation Guide](https://github.com/verygoodplugins/mcp-automem/blob/main/INSTALLATION.md)** for every platform's setup and verification steps\n\n---\n\n## Remote MCP via HTTP\n\nAn optional sidecar service (deployable to Railway or any Docker host) connects AutoMem to platforms that support remote MCP over **Streamable HTTP** or SSE — ChatGPT (Developer Mode connectors), Claude.ai web and Claude Mobile, and ElevenLabs Agents.\n\n👉 **[Remote MCP setup](https://github.com/verygoodplugins/mcp-automem/blob/main/INSTALLATION.md#remote-mcp-via-http-sidecar)** for deployment, connect URLs, and per-platform screenshots.\n\n## Architecture\n\n```\n┌─────────────────────────────────────────────┐\n│ Your AI Platforms │\n│ Claude Desktop │ Cursor │ Claude Code │\n└──────────────┬──────────────────────────────┘\n │ MCP Protocol\n ▼\n┌──────────────────────────────────────────────┐\n│ @verygoodplugins/mcp-automem (this repo) │\n│ • Translates MCP calls → AutoMem API │\n│ • Platform integrations & rules │\n│ • Handles authentication │\n└──────────────┬───────────────────────────────┘\n │ HTTP API\n ▼\n┌──────────────────────────────────────────────┐\n│ AutoMem Service (separate repo) │\n│ github.com/verygoodplugins/automem │\n│ ┌────────────┐ ┌────────────┐ │\n│ │ FalkorDB │ │ Qdrant │ │\n│ │ (Graph) │ │ (Vectors) │ │\n│ └────────────┘ └────────────┘ │\n└──────────────────────────────────────────────┘\n```\n\n**This repo (mcp-automem):**\n\n- MCP client that connects AI platforms to AutoMem\n- Platform-specific integrations (Cursor rules, Claude Code hooks, etc.)\n- Setup wizards and configuration tools\n\n**[AutoMem service](https://github.com/verygoodplugins/automem):**\n\n- Backend memory service with graph + vector storage\n- Deployment guides (local, Railway, Docker, production)\n- API server with FalkorDB + Qdrant\n\n## Features\n\n### Core Memory Operations\n\n- **`store_memory`** — Save memories with content, tags, importance, metadata. Two modes:\n - **Single (default)**: top-level `content` plus optional fields, including `embedding`, `t_valid`, `t_invalid`, custom `id`.\n - **Batch**: `memories: [...]` (≤500 items) for bulk ingestion. Per-item `id`/`embedding`/`t_valid`/`t_invalid` are not supported in batch mode.\n- **`recall_memory`** — Three modes selected by which params you pass:\n - **ID fetch**: `memory_id` → fetches one memory by ID; updates `last_accessed`.\n - **Tag enumeration**: `tags` + `exhaustive: true` → paginated exact-match listing for cleanup/audit workflows where ranked recall undercounts. Pair with `limit` (≤200) and `offset`; returns `has_more`.\n - **Ranked retrieval (default)**: hybrid search across vector, keyword, tags, recency/state controls, score filters, and graph expansion. Supports `state_mode`, `recency_bias`, `scope_fallback`, `expand_respect_tags`, `min_score`, `adaptive_floor`, and diagnostics such as `tag_scope`, `score_filter`, `query_time_ms`, `vector_search`, and per-result `outside_tag_scope`/`state_replaces`.\n- **`associate_memories`** — Create relationships (11 public authorable types; recall results may also include read-only system relations). Supports single-pair mode and batch mode via `associations: [...]` (≤500) with relation-specific props like `reason`, `context`, `resolution`, `observations`, `transformation`, and `role`.\n- **`update_memory`** — Modify existing memories\n- **`delete_memory`** — Two modes:\n - **Single (default)**: `memory_id` → removes one memory and its embedding.\n - **Bulk-by-tag**: `tags: [...]` → bulk-delete all memories matching ANY tag (exact, case-insensitive). No dry-run; verify with `recall_memory({ tags, exhaustive: true })` first.\n- **`check_database_health`** — Monitor service health, degraded state, sync counts, vector dimensions, and enrichment diagnostics when the service provides them\n\n### Advanced Recall (v0.8.0+)\n\n**Multi-hop Reasoning** - Answer complex questions like \"What is Amanda's sister's career?\"\n\n```javascript\nmcp__memory__recall_memory({\n query: \"What is Amanda's sister's career?\",\n expand_entities: true, // Finds \"Amanda's sister is Rachel\" → memories about Rachel\n});\n```\n\n**Context-Aware Coding** - Recall prioritizes language and style preferences\n\n```javascript\nmcp__memory__recall_memory({\n query: \"error handling patterns\",\n language: \"typescript\",\n context_types: [\"Style\", \"Pattern\"],\n});\n```\n\n### Platform Integrations\n\n#### Cursor IDE\n\n- ✅ **Memory-first rule file** (`automem.mdc` in `.cursor/rules/`)\n- ✅ **Automatic memory recall** at conversation start\n- ✅ **Auto-detects project context** (package.json, git remote)\n- ✅ **Global user rules option** for all projects\n- ✅ **Simple setup** via CLI or one-click install\n\n#### Claude Code\n\n- ✅ **Native plugin** - MCP server, silent hooks, and skill in one `/plugin install`, with enable-time config prompts and auto-updates\n- ✅ **LLM-judged storage** - session-start guidance nudges Claude to store, verify, and associate durable memories during normal work\n- ✅ **Memory rules** in CLAUDE.md guide Claude's memory usage\n\n#### GitHub Copilot\n\n- ✅ **Standalone hook JSON files** installed into `$COPILOT_HOME/hooks/` or `~/.copilot/hooks/`\n- ✅ **Memory rules** template for `copilot-instructions.md`\n- ✅ **Format flag** - `--format cli` (camelCase) or `--format vscode` (PascalCase)\n- ✅ **Setup**: `npx @verygoodplugins/mcp-automem copilot --yes`\n\n#### Claude Desktop\n\n- ✅ Direct MCP integration\n- ✅ Paste-ready Personal Preferences starter template\n- ✅ Full memory API access\n\n## Why AutoMem MCP?\n\n### vs. Building Your Own\n\n- ✅ **2 years of R&D** already done\n- ✅ **Research-validated** architecture (HippoRAG 2, MELODI, A-MEM)\n- ✅ **Working integrations** across all MCP platforms\n- ✅ **Active development** and community\n\n### vs. Other Memory Solutions\n\n- ✅ **True graph relationships** (not just vector similarity)\n- ✅ **Universal MCP compatibility** (works with any MCP client)\n- ✅ **7 memory types** (Decision/Pattern/Preference/Style/Habit/Insight/Context)\n- ✅ **Self-hostable** ($5/month vs $150+ for alternatives)\n\n### vs. Native AI Memory\n\n- ✅ **Persistent across sessions** (not just context window)\n- ✅ **Cross-platform** (same memory in Claude, Cursor, Code)\n- ✅ **Structured relationships** (not just RAG)\n- ✅ **Infinite scale** (no context window limits)\n\n## Documentation\n\n### MCP Client & Integrations (this repo)\n\n- 📦 **[Installation Guide](https://github.com/verygoodplugins/mcp-automem/blob/main/INSTALLATION.md)** - MCP client setup for all platforms\n- 🌐 **[Remote MCP via HTTP](https://github.com/verygoodplugins/mcp-automem/blob/main/INSTALLATION.md#remote-mcp-via-http-sidecar)** - Connect ChatGPT, Claude Web/Mobile, ElevenLabs\n- 🎯 **[Cursor Setup](https://github.com/verygoodplugins/mcp-automem/blob/main/INSTALLATION.md#cursor-ide)** - IDE integration with rules\n- 🤖 **[Claude Code Setup](https://github.com/verygoodplugins/mcp-automem/blob/main/templates/CLAUDE_CODE_INTEGRATION.md)** - Plugin install, hooks, and memory rules\n- ⚠️ **[Deprecations](https://github.com/verygoodplugins/mcp-automem/blob/main/DEPRECATION.md)** - History of the plugin deprecation and its reversal\n- 🚀 **[OpenAI Codex Setup](https://github.com/verygoodplugins/mcp-automem/blob/main/INSTALLATION.md#openai-codex)** - Codex CLI/IDE/Cloud integration\n- 🪐 **[Google Antigravity Setup](https://github.com/verygoodplugins/mcp-automem/blob/main/INSTALLATION.md#google-antigravity)** - Raw MCP config via Antigravity's MCP Store\n- 📖 **[MCP Tools Reference](https://github.com/verygoodplugins/mcp-automem/blob/main/INSTALLATION.md#mcp-tools)** - All memory operations\n- 📝 **[Changelog](https://github.com/verygoodplugins/mcp-automem/blob/main/CHANGELOG.md)** - Release history\n\n### AutoMem Service (separate repo)\n\n- 🏗️ **[AutoMem Service](https://github.com/verygoodplugins/automem)** - Backend repository\n- 🚀 **[Service Installation](https://github.com/verygoodplugins/automem/blob/main/INSTALLATION.md)** - Local, Railway, Docker deployment\n- ⚙️ **[API Documentation](https://github.com/verygoodplugins/automem#api-reference)** - REST API reference\n- 🧪 **[Evaluation Lab](https://github.com/verygoodplugins/automem-evals)** - Exploratory recall-quality benchmarks and ruleset A/B testing\n\n## The Science Behind AutoMem\n\nThe AutoMem service implements cutting-edge 2025 research:\n\n- **[HippoRAG 2](https://arxiv.org/abs/2502.14802)** (OSU, June 2025): Graph-vector approach achieves 7% better associative memory\n- **A-MEM** (July 2025): Dynamic memory organization with Zettelkasten principles\n- **MELODI** (DeepMind, 2025): 8x memory compression without quality loss\n- **ReadAgent** (DeepMind, 2024): 20x context extension through gist memories\n\nThis MCP package provides the bridge between your AI and that research-validated memory system. The backend has also been benchmarked on the neutral [Agent Memory Benchmark](https://automem.ai/benchmarks), including BEAM large-context scaling tiers — reproducible end to end, so you can run it yourself.\n\n## Community & Support\n\n- 💬 **[Discord](https://automem.ai/discord)** - Join the community, get help, share feedback\n- 🐦 **[X Community](https://x.com/i/communities/2013114118912225326)** - Discussion and updates\n- 📣 **[@automem_ai](https://x.com/automem_ai)** - Official announcements\n- 📦 **[NPM Package](https://www.npmjs.com/package/@verygoodplugins/mcp-automem)** - This MCP client\n- 🔬 **[AutoMem Service](https://github.com/verygoodplugins/automem)** - Backend repo with deployment guides\n- 🐛 **[GitHub Issues](https://github.com/verygoodplugins/mcp-automem/issues)** - Bug reports and feature requests\n\n## Contributing\n\nWe welcome contributions! Please:\n\n1. Fork the repository\n2. Create a feature branch\n3. Make your changes with tests\n4. Submit a pull request with a Conventional Commit title such as `fix:`, `feat:`, `docs:`, or `chore:`\n5. Do not prefix the PR title with labels like `[codex]` or `[wip]` because the squash-merge commit is taken from the PR title\n\n## License\n\nMIT - Because great memory should be free.\n\n---\n\n**Ready to give your AI perfect memory?**\n\n```bash\nnpx @verygoodplugins/mcp-automem setup\n```\n\n_Built with obsession. Validated by neuroscience. Powered by graph theory. Works with every MCP-enabled AI._\n\n_Designed by Jack Arturo at [Very Good Plugins](https://verygoodplugins.com)_ 🧡\n\n**Transform your AI from a tool into a teammate. Start now.**\n","changelogMarkdown","videoKey","requiredSecretsJson","publishedAt","priceCents","trialDays",0,"upstream",{"_107":108,"_109":110,"_111":112,"_113":114,"_115":116,"_117":118},"requiredSecrets",[],"tags",[96,97,98,99,100,101,102,103,104,105,106],"assets",[],"stats",{"_94":83,"_95":83},"ratingAvg","reviewCount","ai","ai-memory","automem","falkordb","graph-database","memory","nodejs","qdrant","rag","redis","vector-database","topics",[96,97,98,99,100,123,124,101,125,102,103,104,105,106],"license","MIT","language","TypeScript","registryName","io.github.verygoodplugins/mcp-automem","homepage","https://automem.ai/?utm_source=mcp-registry","packages",[119],{"_120":121,"_122":22,"_73":74},"registryType","npm","identifier","mcp","mcp-server","model-context-protocol","ENV",{"_128":129,"_130":131,"_132":133},"ENVIRONMENT","production","TURNSTILE_SITE_KEY","0x4AAAAAAB8-rEI2gNDf_QhU","SENTRY_DSN","https://45fd1229f78089d5c3ee78be128030e1@o4510583261757440.ingest.de.sentry.io/4510584253448272"]