
Memento
io.github.scrypsterPublished by GitHub account scrypsterv0.1.0Updated Oct 27, 2026
Persistent memory for AI tools. Local-first knowledge graph with hybrid search.
Overview
Local-first persistent memory server that builds a knowledge graph from AI conversations so assistants recall decisions and context across sessions.
- What you can do
- Store, recall, update and forget memories, with soft delete, restore and deleted-memory listing
- Search memories with hybrid full-text plus semantic vector ranking, and find related items
- Explore the knowledge graph: traverse entity relationships, detect contradictions, explain why memories were retrieved, get session context
- Manage memory lifecycle: change state, evolve into new versions, consolidate related memories, view version history
- Organize projects: create projects, add epics, phases, tasks and milestones, list projects and fetch the project tree
- When to use it
- Useful when you want an assistant to remember preferences, architectural decisions and project context between sessions without re-explaining, or when a team wants shared, attributable memory across their AI tools.
- Requirements
- Runs locally over stdio. Needs Docker, or Go 1.23+ with Node.js 18+ and Ollama; the first run downloads roughly 5 GB of Ollama models. Optional settings include MEMENTO_DATA_PATH, MEMENTO_STORAGE_ENGINE, MEMENTO_LLM_PROVIDER, MEMENTO_USER and a PostgreSQL connection URL for team setups.
Installation
In SourceWeft
- Open Memento in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
[Memento — Remember Everything, Forget Nothing]
Memento
Give your AI tools a persistent memory — so every session starts where the last one left off.
[Version] [Go Version] [License] [Docker] [MCP]
Your AI starts fresh every session. Memento fixes that.
It runs on your machine, connects to any MCP-compatible AI tool, and builds a persistent knowledge graph from your conversations — entities, relationships, decisions, and context that survive every session restart.
No cloud. No API keys required. No subscriptions. Your data stays on your machine.
Quick Start
Prerequisites: Docker — or — Go 1.23+ + Node.js 18+ + Ollama
The script detects your environment, runs preflight checks, builds everything, and prints the exact command to connect your AI tool at the end. First run downloads Ollama models (~5 GB). After that, starts in seconds.
Your first memory
Once connected, try this in Claude:
Close the tab. Open a new session. Ask:
Your AI already knows. No re-explaining. No context window tricks.
Close the tab. Open a new session.
Behind the scenes, Memento built this automatically:
Every entity gets wired into a knowledge graph — people, tools, projects, decisions — with confidence scores and timestamps.
Connect Your Tools
Open http://localhost:6363/integrations — the web UI generates configs, download buttons, and connection testing for every client:
The integrations page generates ready-to-paste configs with your actual binary paths and data directories. It also has connection testing, troubleshooting, and per-project workspace scoping.
Make Claude Code proactive (recommended)
The MCP connection makes tools available, but Claude won't use them automatically. Add this to ~/.claude/CLAUDE.md to make Claude store decisions and recall context without being asked:
The web UI at Integrations → Claude Code → Make it proactive generates a version with your specific paths and connection settings, plus a download button.
See the full integration guides: Claude Code | Claude Desktop | Cursor & Windsurf | OpenClaw
Team memory — shared knowledge across your whole engineering team
Point everyone's AI tools at the same Memento instance and your team's decisions, conventions, and context become shared knowledge — queryable by anyone, attributable to anyone.
Every memory is tagged with who stored it. Memento auto-detects this from your git config, or you can set it explicitly:
Or in your MCP config:
Once set, you can ask:
Setup: Each teammate runs Memento pointing at the same PostgreSQL database. Personal context stays personal (use a separate personal connection). Shared architectural decisions, conventions, and project context go into the shared connection.
See the team setup guide for full PostgreSQL configuration.
What Your AI Gets
Once connected, your AI has 20 tools it can call — no prompting required:
Core memory operations
Search and intelligence
Memory lifecycle
Soft delete and recovery
Project management
Store returns in <10ms. Enrichment — entity extraction, relationship mapping, embedding generation — runs asynchronously. Your AI is never blocked.
What It Looks Like
Auto-extracted entities — zero manual input
People, projects, tools, organizations, languages, APIs — extracted automatically from your AI conversations. No tagging required.
Relationship intelligence
Your AI knows who works_on what, which tools depend_on which services, and what the current state of each decision is — with confidence scores and timestamps.
The dashboard
Live enrichment queue, entity browser, relationship explorer, and graph visualizer — all in the web UI.
Why Memento
vs. Mem0
Mem0 requires cloud API keys and a paid plan for production use. Memento runs entirely on your machine with Ollama — no API keys, no cloud, no per-memory pricing. Memento also ships a full web UI with graph visualization, entity browser, and one-click integration setup. Mem0 has no web interface.
vs. Zep / Graphiti
Zep requires Neo4j or FalkorDB for its knowledge graph. Memento uses SQLite (zero deps) or PostgreSQL — no graph database to manage. Zep's open-source version is limited; the full feature set requires Zep Cloud.
vs. Built-in AI memory (ChatGPT, Claude)
Built-in memory is a flat list of facts with no relationships, no search, no graph, and no way to export or control your data. Memento gives you a structured knowledge graph you own, with hybrid search and full lifecycle management.
vs. Writing docs or wikis
Memento captures context automatically as you work — no manual effort. It builds relationships between concepts instead of isolated pages, and it's designed to be queried by LLMs, not just humans.
How It Works
Features
Runs entirely offline
- Ollama runs locally — default setup never makes an external network call
- SQLite database is a single file you own:
~/.memento/memento.db - Swap to OpenAI or Anthropic when you want stronger extraction — opt-in only
Hybrid search
- FTS5 full-text + semantic vector search fused with Reciprocal Rank Fusion (RRF)
- Finds what you mean, not just what you typed
Knowledge graph
- Extracts 22 entity types: people, projects, tools, languages, APIs, databases, concepts, and more
- Maps 44 relationship types with confidence scores
- Interactive graph explorer in the web UI
Memory lifecycle
- Lifecycle states:
planning → active → paused | blocked | completed | cancelled → archived - Decay scoring — stale context loses ranking weight naturally
- Access-frequency boosting — memories you recall often stay prominent
Production-ready backends
- SQLite (zero deps, CGo-free) for personal/local use
- PostgreSQL + pgvector + ivfflat index for team or production deployments
Multi-connection isolation
- Separate memory namespaces per project, client, or workspace
- Route MCP calls to different connections with a single env var
Web UI
- Dashboard with live enrichment queue, entity browser, relationship explorer, graph visualizer
- One-click integration setup for every supported client
- Connection testing, CLAUDE.md generation, Cursor Rules download
- Tracks unrecognized LLM entity types so you can expand your taxonomy over time
LLM Providers
Switch providers per connection — different projects can use different LLMs.
Configuration
PostgreSQL
Project Structure
Contributing
Issues and PRs welcome. Open an issue before starting significant work.
License
MIT — see LICENSE.
Built by
MJ Bonanno — software architect and founder of Scrypster.
Remember everything. Forget nothing. Unlike Leonard Shelby, your context is here to stay — searchable, versioned, and backed by a knowledge graph that never fades.
Source: README.md at commit cad457c
Tools
0Version history
1- v0.1.0LatestSep 16, 2026
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