MemoryStar
FreeNot checkedA local semantic memory MCP server for AI coding agents that provides persistent, searchable project knowledge including architecture notes, file symbols, git h
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A local semantic memory MCP server for AI coding agents that provides persistent, searchable project knowledge including architecture notes, file symbols, git history, progress tracking, and a knowledge graph, all stored locally.
README
Local semantic memory MCP server for AI coding agents — Cursor, VS Code / GitHub Copilot, and OpenCode.
MemoryStar gives your agent persistent, searchable project knowledge: architecture notes, file symbols, git history, progress tracking, and a knowledge graph — all stored locally (SQLite + ChromaDB).
Repository: github.com/ussdeveloper/memory-star
License: MIT
Author: Przemyslaw Lusina
Features
- 33 MCP tools — save, search (FTS5 + vectors), link, archive, sync, and more
- Per-file tracking — SHA256 change detection, symbol extraction, descriptions
- Knowledge graph — relationships between memories (
depends_on,implements, …) - Auto-sync — background watcher + Cursor hooks after every edit
- Web dashboard — graph view, browse, semantic search (
http://127.0.0.1:7988) - Windows installer — one-click setup into any project folder
- Privacy-first — all data stays on your machine
Quick start
Option A — Install into your project (Windows)
- Download or build
dist/MemoryStar-Setup.exe(see dist/README.md) - Requires Python 3.10–3.13 on PATH
- Run the installer → pick project folder → pick IDE
- Open project in IDE → Reload Window
- Dashboard: http://127.0.0.1:7988
Installed layout:
your-project/
.memorystar/ # server, venv, database
data/ # SQLite + ChromaDB
server.py
.venv/
.cursor/mcp.json # or .vscode/mcp.json
AGENTS.md
Option B — Run from source (this repo)
git clone https://github.com/ussdeveloper/memory-star.git
cd memory-star
python -m venv .venv
.venv/Scripts/activate # Windows
pip install -r requirements.txt
Copy examples/dev-cursor.mcp.json → .cursor/mcp.json (or VS Code equivalent — see examples/README.md).
python server.py
MCP tools (overview)
| Category | Tools |
|---|---|
| Core | memory_save, memory_load, memory_update, memory_search, memory_archive |
| Graph | memory_link, memory_get_links |
| Files | memory_update_file_structure, memory_get_file_info, memory_list_files |
| Hooks | memory_check_for_changes, memory_process_changes |
| Orchestration | memory_sync_project, memory_suggest_scan |
| Git | memory_git_history |
| Watcher | memory_start_watcher, memory_stop_watcher |
| Progress | memory_track_progress, memory_progress_update, memory_get_progress |
| Changelog | memory_changelog_add, memory_changelog_get, memory_changelog_trends |
| Maintenance | memory_clear, memory_restore, memory_list_backups, memory_stats, memory_trends |
Full tool reference is in the server docstring and AGENTS.md.
Agent workflow (recommended)
Session start → memory_suggest_scan(project_path=".")
After edits → memory_check_for_changes → memory_process_changes (if changed)
Save knowledge → memory_save(key=..., scope="architecture|api|decisions|...")
Before task → memory_search(query=..., mode="combined")
Architecture
Agent (MCP client)
│
├── stdio ── MemoryStar MCP Server (server.py)
│ ├── SQLite + FTS5
│ ├── ChromaDB (vectors)
│ ├── file_structure + memory_links
│
├── HTTP :9120 ── Webhook (watcher, context monitor)
│
└── HTTP :7988 ── UI dashboard
Configuration
Key environment variables (set in .cursor/mcp.json or .vscode/mcp.json):
| Variable | Description | Default |
|---|---|---|
MEMORYSTAR_DATA_DIR |
Database directory | ./data (dev) or .memorystar/data (install) |
MEMORYSTAR_PROJECT_PATH |
Workspace root to watch | — |
MEMORYSTAR_AUTO_SYNC |
Sync on MCP startup | 1 |
MEMORYSTAR_AUTO_WATCH |
Background file watcher | 1 |
MEMORYSTAR_UI_PORT |
Dashboard port | 7988 |
MEMORYSTAR_ENABLE_* |
Per-feature toggles | all 1 |
See README configuration section below for full list.
Feature toggles
| Flag | Tools |
|---|---|
MEMORYSTAR_ENABLE_CORE |
save, load, update, search |
MEMORYSTAR_ENABLE_FILE_STRUCTURE |
file scan, symbols, change hooks |
MEMORYSTAR_ENABLE_SYNC |
memory_sync_project |
MEMORYSTAR_ENABLE_WATCHER |
start/stop watcher |
All flags documented in AGENTS.md.
UI dashboard
Open http://127.0.0.1:7988 when the MCP server is running.
- Browse — memories, files, scopes, project tree
- Graph — force-directed knowledge graph
- Search — semantic + full-text
- Guide — built-in agent instructions
Project structure
memory-star/
server.py MCP server + webhook + UI
database.py SQLite + ChromaDB layer
config.py Environment configuration
ui.html Dashboard (single file)
requirements.txt
AGENTS.md Agent instructions (copy to projects)
examples/ MCP config templates
dist/ Windows installer + build scripts
.cursor/hooks/ Cursor hook scripts
Building the Windows installer
cd dist
.\build.ps1
Produces MemoryStar-Setup.exe and MemoryStar-Windows.zip.
Scopes
Use meaningful scope values when saving memories:
architecture · api · dependencies · patterns · decisions · bugs · notes · file-structure · git-history
Contributing
See CONTRIBUTING.md. Changelog: CHANGELOG.md.
License
MIT © 2026 Przemyslaw Lusina — see LICENSE.
Installing MemoryStar
This server has no published package — it is built from source. Open the repository and follow its README.
▸ github.com/ussdeveloper/memory-starFAQ
Is MemoryStar MCP free?
Yes, MemoryStar MCP is free — one-click install via Unyly at no cost.
Does MemoryStar need an API key?
No, MemoryStar runs without API keys or environment variables.
Is MemoryStar hosted or self-hosted?
Self-hosted: the server runs locally on your machine via the install command above.
How do I install MemoryStar in Claude Desktop, Claude Code or Cursor?
Open MemoryStar on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
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