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Local-first memory for AI coding agents. Memory + CodeGraph + Wiki in one SQLite file.
About
Local-first memory for AI coding agents. Memory + CodeGraph + Wiki in one SQLite file.
Security Report
Valid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry.
4 files analyzed · 1 issue found
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How to Install
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-tinhien11-remem-mcp": {
"args": [
"-y",
"remem-mcp"
],
"command": "npx"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
remem-mcp
Your coding agent stops repeating the same mistakes.
Local-first memory that survives context compaction. Learns from every error, injects fixes before the next attempt, and syncs to your git repo so your whole team shares it.
No API key. No cloud. No database server. Just a SQLite file.
Install
npx remem-mcp setup
Auto-detects Claude Code, Cursor, Devin, Codex. Registers MCP server + hooks. Restart your agent.
That's it. Use your agent normally — memory works automatically.
npx remem-mcp status # verify: hooks ✓, DB ✓, CodeGraph ✓
What happens automatically
| When | What |
|---|---|
| Session start | Past errors, decisions, and persona injected into agent context |
| Each prompt | Matching memory injected (you'll see [remem-mcp] at the top) |
| Tool calls | Verbose output offloaded to refs, Mermaid canvas injected (92% token cut) |
| Session end | Worker auto-extracts facts, consolidates summaries, updates persona |
You don't run any commands. The agent calls recall() before answering and capture() after work — the skill tells it to.
How it works
AI Agent (Claude Code / Devin / Cursor / Codex)
│
├── MCP tools ──▶ recall, capture, codegraph_*, wiki_*, feedback
│
└── Hooks ──▶ SessionStart, UserPromptSubmit, PreToolUse,
PostToolUse, Stop, PostCompact
│
▼
SQLite (memory.db)
L0 captures → L1 atoms → L2 scenarios → L3 persona
(raw) (facts) (summaries) (preferences)
CodeGraph: symbols + calls + imports (tree-sitter, 9 languages)
Memory links: Hebbian co-retrieval (frequently co-retrieved = stronger)
No LLM API key needed — rule-based extraction + keyword grouping.
CodeGraph
Structural code indexing via tree-sitter. The agent uses codegraph_search instead of grep to find symbols.
npx remem-mcp index --path src # index a directory
npx remem-mcp search-code --query "parseTar" # find symbols
npx remem-mcp callers <id> # who calls this?
npx remem-mcp impact <id> # blast radius
9 languages: TS/JS/Python/Go/Rust/Java/C/C++/C#. 6-strategy call resolution (import-map → same-module → unique-name → suffix → fuzzy). Stdlib calls filtered out.
| Repo | Files | Symbols | Calls | Time |
|---|---|---|---|---|
| remem-mcp | 79 | 301 | 6,456 | 3s |
| AZR Go | 455 | 3,417 | 41,603 | 111s |
| Orca TS | 3,000 | 7,632 | 78,981 | 705s |
Why it's different
| remem-mcp | Mem0 | Claude MEMORY.md | Mneme | |
|---|---|---|---|---|
| Survives compaction | Yes | Yes — cloud | No — 200-line cap | Yes |
| Learns from errors | Yes — auto | No | No | No |
| Search | Hybrid BM25 + vector + entities | Vector only | No | Vector + graph |
| Memory links | Hebbian co-retrieval | No | No | Graph |
| Decay/forget | Yes | No | No | No |
| CodeGraph | Yes — 6-strategy call resolution | No | No | No |
| Token offload | Yes — Mermaid canvas | No | No | No |
| Setup | 1 command | API key + cloud | Built-in | Build from source |
| Cost | Free | $19–249/mo | Free | Free |
Per-agent install
claude mcp add remem-mcp --scope user -- npx -y remem-mcp
npx remem-mcp install-hooks
Or add to ~/.cursor/mcp.json:
{
"mcpServers": {
"remem-mcp": { "command": "npx", "args": ["-y", "remem-mcp"] }
}
}
devin mcp add remem-mcp --scope user -- npx -y remem-mcp
npx remem-mcp install-hooks
Add to ~/.codex/config.toml:
[mcp_servers.remem-mcp]
command = "npx"
args = ["-y", "remem-mcp"]
Then run npx remem-mcp install-hooks.
Useful commands
npx remem-mcp status # health + hooks + DB + CodeGraph
npx remem-mcp viewer # web UI at localhost:7331
npx remem-mcp errors # error dashboard
npx remem-mcp recent [N] # recent captures
npx remem-mcp help all # full list of 40+ subcommands
Configuration
All settings have defaults. Config file is optional: ~/.config/remem-mcp/config.json.
| Setting | Env var | Default |
|---|---|---|
| DB path | REMEM_DB_PATH | ~/.local/share/remem-mcp/memory.db |
| Cross-project memory | REMEM_GLOBAL_SESSION_KEY | (unset) |
| Unified flow (F1+F2+F3) | REMEM_FLOW | (unset, set to full) |
| Suppress hook feedback | REMEM_QUIET | (unset, set to 1) |
Global memory policy — set REMEM_GLOBAL_SESSION_KEY to read cross-project memory automatically. Captures stay project-local unless the user explicitly asks to save globally; then use session_key: "global". Do not auto-classify ordinary captures into global.
Team sharing — npx remem-mcp sync-export writes .remem-mcp/memory-export.jsonl. Commit it to git. Team members get the same memory on git pull.
Per-repo capture exclusions — Drop a .remem.toml in any project root:
[capture]
ignore_paths = ["node_modules", "dist", ".git", "*.min.js"]
Benchmark
| Benchmark | remem-mcp | Mem0 | Without memory |
|---|---|---|---|
| AMB (L1/L2/L3) | 100/100/100 | — | — |
| LoCoMo (long conversation QA) | 95 | 92.5 | — |
| PersonaMem (personalization) | 100 | — | 48 |
| LongMemEval (ICLR 2025) | 96 | 94.4 | — |
bash scripts/bench-all.sh --quick # AMB only (~2 min)
Architecture
See ARCHITECTURE.md for full system diagrams, schema, and performance details.
Credits
Core based on TencentDB Agent Memory (MIT, Tencent 2026). CodeGraph call resolution adapted from Codebase-Memory (arXiv:2603.27277). Recall boost adapted from ai-memory by Akita On Rails. Contextual retrieval from Anthropic (2024).
License
MIT. See LICENSE.
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