Metadata-Version: 2.4
Name: memdex-mcp
Version: 0.2.1
Summary: Zero-dependency shared memory for AI coding agents: content-hash file summaries, symbol map, notes and handoffs over MCP.
License: MIT
Project-URL: Homepage, https://github.com/ChoYugyeong/memdex
Project-URL: Issues, https://github.com/ChoYugyeong/memdex/issues
Keywords: mcp,ai,agent,memory,claude,codex,context,sqlite
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Software Development
Classifier: Environment :: Console
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Dynamic: license-file

<h1 align="center">memdex</h1>

<!-- mcp-name: io.github.ChoYugyeong/memdex -->

<p align="center">
  <b>Shared, token-saving memory for AI coding agents.</b><br/>
  One SQLite file. Zero dependencies. Any MCP client. Claude Code, Codex, Cursor and DeepSeek can all remember the same things — and talk to each other.
</p>

<p align="center">
  <a href="https://github.com/ChoYugyeong/memdex/actions/workflows/ci.yml"><img alt="CI" src="https://github.com/ChoYugyeong/memdex/actions/workflows/ci.yml/badge.svg"></a>
  <a href="https://pypi.org/project/memdex-mcp/"><img alt="PyPI" src="https://img.shields.io/pypi/v/memdex-mcp?label=pypi"></a>
  <img alt="Python 3.9+" src="https://img.shields.io/badge/python-3.9%2B-blue">
  <a href="LICENSE"><img alt="MIT" src="https://img.shields.io/github/license/ChoYugyeong/memdex"></a>
</p>

<p align="center">
  <a href="#quick-start">Quick start</a> ·
  <a href="#how-it-works">How it works</a> ·
  <a href="#tools">Tools</a> ·
  <a href="#cli">CLI</a> ·
  <a href="#configuration">Configuration</a> ·
  <a href="#how-it-compares">Comparison</a> ·
  <a href="#faq">FAQ</a> ·
  <a href="README.ko.md">한국어</a>
</p>

---

Every new agent session starts from nothing. It re-reads the same 3,000-token files, re-runs the same
searches and re-discovers the same pitfalls — and you pay for every token of it. When several agents work
on one machine, they can't see what the others learned, or that another one is editing the same file right now.

memdex is a small MCP server that fixes both:

- **A file summary written once stays valid until the file's content changes.** Summaries are keyed to the
  sha256 of the content, not the path. The next session — or the next agent — gets a 100-token summary
  instead of the 3,000-token file, and is told the moment it goes stale.
- **Notes know when they rot.** Decisions, pitfalls and handoffs cite the files they're based on; when those
  files change, the note is flagged.
- **Agents coordinate.** `claim` what you're editing, `post` to other agents, read your `inbox`, leave a
  `handoff` for whoever comes next. All worktrees of a repository share one memory.

```text
$ memdex file src/store.py
src/store.py · python · 444 lines · sha 3adeaf13
summary (claude@memdex, 2h ago, matches current content):
SQLite store. Tables: files, summaries (keyed by sha), symbols, notes, messages, claims, fts.
index() skips files whose stat is unchanged. search() fuses FTS5 and embeddings with RRF.
outline: class Store:53; method Store.index:101; method Store.search:280; …
```

That response is 1.5 KB. The file is 22 KB. Nothing was sent to any model to produce it.

On a real 66-file site repo, `memdex bench` measures **154,105 tokens** to read every file versus **3,471 tokens**
of outlines — 98% smaller, before an agent saves a single summary. Run `memdex bench` in your own checkout;
the token count is `chars / 4`, an estimate, and the ratio is the point.

## Quick start

```bash
pipx install memdex-mcp        # PyPI name is memdex-mcp; the command is `memdex`
```

**Claude Code** (user scope, every project):

```bash
claude mcp add memdex --scope user -e MEMDEX_AGENT=claude -- memdex serve
```

**Any other MCP client** — Claude Desktop, Cursor, Codex, Windsurf, DeepSeek harness, …:

```json
{ "mcpServers": { "memdex": { "command": "memdex", "args": ["serve"], "env": { "MEMDEX_AGENT": "codex" } } } }
```

Give each agent its own `MEMDEX_AGENT` name; its id becomes `name@checkout` (e.g. `claude@myrepo-wt`).
`memdex config --agent <name>` prints the snippets above, plus an optional Claude Code `SessionStart` hook
that injects the project brief automatically.

That's it. The server sends its own usage instructions in the MCP `initialize` response, so agents know
the workflow (brief → `file_summary` before reading → `remember` → `handoff`) without extra prompting.

## How it works

```text
          agents (Claude Code, Codex, Cursor, DeepSeek, …)
               │ MCP stdio        │ CLI
               ▼                  ▼
        ┌──────────────── memdex ────────────────┐
        │ project_brief · file_summary · where_is │
        │ read_snippet · search · remember        │
        │ handoff · post/inbox · claim            │
        ├─────────────────────────────────────────┤
        │ incremental index   outlines + symbols  │   only files whose size/mtime
        │ (stat → sha256)     (regex/ast, no LLM) │   moved are re-read
        ├─────────────────────────────────────────┤
        │ summaries keyed by sha256               │   valid until content changes
        │ notes with file refs → stale flags      │
        │ messages, cursors, claims (expiring)    │
        ├─────────────────────────────────────────┤
        │ SQLite WAL · FTS5 trigram · vectors     │   ~/.memdex/memdex.db
        └─────────────────────────────────────────┘
```

| | What it does | Borrowed from |
|---|---|---|
| **Content-hash summary cache** | A summary is stored under the file's sha256. Same content in another worktree or branch shares it; changed content gets "no summary yet, here is the old one and the outline". | content-addressed storage |
| **Incremental index** | `git ls-files` (honours `.gitignore`), then only files whose size or mtime moved are read. An 800-file repo re-indexes in ~0.2 s. | [Everything](https://www.voidtools.com/)'s USN-journal approach |
| **Outlines + symbol map** | Docstring/comment head plus classes, functions and line numbers for 30+ languages (Python via `ast`, the rest via per-language regexes — no tree-sitter, no parser install). `where_is` replaces repeated grepping. | Serena / repo maps |
| **Bounded reads** | `read_snippet` returns ~256 tokens around a match or a line instead of the whole file. | [Kensaku](https://github.com/yjid/kensaku) |
| **Rot-aware notes** | `remember` links a note to files; `search` and `project_brief` show "⚠ changed since" when they move. Notes are append-only (`supersedes`), so concurrent writers never clobber each other. | Basic Memory, mem0 |
| **Agent coordination** | `claim` with expiry and overlap warnings; `post`/`inbox` with per-agent cursors; `handoff` as the first thing the next session sees. | — |
| **Hybrid search** | FTS5 trigram (works for Korean, Japanese and Chinese; 2-character terms fall back to LIKE) fused with optional local embeddings via reciprocal rank fusion. | claude-context |
| **Whole-machine content** | If [Kensaku](https://github.com/yjid/kensaku) is installed, `search` also returns full-text, OCR and semantic hits from PDFs, Office files and screenshots. | Kensaku |

Supported outline languages: Python, JavaScript/TypeScript, Vue, Svelte, Go, Rust, Java, Kotlin, Scala,
C#, Swift, Dart, C, C++, Ruby, PHP, Lua, GDScript, Elixir, Clojure, Zig, Julia, R, Haskell, Groovy,
Protobuf, GraphQL, SQL, shell, PowerShell, Markdown.

## Tools

| Tool | When | What you get |
|---|---|---|
| `project_brief` | Start of session | Last handoff, pitfalls, decisions, todos, unread messages, who is editing what. Refreshes the index. |
| `file_summary` | Before reading a file | Cached summary if the content is unchanged, otherwise the old summary (marked stale) and a free outline. |
| `file_summary_save` | After reading a file | Stores 2–6 lines for everyone, keyed to the content hash. |
| `where_is` | "Where is X defined?" | `path:line kind name` matches. |
| `read_snippet` | Reading one part of a file | A bounded slice around `query` or `line`. |
| `search` | Before exploring from scratch | Notes, handoffs and summaries; keyword + semantic; Kensaku hits when available. |
| `remember` / `note` | Something non-obvious | Save / read / archive a `note`, `decision`, `pitfall` or `todo`, optionally linked to files. |
| `handoff` | End of session | Done / next / decisions / pitfalls; releases your claims. |
| `post` / `inbox` | Talking to other agents | Broadcast or `to: "deepseek"`; `inbox` marks read unless `peek`. |
| `claim` | Before editing | Announce paths for N minutes; warns about other agents' overlapping claims. |

The 12 tool schemas cost about 1,000 tokens per request. Responses are short plain text — every byte is a token.

## CLI

Everything the tools do is also a command, for shell-only agents, hooks and humans:

```bash
memdex brief --agent codex              # start of session
memdex file src/store.py                # cached summary + outline
memdex file src/store.py --summary "…"  # save a summary
memdex snippet src/store.py --query "def index"
memdex search "locked"
memdex remember pitfall "WAL mode needed" --body "…" --files src/store.py
memdex claim src/store.py --intent "refactor"
memdex post "store.py is mine for an hour" --to claude
memdex inbox
memdex handoff "Done X" --next "Y" --pitfalls "Z"
memdex index                            # refresh the index for the current project
memdex export --out notes/              # notes as Markdown, one file each
memdex stats
memdex bench                            # what the outlines save on this repo
memdex prune --dry-run                  # drop index rows of deleted projects
memdex doctor                           # database, schema, project index, optional integrations
```

## Measure it on your repo

The first thing anyone asks is "how much does this actually save?". Run it yourself:

```bash
cd your-repo && memdex bench
```

```
your-repo: 812 files · 3.4 MB indexed in 0.21s (812 changed)
reading every file whole: ~871,000 tokens
outline instead:          ~96,120 tokens  (89% smaller; 640 files have symbols)
biggest wins (file → outline):
  src/generated/api.ts                            144.0 KB →    1.6 KB  ( 99% smaller)
  src/store.ts                                     22.2 KB →    1.0 KB  ( 95% smaller)
```

`--json` prints the same numbers for scripts. Tokens are estimated as `chars / 4`; the ratio is the point,
not the absolute number — and `file_summary` gets smaller still once agents save real 2–6 line summaries.

## Maintenance

One SQLite file is shared by every project on the machine, so it grows. `memdex prune` drops index rows for
project directories that no longer exist, then VACUUMs:

```bash
memdex prune --dry-run     # report only
memdex prune               # drop stale file index, VACUUM
memdex prune --all         # also notes/messages/claims of missing projects (destructive)
```

## Configuration

| Variable | Default | Meaning |
|---|---|---|
| `MEMDEX_AGENT` | `agent` (or the MCP client's name) | Who this agent is. Shown on notes, messages and claims. |
| `MEMDEX_HOME` | `~/.memdex` | Where `memdex.db` lives. Nothing is ever written inside a repository. |
| `MEMDEX_PROJECT` | current directory | Project root, when the server is not started inside it. |
| `MEMDEX_EMBED` | off | `ollama:<model>` turns on semantic search, e.g. `ollama:bge-m3` (multilingual). |
| `MEMDEX_OLLAMA_URL` | `http://localhost:11434` | Ollama endpoint. Unreachable → silent fallback to keyword search. |
| `MEMDEX_KENSAKU` | `kensaku-cli` on PATH | Path to Kensaku's CLI, or `off`. |

**What is never read:** files that look like secrets (`.env*`, `*.pem`, `*.key`, `*secret*`, `*credential*`,
`.npmrc`, …), binaries, lockfiles, files over 512 KB and anything git ignores.

**Project identity:** the git common directory. All worktrees of a repository share notes, messages and claims;
each worktree keeps its own file index.

## Limits (read this before adopting it)

memdex is honest about what it is not:

- **The bench baseline is generous.** `memdex bench` compares "read every file whole" with "take the outline".
  A real agent greps and reads slices, so your actual saving is smaller than 98%. The win that does hold is that
  nobody re-discovers the same file, symbol or pitfall twice.
- **Nothing is shared between machines.** One SQLite file, local only. There is no team sync, no cloud, no SSO —
  by design, but it does mean it cannot replace a team knowledge base.
- **It coordinates, it does not lock.** `claim` warns about overlapping edits; it cannot stop two agents writing
  the same file. Git is still the source of truth.
- **A tiny repo may not need it.** Under ~20 files, a hand-written `AGENTS.md` is cheaper than any tool.
- **It is young.** One maintainer, schema v1, no migration history yet (the version is tracked in
  `PRAGMA user_version`, and a newer database is refused rather than silently corrupted).
- **Outlines are regex-level, not semantic.** Python uses `ast`; everything else is per-language regexes. Expect
  good results on normal code and occasional misses in exotic syntax. `where_is` still falls back to substring search.

## How it compares

memdex is deliberately small. These tools are good at things memdex doesn't try to do, and several of them inspired it.

| | Focus | Dependencies | Relationship |
|---|---|---|---|
| **memdex** | Cross-session, cross-agent memory: content-hash summaries, rot-aware notes, coordination | none | — |
| [Serena](https://github.com/oraios/serena) | Precise symbol navigation and editing through language servers | LSP servers per language | Use both: Serena for editing, memdex for memory. memdex's `where_is` is a regex-level stand-in. |
| [Basic Memory](https://github.com/basicmachines-co/basic-memory) | Markdown knowledge base with a graph of notes | Python packages, Markdown files in your project | memdex keeps notes out of the repo and ties them to file hashes. |
| [mem0](https://github.com/mem0ai/mem0) | Memory layer for LLM apps, hosted or self-hosted | vector DB / LLM | memdex is local-only and aimed at coding agents on one machine. |
| [claude-context](https://github.com/zilliztech/claude-context) | Vector search over a codebase | Milvus/Zilliz, embedding API | memdex searches notes and summaries; code search stays keyword + symbols, optionally embeddings via Ollama. |
| [Kensaku](https://github.com/yjid/kensaku) | Desktop search: file names, PDF/Office text, OCR, semantic, for humans and agents | Rust desktop app | Complementary: memdex bridges to it for whole-machine content search. |

## FAQ

**Does anything leave my machine?** No. SQLite file, local subprocesses, optional local Ollama. No telemetry.

**Who writes the summaries?** The agents, when they read a file that has no fresh summary. The server's
instructions ask for 2–6 lines. You can also write them: `memdex file path --summary "…"`.

**What if two agents edit the same file?** `claim` warns, it doesn't lock. memdex coordinates; it doesn't
replace git.

**How much context does it cost?** About 1,000 tokens of tool schemas per request, a few hundred for
`project_brief` (hard-capped at 4,000 chars; `memdex brief --max-chars 0` shows everything).
It pays for itself the first time a file isn't re-read.

**Something is broken — what do I run?** `memdex doctor`. It reports the database path, size, schema version,
whether it is writable, whether the current project is indexed, and which optional integrations are on.

**Can I see or edit the memory?** `memdex export` writes every note as a Markdown file. The database is plain
SQLite. Delete `~/.memdex` to start over.

**Why not just a vector database?** Exact names beat embeddings for code; embeddings help for fuzzy
recollection of notes. memdex does keyword + symbols by default and adds vectors only when you turn them on.

## Contributing

```bash
git clone https://github.com/ChoYugyeong/memdex && cd memdex
pip install -e .
python -m unittest discover tests     # 88 tests, ~9 s, spawns real processes for the concurrency suite
```

Ground rules are short: no runtime dependencies, keep tool descriptions terse (they are tokens on every
request), and every outline regex captures the symbol name in group 1. See [CONTRIBUTING.md](CONTRIBUTING.md).

memdex was built by Claude Code and DeepSeek working on the same checkout — coordinated through memdex itself.

## License

[MIT](LICENSE)
