mempal
Memory framework
First committed by ZhangHanDong
Published in ZhangHanDong/mempal. Publisher page
284 GitHub stars
What it is
AI Agent Memory
AutoGineer overview, from the brain’s own files
Mempal is a project memory system designed for coding agents, implemented as a single binary. It enables agents to store, search, and retrieve decision context across sessions. The system utilizes a hybrid search approach combining BM25 keyword matching and vector semantic search, alongside a knowledge graph for tracking entity relationships. It includes a self-describing protocol that allows agents to understand how to interact with the memory system without manual system prompt configuration. Mempal supports cross-project tunnels, multilingual embedding, and collaborative agent workflows through inbox-based handoffs.
How it works
Memory model: Hybrid
AutoGineer overview, from the brain’s own files
Mempal stores data in a SQLite database located at ~/.mempal/palace.db. It ingests project information by chunking and embedding content, which is then searchable via CLI or MCP tools. The system uses a memory protocol to guide agent behavior, such as verifying facts before ingestion and citing sources. It supports collaborative agent interactions by allowing agents to push messages to a per-project inbox, which are then processed via hooks during user prompt submission. The knowledge graph tracks triples with temporal validity, and the system provides tools for fact-checking and context assembly.
| Folder | Role | Files |
|---|---|---|
| .claude | agent-config | 2 |
| .github | agent-config | 3 |
| docs | docs | 129 |
| hooks | hooks | 2 |
| src | source-code | 30 |
| tests | tests | 31 |
| benchmarks | folder | 1 |
| books | folder | 41 |
| crates | folder | 71 |
| specs | folder | 131 |
The agent writes
- record_checked evidence: AGENTS.md
Requirements
Runtimes: Rust
Databases: SQLite
Works with: Claude Code, OpenAI Codex, GitHub Copilot, Cursor, Kiro, OpenCode, Amp, Cline, JetBrains Junie, Devin (ex-Windsurf)
Set it up
This brain runs code automatically: 2 hooks (claude-code). Review .claude/settings.json before opening the folder in Claude Code. No step below turns a hook on for you.
.claude/settings.json:if echo "$TOOL_INPUT" | grep -q 'git commit'; then echo 'MEMPAL REMINDER: You just committed code. Call mempal_ingest to save the decision context (what was built, why, what was considered). Rule 4: SAVE AFTER DECISIONS.'; fi.claude/settings.json:bash .claude/hooks/user-prompt-submit.sh
- Not scanned by AutoGineerThe author’s MCP configuration (.mcp.json) also starts it in a way AutoGineer does not offer. Read that file: AutoGineer did not scan that path; what it runs is listed under “This brain runs”. https://github.com/ZhangHanDong/mempal/blob/9ed705d78321daf5878e9579777b1a471e97c6f1/.mcp.json
- Not scanned by AutoGineerThe author’s README also describes installing it with cargo. Read its install section: AutoGineer did not scan that path. https://github.com/ZhangHanDong/mempal/blob/9ed705d78321daf5878e9579777b1a471e97c6f1/README.md#quick-start
First committed by ZhangHanDong. Published in ZhangHanDong/mempal. Licence: MIT License.
Usage
AutoGineer overview, from the brain’s own files
- Initialize project memory for a directory
- Ingest project files into a specific wing
- Perform hybrid search for past decisions
- Fact-check assertions against the knowledge graph
- Collaborate between agents using inbox pushes
- Manage knowledge lifecycle and anchor publication
- “mempal search "auth decision clerk"”
- Returns past decisions related to authentication and Clerk, including source citations.
- “mempal fact-check path/to/file”
- Identifies potential contradictions like similar name conflicts or stale facts against the knowledge graph.
Documentation by ZhangHanDong
mempal
Image: Crates.io Image: Downloads Image: docs.rs Image: CI Image: Release Image: License: MIT
Project memory for coding agents. Single binary, cargo install mempal, find past decisions with citations in seconds.
Latest release: v0.9.1 (2026-08-19).
What It Does
Agent writes code → commits → mempal saves the decision context
Next session (any agent) → mempal search → finds the decision with source citationHybrid search: BM25 keyword matching + vector semantic search, merged via Reciprocal Rank Fusion
Knowledge graph: subject-predicate-object triples with temporal validity (valid_from/valid_to)
Cross-project tunnels: automatic discovery when the same room appears in multiple wings
Self-describing protocol: MEMORY_PROTOCOL embedded in MCP ServerInfo teaches any agent how to use mempal — no system prompt configuration required
Multilingual: model2vec-rs (BGE-M3 distilled) as default embedder, zero native dependencies
Single file: everything lives in
~/.mempal/palace.db(SQLite + sqlite-vec)
Quick Start
cargo install mempal --version 0.9.1 --locked
mempal init ~/code/myapp
mempal ingest ~/code/myapp --wing myapp
mempal search "auth decision clerk"
mempal wake-upWith REST support:
cargo install mempal --version 0.9.1 --locked --features restFrom a source checkout:
cargo install --path . --lockedConfiguration
Config at ~/.mempal/config.toml (optional, defaults work without it):
db_path = "~/.mempal/palace.db"
[embed]
backend = "model2vec" # default, zero native deps
# model = "minishlab/potion-multilingual-128M" # default multilingual model (1024d)Other backends:
# Local ONNX (requires --features onnx)
[embed]
backend = "onnx"
# External API
[embed]
backend = "api"
api_endpoint = "http://localhost:11434/api/embeddings"
api_model = "nomic-embed-text"
dimensions = 768 # optional; defaults to 384 when omittedCommands
| Command | Purpose |
|---|---|
mempal init <DIR> [--dry-run] | Infer wing/rooms from project tree |
mempal ingest <DIR> --wing <W> [--dry-run] | Chunk, embed, and store |
mempal search <QUERY> [--wing W] [--room R] [--json] | Hybrid search (BM25 + vector + RRF) |
mempal wake-up [--format aaak] | Context refresh, sorted by importance |
mempal compress <TEXT> | AAAK format output |
mempal delete <DRAWER_ID> | Soft-delete a drawer |
mempal purge [--before TIMESTAMP] | Permanently remove soft-deleted drawers |
mempal kg add <S> <P> <O> | Add a knowledge graph triple |
mempal kg query [--subject S] [--predicate P] | Query triples |
mempal kg timeline <ENTITY> | Chronological view of an entity |
mempal kg stats | Knowledge graph statistics |
mempal tunnels | Cross-wing room links |
mempal taxonomy list / edit | Manage routing keywords |
mempal reindex | Re-embed all drawers after model change |
mempal status | DB stats, schema version, scopes |
mempal serve [--mcp] | MCP server (+ REST with feature) |
mempal cowork-install-hooks [--global-codex] | Install UserPromptSubmit hooks for Claude Code (+ optional Codex merge) |
mempal cowork-drain --target <claude|codex> | Drain inbox messages (for hook use; exits 0 on any failure) |
mempal cowork-status --cwd <PATH> | Read-only view of both inboxes at <PATH> |
mempal fact-check [PATH|-] [--wing W] [--room R] [--now <UNIX_SECS>] | Offline contradiction check against KG triples + known entities |
mempal bench longmemeval <FILE> | LongMemEval retrieval benchmark |
Project ignore rules
mempal init <DIR> and directory-mode mempal ingest <DIR> use the target
project's ignore rules by default. They respect .gitignore, .git/info/exclude,
global Git excludes, and a root-level .mempalignore. Built artifacts that should
never become project memory can be listed in .mempalignore without changing the
project's Git behavior.
Use --ignore-file <PATH> to add one or more extra ignore files for a run. Use
--no-gitignore or --no-mempalignore to disable either default source. Explicit
file ingest remains explicit: mempal ingest path/to/file --wing <W> still ingests
that file even if the project ignore rules would skip it during directory traversal.
MCP Server (10 tools)
mempal serve --mcp exposes these tools via Model Context Protocol:
| Tool | Purpose |
|---|---|
mempal_status | State + protocol + AAAK spec (teaches agent on first call) |
mempal_search | Hybrid search with tunnel hints, citations, and AAAK-derived structured signals |
mempal_ingest | Store memories with optional importance (0-5) and dry_run; reports lock_wait_ms when concurrent ingest was observed |
mempal_delete | Soft-delete with audit trail |
mempal_taxonomy | List or edit routing keywords |
mempal_kg | Knowledge graph: add/query/invalidate/timeline/stats |
mempal_tunnels | Cross-wing room discovery |
mempal_peek_partner | Read partner agent's live session (Claude ↔ Codex), pure read, never writes |
mempal_session_peek | Read an explicit Claude/Codex local session by concrete tool + cwd, including same-tool cross-project reads |
mempal_cowork_push | Send a short handoff message to partner agent's inbox (at-next-submit delivery) |
mempal_fact_check | Offline contradiction detection vs KG triples + known entities (similar-name, relation mismatch, stale facts) |
The server embeds MEMORY_PROTOCOL (11 behavioral rules) in the MCP initialize.instructions field. Any MCP client learns the workflow automatically.
Memory Protocol
mempal teaches agents these rules through self-description:
FIRST-TIME SETUP — call
mempal_statusto discover wings before filteringWAKE UP — different clients have different pre-load mechanisms
VERIFY BEFORE ASSERTING — search before stating project facts
QUERY WHEN UNCERTAIN — search on "why did we...", "last time we..." 3a. TRANSLATE TO ENGLISH — translate non-English queries before searching
SAVE AFTER DECISIONS — persist rationale, not just outcomes
CITE EVERYTHING — reference drawer_id and source_file 5a. KEEP A DIARY — record behavioral observations in wing="agent-diary"
PARTNER AWARENESS — use
mempal_peek_partnerfor live partner-agent session,mempal_session_peekfor explicit same-tool/cross-project local sessions, and mempal search only for crystallized drawersDECISION CAPTURE —
mempal_ingestis for firm decisions only; include partner input when peek informed the callCOWORK PUSH — use
mempal_cowork_pushas the SEND primitive in the SEND/READ/PERSIST triad; at-next-submit delivery, not real-timeVERIFY BEFORE INGEST — call
mempal_fact_checkbefore persisting a decision that asserts entity relationships; it catches similar-name typos, relation mismatches against the KG, and stale facts with expiredvalid_to
Agent Cowork (P6 peek + P8 push)
Two coding agents (Claude Code and Codex) can collaborate on the same repo through a per-project inbox + hook-driven injection channel, on top of mempal_peek_partner (read live partner session), mempal_session_peek (read an explicit local session by concrete tool + cwd), and mempal_cowork_push (send ephemeral handoff).
Install hooks once per repo (run at the repo root):
mempal cowork-install-hooks --global-codexThis writes:
.claude/hooks/user-prompt-submit.sh+ merges a registration entry into.claude/settings.jsonso Claude Code fires the hook on every user prompt.~/.codex/hooks.jsonUserPromptSubmit entry so Codex fires the same drain on every user prompt.
The --global-codex part is optional. The re-run is idempotent and self-heals stale/wrong drain entries — re-installing after a mempal upgrade is always safe.
Delivery is at-next-UserPromptSubmit, not real-time: a push from Claude to Codex becomes visible only when the Codex user submits their next prompt, at which point the hook drains the inbox and prepends the message as additionalContext on that turn.
Check inbox state at any time without draining:
mempal cowork-status --cwd "$PWD"Known limitations
Codex feature flag dependency: Codex's hooks runtime is gated behind the
codex_hooksfeature flag (currently "under development" in shippedcodex-cli). If the flag is off, Codex silently ignores~/.codex/hooks.json.install-hooksdetects this and prints a warning with the activation command:codex features enable codex_hooks.Two Claude-side artifacts: Claude Code does not auto-discover hook scripts by filename. Both
.claude/hooks/user-prompt-submit.shand the matching entry in.claude/settings.jsonare required.install-hookswrites both; do not remove either by hand.TUI restart needed after config changes on the Codex side: Codex reads
config.toml+hooks.jsonat process startup only. After enabling the feature flag or runninginstall-hooks, fully quit and relaunch the Codex TUI before expecting hooks to fire.MCP server re-spawn: Claude Code spawns the mempal MCP server at client startup. After upgrading the mempal binary (
cargo install ...), restart Claude Code so the MCP server respawns and exposes newly added tools likemempal_cowork_pushormempal_fact_check.Bidirectional scope:
mempal_cowork_pushcurrently requires an MCP client identifying itself asclaude-codeorcodex(or their aliases). Generic MCP clients cannot push because caller identity is required to fill thefromfield and enforce self-push rejection. This is by design for the Claude ↔ Codex pair.
Concurrent Ingest Safety (P9-B)
Two agents writing to the same source simultaneously used to be a TOCTOU race: both would pass the dedup check, both would insert, producing duplicate drawers or mismatched vectors. Since 0.4.0, mempal_ingest and ingest_file_with_options acquire a per-source advisory lock before entering the dedup + insert critical section.
Lock files live at
~/.mempal/locks/<16-hex>.lock, created lazily, released on guard drop.5 s timeout, 50 ms retry + jitter;
LockError::Timeoutsurfaces as aningesterror.Every non-dry-run response carries
lock_wait_ms: Option<u64>so agents can detect contention.Dry-run does not acquire the lock (no writes, no race).
Unix only in 0.4.0. On Windows the lock path is a no-op fallback;
LockFileExsupport is tracked for a follow-up.
Offline Fact Checking (P9-A)
mempal_fact_check — and its CLI counterpart mempal fact-check — compare a text blob against the existing KG triples + the entity registry derived from recent drawers. It flags three issue classes, all deterministic and zero-LLM:
| Issue | Trigger |
|---|---|
SimilarNameConflict | Text mentions a name within Levenshtein distance ≤ 2 of a known entity, and the names are not equal. |
RelationContradiction | Text asserts a predicate (e.g. brother_of) that's in the incompatibility dictionary against an existing KG triple with the same (subject, object) endpoints. |
StaleFact | Text asserts a triple whose KG row has valid_to < now (Unix seconds). |
Extracted triples today cover three narrow patterns: "X is Y's ROLE", "X works at / for Y", and "X is [the|a|an] ROLE of Y". Unknown sentence shapes are silently ignored, so the tool errs toward under-reporting rather than false positives.
Protocol Rule 11 guides agents to run this before ingesting a decision that asserts entity relationships. See specs/p9-fact-checker.spec.md for the full contract.
Search Architecture
query → BM25 (FTS5) → ranked by keyword match
→ Vector (sqlite-vec) → ranked by semantic similarity
→ RRF Fusion (k=60) → merged ranking
→ Wing/Room filter → scoped results
→ Tunnel hints → cross-project referencesKnowledge Graph
mempal kg add "Kai" "recommends" "Clerk"
mempal kg add "Clerk" "replaced" "Auth0" --source-drawer drawer_xxx
mempal kg timeline "Kai"
mempal kg statsTriples support temporal validity — relationships can be invalidated when they expire.
Agent Diary
Cross-session behavioral learning — agents record observations, lessons, and patterns:
# Search diary entries
mempal search "lesson" --wing agent-diary
mempal search "pattern" --wing agent-diary --room claudeDiary entries use the existing mempal_ingest tool with wing="agent-diary" and room=agent-name. MEMORY_PROTOCOL Rule 5a teaches agents to write diary entries. Integrates with Claude Code's auto-dream for automatic memory consolidation.
Ingest Formats (5)
| Format | Auto-detected by |
|---|---|
| Claude Code JSONL | type + message fields |
| ChatGPT JSON | Array or mapping tree |
| Codex CLI JSONL | session_meta + event_msg entries |
| Slack DM JSON | type: "message" + user + text |
| Plain text | Fallback |
AAAK Compression
Output-only format readable by any LLM without decoding:
mempal compress "Kai recommended Clerk over Auth0 based on pricing and DX"
# V1|manual|compress|1744156800|cli
# 0:KAI+CLK+AUT|kai_clerk_auth0|"Kai recommended Clerk over Auth0..."|★★★★|determ|DECISIONChinese text uses jieba-rs POS tagging for proper word segmentation.
Architecture
| Crate | Responsibility |
|---|---|
mempal | Installable CLI package, REST entrypoint, and legacy facade paths |
mempal-embed | Public Embedder / EmbedderFactory traits, API embedder, model2vec and ONNX implementations |
mempal-search-core | Public FTS5 query escaping and RRF rank-fusion primitives |
mempal-agent-memory | Public agent-memory domain types and anchor helpers |
mempal-mcp-protocol | Public self-describing MEMORY_PROTOCOL text |
mempal-store-sqlite | Public SQLite storage layer: schema, migrations, Database, FTS5, sqlite-vec, KG, tunnels, cards, adoption tables |
mempal-runtime | Public runtime workflows: ingest, search orchestration, context, brief, knowledge, factcheck, projects, cowork, doctor, AAAK |
mempal-mcp-server | Public MCP server adapter and tool wiring for the runtime |
Key design choices:
model2vec-rs default embedder — zero native deps, multilingual (BGE-M3 distilled)
ort (ONNX) available behind
onnxfeature flag for max qualityFTS5 for BM25 keyword search — synced via SQLite triggers
Soft-delete with audit trail —
mempal delete+mempal purgeImportance ranking — drawers have 0-5 importance, wake-up sorts by importance
Semantic dedup — ingest warns (doesn't block) when similar content exists
Public workspace crates — reusable libraries are maintained in this repo and published as versioned crates while
cargo install mempalremains the CLI path. P114 keeps the split coarse: storage, runtime, and MCP server are separate crates, but feature families such as knowledge, cowork, and context remain inmempal-runtime.
Development
cargo test --workspace
cargo test --workspace --all-features
cargo clippy --workspace --all-targets --all-features -- -D warnings
cargo fmt --all --checkAfter changing the embedding model or dimensions, re-embed existing drawers:
mempal reindexDocs
Usage guide:
docs/usage.mdAAAK dialect:
docs/aaak-dialect.mdSpecs (internal agent-spec contracts, on GitHub): https://github.com/ZhangHanDong/mempal/tree/main/specs
Plans (internal implementation plans, on GitHub): https://github.com/ZhangHanDong/mempal/tree/main/docs/plans
Benchmark:
benchmarks/longmemeval_s_summary.md— includes the older 384d baseline and the newer model2vec 256d run
Book: MemPalace — Reforging Memory in Rust
mempal 的设计分析和完整技术叙事,收录在《MemPalace: AI 记忆的第一性原理》Part 10(第 26-30 章):
| 章节 | 内容 |
|---|---|
| 第 26 章 | 为什么用 Rust 重铸 — 触发点、重写判断、语言选择 |
| 第 27 章 | 保留了什么、改变了什么 — 5 维度对比 + 架构图 |
| 第 28 章 | 自描述协议 — MEMORY_PROTOCOL、7 条规则、agent 生命周期 |
| 第 29 章 | 多 Agent 协作 — Claude↔Codex 接力、反模式发现、agent 日记 |
| 第 30 章 | 诚实的差距 — benchmark 数据、6 个 gap |
README_zh.md
mempal
Image: Crates.io Image: 下载量 Image: docs.rs Image: CI Image: Release Image: License: MIT
Coding agent 的项目记忆工具。单二进制,cargo install mempal,10 秒内带出处找回历史决策。
最新版本:v0.9.1(2026-08-19)。
做什么
Agent 写代码 → 提交 → mempal 保存决策上下文
下一个 session(任何 agent)→ mempal search → 带出处找回决策混合检索:BM25 关键词匹配 + 向量语义搜索,通过 RRF(Reciprocal Rank Fusion)融合
知识图谱:subject-predicate-object 三元组,支持时态验证(valid_from/valid_to)
跨项目隧道:自动发现多个 Wing 中同名 Room 的链接
自描述协议:MEMORY_PROTOCOL 嵌入 MCP ServerInfo,任何 agent 连接后自动学会使用方式——无需系统提示配置
多语言:model2vec-rs(BGE-M3 蒸馏)作为默认嵌入器,零原生依赖
单文件:所有数据在
~/.mempal/palace.db(SQLite + sqlite-vec)
快速开始
cargo install mempal --version 0.9.1 --locked
mempal init ~/code/myapp
mempal ingest ~/code/myapp --wing myapp
mempal search "auth decision clerk"
mempal wake-up启用 REST 支持:
cargo install mempal --version 0.9.1 --locked --features rest从源码 checkout 安装:
cargo install --path . --locked配置
配置文件 ~/.mempal/config.toml(可选,不存在时使用默认值):
db_path = "~/.mempal/palace.db"
[embed]
backend = "model2vec" # 默认,零原生依赖
# model = "minishlab/potion-multilingual-128M" # 默认多语言模型其他后端:
# 本地 ONNX(需要 --features onnx)
[embed]
backend = "onnx"
# 外部 API
[embed]
backend = "api"
api_endpoint = "http://localhost:11434/api/embeddings"
api_model = "nomic-embed-text"
dimensions = 768 # 可选;省略时默认 384命令一览
| 命令 | 用途 |
|---|---|
mempal init <DIR> [--dry-run] | 从项目目录推断 wing/room |
mempal ingest <DIR> --wing <W> [--dry-run] | 分块、嵌入、存储 |
mempal search <QUERY> [--wing W] [--room R] [--json] | 混合检索(BM25 + 向量 + RRF) |
mempal wake-up [--format aaak] | 上下文刷新,按重要性排序 |
mempal compress <TEXT> | AAAK 格式输出 |
mempal delete <DRAWER_ID> | 软删除 |
mempal purge [--before TIMESTAMP] | 永久清除已软删除的记忆 |
mempal kg add <S> <P> <O> | 添加知识图谱三元组 |
mempal kg query [--subject S] [--predicate P] | 查询三元组 |
mempal kg timeline <ENTITY> | 实体的时间线视图 |
mempal kg stats | 知识图谱统计 |
mempal tunnels | 跨 Wing room 链接 |
mempal taxonomy list / edit | 管理路由关键词 |
mempal reindex | 切换模型后重新嵌入所有 drawer |
mempal status | 数据库统计、schema 版本、scope 分布 |
mempal serve [--mcp] | MCP 服务器(+ REST) |
mempal cowork-install-hooks [--global-codex] | 一键安装 Claude Code + Codex 的 UserPromptSubmit hook |
mempal cowork-drain --target <claude|codex> | 排空 inbox(供 hook 调用,任意错误均 exit 0) |
mempal cowork-status --cwd <PATH> | 只读查看双方 inbox 当前状态 |
mempal fact-check [PATH|-] [--wing W] [--room R] [--now <UNIX_SECS>] | 离线矛盾检查(对照 KG 三元组 + 已知 entity) |
mempal bench longmemeval <FILE> | LongMemEval 检索 benchmark |
项目 ignore 规则
mempal init <DIR> 和目录模式的 mempal ingest <DIR> 默认复用目标项目自己的
ignore 规则。它们会尊重 .gitignore、.git/info/exclude、全局 Git exclude,
以及项目根目录的 .mempalignore。只想从项目记忆中排除的编译产物、缓存目录或
生成文件,可以写进 .mempalignore,不需要改变项目本身的 Git 行为。
单次运行可以用 --ignore-file <PATH> 追加一个或多个 ignore 文件。需要关闭默认
来源时,用 --no-gitignore 或 --no-mempalignore。显式文件导入保持显式:
mempal ingest path/to/file --wing <W> 即使在目录遍历时会被 ignore 规则跳过,
仍然会导入这个文件。
MCP 服务器(10 个工具)
mempal serve --mcp 通过 Model Context Protocol 暴露:
| 工具 | 用途 |
|---|---|
mempal_status | 状态 + 协议 + AAAK spec(首次调用即教会 agent) |
mempal_search | 混合检索 + tunnel 提示 + 引用 + P7 的 AAAK 结构化 signals |
mempal_ingest | 存记忆(可选 importance 0-5 + dry_run);并发写入时返回 lock_wait_ms |
mempal_delete | 软删除 + 审计 |
mempal_taxonomy | 路由关键词管理 |
mempal_kg | 知识图谱:add/query/invalidate/timeline/stats |
mempal_tunnels | 跨 Wing room 发现 |
mempal_peek_partner | 读 partner agent 当前 session(Claude ↔ Codex),纯只读 |
mempal_session_peek | 按明确 tool + cwd 读取本地 Claude/Codex session,支持同工具跨项目读取 |
mempal_cowork_push | 向 partner agent inbox 投递短消息(at-next-submit 交付) |
mempal_fact_check | 离线矛盾检测(相似名 / 关系对立 / 时态失效,纯本地无 LLM) |
服务器在 MCP initialize.instructions 中嵌入 MEMORY_PROTOCOL(11 条行为规则),任何 MCP 客户端自动接收。
记忆协议
mempal 通过自描述教 agent 这些规则:
首次设置 — 调用
mempal_status发现 wing 名称唤醒 — 不同客户端有不同的预加载机制
断言前验证 — 陈述项目事实前先搜索
不确定时查询 — "我们为什么..."、"上次我们..." 3a. 翻译为英文 — 非英文查询先翻译再搜索
决策后保存 — 保存理由,不仅是结果
引用一切 — 引用 drawer_id 和 source_file 5a. 记日记 — session 结束时在
wing="agent-diary"下记行为观察Partner 感知 — 问 partner 当前状态用
mempal_peek_partner(live session),明确同工具/跨项目本地 session 用mempal_session_peek,问已沉淀决策才用mempal_search决策沉淀 —
mempal_ingest只存已达成的硬决策;partner 参与时要把 partner 的关键贡献带进 drawer 正文COWORK PUSH —
mempal_cowork_push是 SEND 原语,at-next-submit 交付、非实时;别用它做该 ingest 的事入库前校验 — 在 ingest 含 entity 关系断言的决策前调
mempal_fact_check,它抓相似名拼错、KG 关系矛盾、以及valid_to已过期的 stale fact
并发 Ingest 安全(P9-B)
两个 agent 同时向同一个 source 写入以前是 TOCTOU race:两边都通过 dedup 检查、都 insert,结果重复 drawer 或 vector 错配。从 0.4.0 起 mempal_ingest 和 ingest_file_with_options 在进入 dedup + insert 临界区前获取 per-source 建议锁。
锁文件
~/.mempal/locks/<16-hex>.lock,懒建,guard drop 时 OS 自动释放默认 5s 超时,50ms 重试 + jitter;超时返回
LockError::Timeout非 dry-run 的 ingest response 携带
lock_wait_ms: Option<u64>,agent 可据此察觉并发dry-run 不占锁(零写入,零 race)
0.4.0 仅覆盖 Unix(
flock内联 extern,不引 libc crate);Windows 暂为 no-op 占位,后续用LockFileEx补齐
离线事实核查(P9-A)
mempal_fact_check(以及 CLI mempal fact-check)对一段文本在现有 KG triples + 最近 drawer 聚合的 entity registry 上做比对,标记三类确定性问题(不调 LLM、不走网络):
| 问题类型 | 触发条件 |
|---|---|
SimilarNameConflict | 文本中的名字与已知 entity Levenshtein 距离 ≤ 2 且不相等 |
RelationContradiction | 文本断言的 predicate 与 KG 中同 (subject, object) 的现存 triple 在不兼容字典中 |
StaleFact | 文本断言的三元组在 KG 中 valid_to < now(Unix 秒) |
文本 → 三元组当前支持三种窄模式:"X is Y's ROLE"、"X works at / for Y"、"X is [the|a|an] ROLE of Y"。不认得的句型静默返回空,倾向少报不多报。协议 Rule 11 指导 agent 在 ingest 含实体关系断言的决策前跑一次。完整契约见 specs/p9-fact-checker.spec.md。
检索架构
query → BM25 (FTS5) → 关键词排序
→ Vector (sqlite-vec) → 语义相似度排序
→ RRF 融合 (k=60) → 合并排序
→ Wing/Room 过滤 → 范围限定
→ Tunnel 提示 → 跨项目引用知识图谱
mempal kg add "Kai" "recommends" "Clerk"
mempal kg add "Clerk" "replaced" "Auth0" --source-drawer drawer_xxx
mempal kg timeline "Kai"
mempal kg stats三元组支持时态验证——关系过期后可标记为无效。
Agent 日记
跨 session 行为学习——agent 记录观察、教训和模式:
# 搜索日记
mempal search "lesson" --wing agent-diary
mempal search "pattern" --wing agent-diary --room claude日记通过现有的 mempal_ingest 工具写入,wing="agent-diary",room=agent 名字。MEMORY_PROTOCOL Rule 5a 教 agent 在 session 结束时写日记。可与 Claude Code 的 auto-dream 集成,实现自动记忆整理。
导入格式(5 种)
| 格式 | 自动检测方式 |
|---|---|
| Claude Code JSONL | type + message 字段 |
| ChatGPT JSON | 数组或 mapping 树 |
| Codex CLI JSONL | session_meta + event_msg 条目 |
| Slack DM JSON | type: "message" + user + text |
| 纯文本 | 兜底 |
AAAK 压缩
输出格式化器,任何 LLM 无需解码即可阅读:
mempal compress "Kai recommended Clerk over Auth0 based on pricing and DX"
# V1|manual|compress|1744156800|cli
# 0:KAI+CLK+AUT|kai_clerk_auth0|"Kai recommended Clerk over Auth0..."|★★★★|determ|DECISION中文文本使用 jieba-rs 词性标注进行分词。
架构
| Crate | 职责 |
|---|---|
mempal | 可安装 CLI package、REST 入口、legacy facade paths |
mempal-embed | 公共 Embedder / EmbedderFactory trait、API embedder、model2vec 与 ONNX 实现 |
mempal-search-core | 公共 FTS5 query escaping 与 RRF rank-fusion 基础能力 |
mempal-agent-memory | 公共 agent-memory 领域类型与 anchor helper |
mempal-mcp-protocol | 公共自描述 MEMORY_PROTOCOL 文本 |
mempal-store-sqlite | 公共 SQLite 存储层:schema、migration、Database、FTS5、sqlite-vec、KG、tunnels、cards、adoption tables |
mempal-runtime | 公共 runtime workflows:ingest、search orchestration、context、brief、knowledge、factcheck、projects、cowork、doctor、AAAK |
mempal-mcp-server | 公共 MCP server adapter 与工具 wiring |
关键设计:
model2vec-rs 默认嵌入——零原生依赖,多语言(BGE-M3 蒸馏)
ort (ONNX) 通过
onnxfeature flag 可选启用FTS5 BM25 关键词搜索——通过 SQLite 触发器同步
软删除 + 审计日志——
mempal delete+mempal purge重要性排序——drawer 有 0-5 重要性评分,wake-up 按重要性排序
语义去重——ingest 时检测相似内容,warning 但不阻塞
公共 workspace crates——可复用库在同一 repo/workspace 内维护并以 versioned crates 发布,
cargo install mempal继续作为 CLI 安装路径。P114 保持粗粒度拆分:storage、 runtime、MCP server 独立成 crate,但 knowledge、cowork、context 等功能族仍留在mempal-runtime,不继续碎拆。
开发
cargo test --workspace
cargo test --workspace --all-features
cargo clippy --workspace --all-targets --all-features -- -D warnings
cargo fmt --all --check切换嵌入模型后重建向量:
mempal reindex文档
使用指南:
docs/usage.mdAAAK 方言:
docs/aaak-dialect.mdSpec 体系(仓库内部 agent-spec 合约,GitHub 查看):https://github.com/ZhangHanDong/mempal/tree/main/specs
实现计划(仓库内部实现计划,GitHub 查看):https://github.com/ZhangHanDong/mempal/tree/main/docs/plans
Benchmark:
benchmarks/longmemeval_s_summary.md
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Advantages
- Hybrid search combines BM25 and vector semantic search for improved retrieval. evidence: README.md
- Self-describing protocol allows agents to learn interaction rules automatically. evidence: README.md
- Per-source advisory locking prevents race conditions during concurrent agent ingestion. evidence: README.md
Limitations
- Codex integration requires a specific feature flag to be enabled. evidence: README.md
- Bidirectional cowork push is restricted to identified Claude and Codex agents. evidence: README.md
- Advisory locking for concurrent ingest is currently limited to Unix systems. evidence: README.md
Security
Risk level: Low risk
This brain runs
Hooks (2)
.claude/settings.json(PostToolUse):if echo "$TOOL_INPUT" | grep -q 'git commit'; then echo 'MEMPAL REMINDER: You just committed code. Call mempal_ingest to save the decision context (what was built, why, what was considered). Rule 4: SAVE AFTER DECISIONS.'; fi.claude/settings.json(UserPromptSubmit):bash .claude/hooks/user-prompt-submit.sh
MCP servers (1)
.mcp.json(mempal):mempal serve --mcp
Agent instructions that run or fetch something (22)
AGENTS.md:Rust 实现的 coding agent 项目记忆工具。单二进制,`cargo install mempal`,10 秒内带出处找回历史决策。AGENTS.md:| Spec | 状态 | 范围 | |------|------|------| | `specs/p0-core-scaffold.spec.md` | 完成 | workspace 骨架 + SQLite schema | | `specs/p0-embed-trait.spec.md` | 完成 | Embedder trait(model2vec 默认 + ort 可选) | | `specs/p0-ingest.spec.md` | 完成 | 导入管道(格式检测/归一化/分块/存储) | | `specs/p0-search-cli.spec.md` …[+7715 chars]AGENTS.md:`docs/plans/2026-05-26-p98-release-install-doctor.md` — P98 release install doctor(已完成)AGENTS.md:`docs/plans/2026-05-26-p100-guided-maintenance-run.md` — P100 guided maintenance run(已完成)AGENTS.md:`docs/plans/2026-08-18-p117-reindex-atomic-replace.md` — P117 atomic reindex replace + dry-run feasibility report(已完成)AGENTS.md:| 工具 | 作用 | |------|------| | `mempal_status` | 状态 + 协议 + AAAK spec | | `mempal_doctor` | release/install + MCP runtime diagnostics:报告 binary/PATH/schema 兼容性和 required MCP tool/action 能力清单(P99) | | `mempal_search` | 混合检索(BM25 + 向量 + RRF + tunnel hints)+ AAAK 结构化 signals(P7) | | `mempa …[+2688 chars]AGENTS.md:Cargo workspace,root package 仍是 `mempal`,并继续提供 `cargo install mempal` 的 CLI binary。P113/P114 已把可复用边界拆成公开 workspace crates;root crate 现在主要负责 CLI、REST entrypoint、package metadata 和 legacy facade paths。AGENTS.md:**`mempal cowork-install-hooks` 写两件 Claude 侧制品**:`.claude/hooks/user-prompt-submit.sh`(脚本)+ `.claude/settings.json` 下的 `hooks.UserPromptSubmit` 条目(注册)。Claude Code 不按文件名约定自动发现脚本,两件**都必须有**hook 才会 fire。`install-hooks` 已自动处理 + 自愈 stale 条目;请勿手工移除其中任一。AGENTS.md:**Codex 侧依赖 `codex_hooks` feature flag**:shipped `codex-cli ≤ 0.120.0` 该 flag 处于 "under development" 且默认 `false`,此时 Codex runtime 完全忽略 `~/.codex/hooks.json`。`install-hooks` 检测到会打印 warning + 激活命令 `codex features enable codex_hooks`。AGENTS.md:**Codex TUI 进程启动时一次性缓存 config**:改完 `config.toml` 或 `hooks.json`(含 feature flag / install-hooks)后,必须完全退出并重启 Codex TUI;已在跑的进程拿不到新配置。AGENTS.md:**Claude Code 的 MCP server 是 session startup spawn**:`cargo install` 升级 mempal binary 后,Claude Code 还在用旧 MCP server 进程,**不认识新加的工具**(如 `mempal_cowork_push`)。升级后重启 Claude Code,MCP server 会 respawn 到新 binary。CLAUDE.md:Rust 实现的 coding agent 项目记忆工具。单二进制,`cargo install mempal`,10 秒内带出处找回历史决策。CLAUDE.md:| Spec | 状态 | 范围 | |------|------|------| | `specs/p0-core-scaffold.spec.md` | 完成 | workspace 骨架 + SQLite schema | | `specs/p0-embed-trait.spec.md` | 完成 | Embedder trait(model2vec 默认 + ort 可选) | | `specs/p0-ingest.spec.md` | 完成 | 导入管道(格式检测/归一化/分块/存储) | | `specs/p0-search-cli.spec.md` …[+7715 chars]CLAUDE.md:`docs/plans/2026-05-26-p98-release-install-doctor.md` — P98 release install doctor(已完成)CLAUDE.md:`docs/plans/2026-05-26-p100-guided-maintenance-run.md` — P100 guided maintenance run(已完成)CLAUDE.md:`docs/plans/2026-08-18-p117-reindex-atomic-replace.md` — P117 atomic reindex replace + dry-run feasibility report(已完成)CLAUDE.md:| 工具 | 作用 | |------|------| | `mempal_status` | 状态 + 协议 + AAAK spec | | `mempal_doctor` | release/install + MCP runtime diagnostics:报告 binary/PATH/schema 兼容性和 required MCP tool/action 能力清单(P99) | | `mempal_search` | 混合检索(BM25 + 向量 + RRF + tunnel hints)+ AAAK 结构化 signals(P7) | | `mempa …[+2688 chars]CLAUDE.md:Cargo workspace,root package 仍是 `mempal`,并继续提供 `cargo install mempal` 的 CLI binary。P113/P114 已把可复用边界拆成公开 workspace crates;root crate 现在主要负责 CLI、REST entrypoint、package metadata 和 legacy facade paths。CLAUDE.md:**`mempal cowork-install-hooks` 写两件 Claude 侧制品**:`.claude/hooks/user-prompt-submit.sh`(脚本)+ `.claude/settings.json` 下的 `hooks.UserPromptSubmit` 条目(注册)。Claude Code 不按文件名约定自动发现脚本,两件**都必须有**hook 才会 fire。`install-hooks` 已自动处理 + 自愈 stale 条目;请勿手工移除其中任一。CLAUDE.md:**Codex 侧依赖 `codex_hooks` feature flag**:shipped `codex-cli ≤ 0.120.0` 该 flag 处于 "under development" 且默认 `false`,此时 Codex runtime 完全忽略 `~/.codex/hooks.json`。`install-hooks` 检测到会打印 warning + 激活命令 `codex features enable codex_hooks`。CLAUDE.md:**Codex TUI 进程启动时一次性缓存 config**:改完 `config.toml` 或 `hooks.json`(含 feature flag / install-hooks)后,必须完全退出并重启 Codex TUI;已在跑的进程拿不到新配置。CLAUDE.md:**Claude Code 的 MCP server 是 session startup spawn**:`cargo install` 升级 mempal binary 后,Claude Code 还在用旧 MCP server 进程,**不认识新加的工具**(如 `mempal_cowork_push`)。升级后重启 Claude Code,MCP server 会 respawn 到新 binary。
- Low risk: scripts-present (.claude/hooks/user-prompt-submit.sh)
Attribution and licence
- First committed by
ZhangHanDong
- Publisher
- Alex (Community)
- Source
- ZhangHanDong/mempal · commit 9ed705d
- Licence
- MIT License (files served here)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
- Contributors
- ZhangHanDong, LiuZiqi-dual, TigerInYourDream, jolestar, ryushione
AutoGineer is not affiliated with or endorsed by ZhangHanDong.
Install from source
436 of its files are not served here, so there is no ZIP. ZhangHanDong/mempal at 9ed705d