Skip to main content
Glama

scratchbook-mcp

A codebase-memory MCP server for AI coding agents (Claude Code and others): hybrid semantic + BM25 code search, a structural outline, a work journal, and gaze-and-think deep reasoning — over a local LanceDB.

給 AI 編碼代理(Claude Code 等)的程式碼記憶 MCP 伺服器: 混合語意 + BM25 的程式碼搜尋、結構大綱、工作日記,以及 gaze-and-think 深度推理 —— 全部建在本機 LanceDB 上。

License: Apache 2.0 Node


Why / 為什麼

grep/rg only find what you can already name, and mostly within one directory. When an agent works in a large or unfamiliar repo, it spends attention locating code instead of understanding it. scratchbook gives the agent a cross-directory, meaning-based index of the code, a lexical (exact-identifier) arm fused in, a place to write notes it can recall later, and a way to think deeply about a tangled subsystem in a clean, isolated session. It augments grep/Read — it does not replace them.

grep/rg 只找得到你叫得出名字的東西,而且多半困在單一目錄。當代理在龐大或 陌生的 repo 裡工作,注意力都耗在「定位程式碼」而不是「理解它」。scratchbook 給代理 一份跨目錄、以意義為基礎的程式碼索引,融入一條詞彙(精確識別字)臂,一個可日後 回想的筆記空間,以及一種在乾淨隔離的 session 裡把糾結子系統想透的方法。它增強 grep/Read —— 不是取代它們。

Related MCP server: nexus-mcp-ci

Features / 特色

  • Hybrid retrieval / 混合檢索 — semantic (embedding) search fused with lexical BM25 via Reciprocal Rank Fusion. Meaning-based recall and exact-identifier precision (a query for resolveAnnotatedMap surfaces the exact symbol the embedding alone would rank below near-synonyms). Each hit is tagged sem / lex / lex+sem. 語意(向量)搜尋與詞彙 BM25 以 RRF 融合:兼得「概念召回」與「精確識別字」。每筆 結果標記由哪一臂命中(sem / lex / lex+sem)。

  • Zero-dependency fallback / 零依賴降級 — no embedding service? Everything still works in lexical-only mode (BM25 + refs/events/outline/journal); the first index run after an embedder appears auto-upgrades to hybrid. 沒有 embedding 服務也能用:自動進入 lexical-only 模式(BM25 + 交叉引用/outline/ 日誌照常),之後偵測到端點會自動全量升級成混合檢索。

  • Exact cross-reference / 精確交叉引用scratchbook_refs enumerates every definition and reference of an identifier: grep-shaped (LIKE prefilter + line-level regex), deliberately not BM25 — an FTS tokenizer splits snake_case into an OR-flood and top-k truncation silently drops sites. scratchbook_events cross-references string event names (.emit/.on + wrapper methods) into an event → send sites / listen sites table and flags one-sided events — the string edges a syntactic call graph can't see. scratchbook_refs 窮舉一個識別字的所有定義與引用:grep 形而非排序形(LIKE 預過濾 + 行級 regex),刻意不走 BM25 —— FTS tokenizer 會把 snake_case 切成 OR 洪水,top-k 截斷即靜默漏報。scratchbook_events 交叉比對字串事件名 (.emit/.on 與包裝方法),產出「事件 → 發送端/監聽端站點」對照表並標記單邊 事件 —— 這些字串邊是語法呼叫圖看不見的架構。

  • Structural outline / 結構大綱 — each file's imports + top-level symbols with line numbers, to grasp organisation fast. 每個檔案的 imports + 頂層符號 + 行號,快速掌握專案組織。

  • Work journal + recall / 工作日記與回想 — write dated notes (decisions, findings, suspected bugs); recall them later by meaning, with an age shown so stale notes read as old. 寫下有日期的筆記(決策、發現、可疑 bug);日後以語意回想,並顯示年齡讓過時 筆記一眼看得出來。

  • gaze-and-think / 凝視與思考 — dump a tangled problem into a board, then launch a clean, isolated flow session that concentrates solely on it, reasons about the relationships between the pieces, writes inspectable intermediate artifacts, and converges on a synthesis you can persist into recall. 把糾結的問題丟進一個 board,再啟動一個乾淨隔離的心流 session,專注思考各片段間 的關係、產出可檢查的中間產物、收斂成綜合結論,並可持久化進 recall。

  • Control-char-safe snippets / 控制字元安全的片段 — invisible bytes (NUL, …) are rendered cat -A-style (^@) so they can't be misread as spaces. 隱形位元組(NUL 等)以 cat -A 風格顯示(^@),避免被誤讀成空格。

Architecture / 架構

AI agent ──stdio (JSON-RPC)──▶ src/server.mjs  (MCP, 11 tools)
                                     │
     ┌───────────────┬──────────────┼──────────────┬───────────────┬──────────────┐
     ▼               ▼              ▼              ▼               ▼              ▼
 indexer.mjs      store.mjs      embed.mjs      gaze.mjs        walk.mjs      refs.mjs
 walk→chunk       LanceDB        Ollama-style   clean `claude   git ls-files / exact xref:
 →embed→upsert    3 tables +     /api/embed     -p` flow        gitignore-aware LIKE + line
 (incremental)    FTS (BM25)     (bge-m3, 1024) session         chunk.mjs      regex; event
                  ~/.scratchbook                                (symbol-aware)  send/listen
  • Runtime / 執行環境: Node ESM, no build step (node src/server.mjs).

  • Storage / 儲存: one LanceDB at ~/.scratchbook/lancedb, every row namespaced by the canonical (realpath) project root — one server serves every project. 單一 LanceDB,每列以正規化的專案根路徑命名空間 —— 一個伺服器服務所有專案

  • Tables / 資料表: chunks (symbol-aware code chunks + vectors + a BM25 FTS index), files (per-file imports + outline), journal (dated notes + vectors + FTS).

  • Enumeration / 列舉檔案: git ls-files in a git repo (perfect .gitignore respect); a manual walk with built-in ignores otherwise. Binaries, lockfiles, minified, and >512 KB files are skipped.

  • Incremental / 增量: unchanged files skipped by (mtime, size) then content hash; only changed files are re-read and re-embedded.

Requirements / 需求

  • Node ≥ 20 — that's all. Everything else is optional. 只需要 Node ≥ 20,其他都是可選的。

Quick start / 一鍵安裝

One command — no clone, no embedding service, works immediately: 一行指令 —— 不用 clone、不用 embedding 服務,立刻可用:

claude mcp add scratchbook --scope user -- npx -y github:jinyaolin/scratchbook

Out of the box scratchbook runs in lexical-only mode: full-text (BM25) search, exact cross-reference (refs / events), outline, and the journal all work with zero external services. Semantic search switches on automatically once an embedder is reachable (next section). 開箱即是 lexical-only 模式:BM25 全文檢索、精確交叉引用(refs / events)、 outline、日誌全部可用,零外部服務。偵測到 embedding 端點後,語意搜尋自動開啟(見下節)。

Remove with claude mcp remove scratchbook -s user.

Point scratchbook at any Ollama-style embedding endpoint — default is a local Ollama with bge-m3 (1024-dim): 給 scratchbook 一個 Ollama 風格的 embedding 端點即可 —— 預設是本機 Ollama 的 bge-m3(1024 維):

# https://ollama.com
ollama pull bge-m3
# Ollama serves the embedding API at http://localhost:11434/api/embed

The next scratchbook_index detects the embedder and auto-upgrades the project (full re-embed); hybrid semantic+BM25 search takes over from there. Use SCRATCHBOOK_EMBED_URL / _MODEL / _DIM for a remote box or another model. 下一次 scratchbook_index 偵測到端點就會自動升級(全量重嵌入),之後就是語意+BM25 混合搜尋。遠端機器或其他模型用 SCRATCHBOOK_EMBED_URL / _MODEL / _DIM 指定。

Install from a clone / 從 clone 安裝

git clone https://github.com/jinyaolin/scratchbook.git
cd scratchbook
npm install

claude mcp add scratchbook --scope user \
  -- node /absolute/path/to/scratchbook/src/server.mjs

Any MCP client works — the server speaks stdio JSON-RPC. See your client's docs for how to register a local stdio MCP server. 任何 MCP 客戶端都行 —— 伺服器走 stdio JSON-RPC。註冊方式見你客戶端的文件。

Tools / 工具

Tool

Purpose / 用途

scratchbook_index

Index/refresh a codebase (incremental). Run once per project, again after big edits. / 索引/刷新一個 codebase(增量)。

scratchbook_search

Hybrid (semantic + BM25) code search → file:line, symbol, snippet, via. / 混合檢索。

scratchbook_refs

Exact, exhaustive who-uses-X: every definition + reference line of one identifier (case-sensitive). / 精確窮舉某識別字的所有定義與引用行。

scratchbook_events

String event-name cross-reference: event → send / listen sites, one-sided events flagged ⚠. / 字串事件名交叉引用表,單邊事件標 ⚠。

scratchbook_outline

Structural map: each file's imports + top-level symbols with line numbers. / 結構大綱。

scratchbook_journal

Write a dated work-note (decisions, findings, suspected bugs). / 寫工作日記。

scratchbook_recall

Hybrid search over past notes, with note age shown. / 回想筆記(顯示年齡)。

scratchbook_status

Embedding health + indexed projects with counts. / 健康檢查與已索引專案。

scratchbook_forget

Drop a project's code index (journal kept). / 移除某專案的程式碼索引(日記保留)。

scratchbook_gaze

Write to a board and/or launch a flow session over it. / 寫入 board 並/或啟動心流 session。

scratchbook_gaze_read

Read a board (notebook, sessions, artifacts); remember=true persists a synthesis into recall. / 讀 board;remember=true 持久化結論。

Every tool takes an absolute project/path; it defaults to the server's cwd. 每個工具都可傳絕對 project/path,預設為伺服器的 cwd。

gaze-and-think / 凝視與思考

For a problem too tangled to hold in the working session, dump the pieces into a board (a notebook), then launch a flow session — a fresh, isolated claude -p that carries no other context and concentrates only on that board. It reasons about the relationships between the pieces, writes intermediate artifacts under the board's artifacts/, and converges on a synthesis. Runs in the background; poll with scratchbook_gaze_read.

當問題糾結到裝不進當下的 session,把片段丟進一個 board(筆記本),再啟動一個 心流 session —— 一個乾淨隔離、不帶其他上下文、只專注在該 board 的 claude -p。 它思考各片段的關係、把中間產物寫進 board 的 artifacts/、收斂成綜合結論。背景 執行,用 scratchbook_gaze_read 取回。

scratchbook_gaze  board="X" note="a hard piece…"     # accumulate material / 累積素材
scratchbook_gaze  board="X" focus="how do these relate?" project="/abs/repo"
scratchbook_gaze_read board="X"                       # read synthesis + artifacts
scratchbook_gaze_read board="X" remember=true         # persist synthesis → recall

The flow session runs with --permission-mode acceptEdits and read/write/search tools but no shell — it can build checkable artifacts and ground claims in real code, but never runs arbitrary commands. A remembered synthesis is stamped with the commit it was grounded in and its age is shown on recall, because it has no source file to re-derive from and so does not auto-update — treat it as understanding as of that commit, and verify against current code.

心流 session 以 --permission-mode acceptEdits 執行,有讀/寫/搜尋工具但無 shell —— 能產出可檢查的產物、對真實程式碼 grounding,但不執行任意指令。被 remember 的 綜合結論會蓋上「當時所依據的 commit」戳記,recall 時顯示年齡:它沒有源檔可重新推導、 不會自動更新,請當成「截至該 commit 的理解」,並對照現行程式碼驗證。

Requires the claude CLI on PATH for the flow session. 心流 session 需要 PATH 上有 claude CLI。

CLI (manual use / debugging) / 命令列(手動使用 / 除錯)

node src/cli.mjs index  /path/to/your/repo               # index a repo
node src/cli.mjs index  /path/to/your/repo --reindex     # force full re-embed
node src/cli.mjs search "where sessions are cached" --project /path/to/your/repo --full
node src/cli.mjs outline --project /path/to/your/repo --path src/lib
node src/cli.mjs status
node src/cli.mjs note "flagged N+1 in loader" --tags bug,perf --project /path/to/your/repo
node src/cli.mjs recall "what was I doing here" --project /path/to/your/repo
node src/cli.mjs forget --project /path/to/your/repo

Configuration (env) / 設定(環境變數)

Env

Default

Meaning / 意義

SCRATCHBOOK_DB

~/.scratchbook/lancedb

LanceDB directory / LanceDB 目錄

SCRATCHBOOK_EMBED_URL

http://localhost:11434/api/embed

Ollama-style embed endpoint / embed 端點

SCRATCHBOOK_EMBED_MODEL

bge-m3

embedding model / 模型

SCRATCHBOOK_EMBED_DIM

1024

vector dimension (must match model) / 向量維度(須與模型一致)

SCRATCHBOOK_EMBED_BATCH

16

texts per embed request / 每次請求文本數

SCRATCHBOOK_EMBED_CONCURRENCY

4

parallel embed requests / 並行請求數

SCRATCHBOOK_GAZE_DIR

<db-dir>/../gaze

gaze boards directory / gaze board 目錄

SCRATCHBOOK_MAX_FILE_KB

512

skip files larger than this / 略過超過此大小的檔

SCRATCHBOOK_CHUNK_MAX_CHARS

1600

max chunk size / chunk 上限

SCRATCHBOOK_CHUNK_MIN_CHARS

240

min before a soft cut / chunk 下限

SCRATCHBOOK_CHUNK_OVERLAP_LINES

8

overlap when window-splitting / 視窗切分重疊行數

Notes / limits / 注意事項與限制

  • The embedding dimension is baked into the LanceDB schema. Changing to a model of a different dimension means a fresh DB (delete ~/.scratchbook/lancedb). embedding 維度寫死進 LanceDB schema;換到不同維度的模型需重建 DB(刪掉該目錄)。

  • A recalled note / remembered gaze synthesis reflects the code as it was when written and does not auto-update — it's a strong prior, not a substitute for reading current code. 回想到的筆記 / 記憶的 gaze 結論反映寫入當下的程式碼、不會自動更新 —— 是強力 的前導,不是「讀現行程式碼」的替身。

  • Chunking is heuristic (regex anchors), not a full parser — good enough for retrieval and outlines, not a semantic analyser. 切塊是啟發式(regex 錨點),不是完整 parser —— 對檢索/大綱夠用,不是語意分析器。

  • Data under ~/.scratchbook/ is fully rebuildable from source — safe to delete. ~/.scratchbook/ 下的資料完全可從原始碼重建 —— 可安心刪除。

License / 授權

Apache License 2.0 — Copyright 2026 Jinyao Lin.

Install Server
A
license - permissive license
A
quality
B
maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Servers

  • A
    license
    B
    quality
    C
    maintenance
    A local-first MCP server that provides AI agents with safe codebase access through file discovery, hybrid lexical-semantic search, and project introspection. It features durable local memory and semantic indexing while keeping all data and processing entirely on your local machine.
    74
    83
    6
    MIT
  • A
    license
    A
    quality
    A
    maintenance
    Persistent memory MCP server for AI coding agents (Claude Code, Codex, Gemini CLI). Hybrid retrieval (vector + BM25), cross-encoder reranking, knowledge graph, session checkpoint/resume, and multi-scope isolation. Local-first with LanceDB.
    30
    57
    15
    MIT

View all related MCP servers

Related MCP Connectors

  • Persistent memory and cross-session learning for AI coding assistants (hosted remote MCP).

  • Person-owned, portable AI memory as a remote MCP server, readable and writable by any MCP client.

  • StremAI MCP: shared memory for AI coding agents. Connected agents can recall. OAuth + local stdio.

View all MCP Connectors

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/jinyaolin/scratchbook'

If you have feedback or need assistance with the MCP directory API, please join our Discord server