ccRecall

中文版

A local memory service for Claude Code — indexes your conversation history, recalls relevant context on demand, and injects it into future sessions. Zero API cost.

📐 v0.3.0 — Trust split (breaking change for harvest write path)

The SessionEnd hook now writes to a low-trust session_journal table instead of memories. Journal entries are scored, surfaced via /health (journalPendingCount), and do not appear in recall_query / recall_context results until you run ccmem promote <id>. Manual recall_save is unchanged — it still writes directly to high-trust memories.

The rule scorer is no longer on the persistence gate; it informs trust grade and promotion priority instead. Background reasoning at issue #21.

Pre-0.3.0 memories stay queryable as-is. The v22 schema migration runs automatically on first daemon startup; existing rows are not touched. New harvest goes to journal from now on.

Core Concept

Every time you start a new Claude Code session, the AI forgets everything. The architecture you spent 20 minutes explaining, the bug you debugged together, the decisions you made — all gone. You start over.

CLAUDE.md and RESUME.md help, but they're static files you maintain by hand. ccRecall automates this: it reads your JSONL conversation logs, builds a searchable index, and serves relevant memories back to Claude Code through hooks and MCP tools. The AI remembers what it learned — you don't have to remind it.

ccRecall is the "memory" counterpart to ccRewind (a conversation replay GUI). ccRewind lets humans look back at what happened; ccRecall lets the AI remember what happened.

Note: This project is unrelated to spences10/ccrecall, an analytics-focused tool that happens to share the name. Because the npm package ccrecall is already taken, we publish as @tznthou/ccrecall and the CLI binary is named ccmem.

Features

Architecture

flowchart TB
    subgraph Input["Data Source (read-only)"]
        JSONL["~/.claude/projects/*/*.jsonl"]
    end

    subgraph Core["ccRecall Service (port 7749)"]
        Scanner["Scanner<br/>find JSONL files"]
        Parser["Parser<br/>parse conversations"]
        Summarizer["Summarizer<br/>rule-based extraction"]
        DB["SQLite + FTS5<br/>index & search"]
        API["HTTP API<br/>8 endpoints"]
    end

    subgraph Consumers["Context Injection"]
        Hook["Claude Code Hooks<br/>SessionStart / SessionEnd"]
        MCP["MCP Server<br/>recall_query / recall_save"]
    end

    JSONL --> Scanner --> Parser --> Summarizer --> DB
    DB --> API
    API --> Hook
    API --> MCP

Tech Stack

Quick Start

First time here? The full walkthrough (install via npm → MCP setup → everyday usage) lives in docs/tutorial.md. The section below is the contributor / dev-mode path.

Prerequisites

• Node.js >=20.0.0,<23.0.0

• pnpm

Installation

git clone https://github.com/tznthou/ccRecall.git
cd ccRecall

pnpm install

# Start development server (auto-indexes on startup, watches ~/.claude/projects)
pnpm dev

The service starts at http://127.0.0.1:7749 and indexes all JSONL files in ~/.claude/projects/.

Verify

# Health check — should show sessionCount > 0
curl http://127.0.0.1:7749/health

# Search your conversation history
curl "http://127.0.0.1:7749/memory/query?q=authentication&limit=5"

API Endpoints

MCP Tools

Memory types (for recall_save):

• decision — explicit choice with rationale

• discovery — non-obvious finding

• preference — user style or convention

• pattern — recurring workflow or code template

• feedback — user correction on past work

Expose them to Claude Code. After pnpm build, the ccmem-mcp bin is on the repo's node_modules/.bin path — point claude mcp add at it or at a global install:

# Using the built bin (after pnpm build)
claude mcp add ccrecall --scope user -- /absolute/path/to/ccRecall/dist/mcp/server.js

# Or using tsx for development (no build step)
claude mcp add ccrecall --scope user -- /absolute/path/to/ccRecall/node_modules/.bin/tsx /absolute/path/to/ccRecall/src/mcp/server.ts

A ready-to-copy example lives at .mcp.json.example.

See hooks/README.md for SessionStart / SessionEnd hook installation.

CLI Commands

@tznthou/ccrecall ships two binaries:

• ccmem — daemon launcher + admin commands

• ccmem-mcp — MCP server (registered with Claude Code via claude mcp add)

Daemon and hook lifecycle (macOS):

Journal review (since v0.3.0):

Surface pending candidates:

curl http://127.0.0.1:7749/journal/pending
# or just check the count
curl http://127.0.0.1:7749/health | jq .journalPendingCount

ccRecall vs auto memory

ccRecall lives alongside Claude Code's built-in auto memory (~/.claude/projects/*/memory/). They're complementary — use them for different things.

Default for saving: write to auto memory, let the hook harvest ccRecall independently. Don't call recall_save to mirror a fact you already curated — duplicate writes just create noise.

Default for querying: MEMORY.md is already in context — check the index first. Fall back to recall_query / recall_context only when the user references past work and auto memory has no matching entry.

ccRecall's value is the long tail that auto memory can't cover (nobody hand-curates 500 sessions of notes). If Claude defaults to both, auto memory wins because it's already loaded and curated. ccRecall earns its keep when the curated index misses.

Within ccRecall there's now a second trust split (since v0.3.0). The SessionEnd hook writes to a low-trust session_journal table that recall_query does not read. Promote a candidate to high-trust memories with ccmem promote <id> to make it queryable. Manual recall_save skips the journal entirely — it writes straight to memories. The point is to let the harvester record broadly while keeping recall results clean.

Running as a service (macOS)

ccRecall runs as a local HTTP daemon. To keep it up across reboots, register a per-user LaunchAgent:

pnpm build
node dist/index.js install-daemon        # or `ccmem install-daemon` if globally linked
node dist/index.js install-daemon --dry-run   # preview plist without writing

# verify
launchctl list | grep ccrecall
curl http://127.0.0.1:7749/health

# remove
node dist/index.js uninstall-daemon

The installer:

• writes ~/Library/LaunchAgents/com.tznthou.ccrecall.plist

• routes logs to ~/Library/Logs/ccrecall/ccrecall.{out,err}.log

• propagates CCRECALL_PORT / CCRECALL_DB_PATH from the current shell into the plist, so the LaunchAgent uses the same settings as your interactive run

• refuses to touch a plist whose Label isn't ccRecall's (safety check)

Full manual-install, troubleshooting, and uninstall docs: docs/launchd.md.

Linux/Windows equivalents (systemd unit, Windows service) are planned for Phase 5. For now, run under nohup or your process manager of choice.

Monitoring

The daemon runs PRAGMA integrity_check on startup and every 6 hours. The result (timestamp + boolean) is cached and surfaced on /health as lastIntegrityCheckAt / lastIntegrityCheckOk. When drift is detected, the full integrity_check output is written to a timestamped file under ~/.ccrecall/integrity-alerts/.

If you see a drift alert, snapshot the DB before running REINDEX. REINDEX fixes the symptom but destroys the forensic state:

cp ~/.ccrecall/ccrecall.db ~/ccrecall-drift-snapshot.db
sqlite3 ~/.ccrecall/ccrecall.db 'REINDEX;'

WAL maintenance

Each indexer batch ends with PRAGMA wal_checkpoint(TRUNCATE) so the ccrecall.db-wal sidecar is reset to 0 bytes after every reindex. On a long-running daemon you should see WAL hovering near 0 most of the time, spiking briefly while a batch runs.

If you ever see WAL growing unboundedly (close to the size of the main DB), check stderr for [indexer] WAL checkpoint busy warnings — that means a reader has been holding a snapshot past busy_timeout across several consecutive batches and the truncate keeps deferring. Identify the offending client and the next clean batch will reclaim the space.

Project Structure

ccRecall/
├── src/
│   ├── core/
│   │   ├── types.ts              # All type definitions
│   │   ├── parser.ts             # JSONL conversation parser
│   │   ├── scanner.ts            # File system scanner
│   │   ├── summarizer.ts         # Rule-based session summarizer
│   │   ├── topic-extractor.ts    # Rule-based topic extraction
│   │   ├── database.ts           # SQLite + FTS5 (trimmed from ccRewind)
│   │   ├── indexer.ts            # Indexing pipeline orchestrator
│   │   ├── memory-service.ts     # Memory lifecycle (touch / delete / update)
│   │   ├── compression.ts        # L0→L1→L2→delete state machine
│   │   ├── lint.ts               # Orphan / stale memory detection
│   │   ├── maintenance-coordinator.ts  # Background compression tick + journal decay sweep
│   │   ├── watcher.ts            # chokidar JSONL watcher (Phase 4e)
│   │   └── log-safe.ts           # scrubErrorMessage — log-injection defence
│   ├── api/
│   │   ├── server.ts             # HTTP server
│   │   └── routes.ts             # Request routing + rescue reindex
│   ├── mcp/
│   │   ├── server.ts             # MCP stdio server entry (shebang bin)
│   │   └── tools.ts              # recall_query + recall_context + recall_save
│   ├── cli/
│   │   ├── daemon.ts             # install-daemon / uninstall-daemon (macOS)
│   │   └── journal.ts            # ccmem promote / reject (since v0.3.0)
│   └── index.ts                  # HTTP entry point + subcommand dispatch
├── hooks/
│   ├── session-start.mjs         # Inject memories on SessionStart (stdout)
│   ├── session-end.mjs           # POST /session/end on SessionEnd
│   └── README.md                 # Hook installation guide
├── docs/
│   ├── tutorial.md               # End-user walkthrough (install → MCP → usage)
│   ├── architecture.md           # Daemon design rationale (contributor-oriented)
│   └── launchd.md                # macOS LaunchAgent install/troubleshoot
├── tests/                        # 562 tests across 37 files (parser, scanner,
│   │                             # summarizer, database, indexer, e2e, MCP,
│   │                             # memories, hooks, watcher, CLI, migrations,
│   │                             # FTS5 CJK edge cases, integrity monitor,
│   │                             # session_journal DAO, promote+reject, sweep, ...)
│   └── fixtures/                 # Sample JSONL + shared test helpers
├── .mcp.json.example             # MCP client config template
└── NOTICE / SECURITY.md / CONTRIBUTING.md / CODE_OF_CONDUCT.md

Related Projects

• ccRewind — Session replay GUI for Claude Code. ccRecall's core modules (parser, scanner, summarizer, database, indexer) were extracted from ccRewind.

Reflections

Why This Exists

Thariq from Anthropic's Claude Code team wrote about context management in April 2026 — 11,908 bookmarks, because everyone saved it to re-read but nobody had the tools to actually do it. He described the problem perfectly: context rot degrades model performance in long sessions, and autocompact fires at the worst possible moment.

But he gave methodology, not tools. ccRecall is the tool.

The real trigger was simpler: I kept re-explaining the same architecture to Claude Code across sessions. Not because the AI is bad at remembering — it literally can't. Every session starts from zero. CLAUDE.md helps, but it's a static file I maintain by hand. The maintenance cost grows faster than the value. Sound familiar? That's exactly why humans abandon wikis too (Karpathy's LLM Wiki insight).

Design Decisions

Rule-based summarizer instead of LLM calls. claude-mem uses the Claude API for summarization — you're paying AI money to help AI remember. ccRecall uses heuristic extraction (regex patterns, tool usage analysis, outcome inference). It's less sophisticated but costs exactly zero. For session summaries, "Edit x8, 5 files, committed" is more useful than a paragraph of prose anyway.

FTS5 instead of vector database. Semantic search sounds better on paper, but for conversation logs — where you're searching for specific tools, file paths, error messages — keyword matching wins. FTS5 queries run in <10ms locally. No embedding model, no Chroma, no Docker container. At the scale we're operating (hundreds of sessions, not millions of documents), Karpathy's own analysis confirms: "plain index + keyword search is already sufficient under 500 sources."

HTTP + MCP dual interface. Research showed that MCP server tools are the most stable way to inject context into Claude (pull-based, Claude decides when to fetch). But SessionStart hooks (push-based, automatic) are also stable. So ccRecall runs both: HTTP for hooks, MCP for on-demand queries. Same SQLite backend, two access patterns.

Read-only constraint. ccRecall never modifies ~/.claude/. This isn't just politeness — it's a trust boundary. If a background service can write to your Claude Code config, one bug could corrupt your sessions. Read-only means the worst case is "ccRecall gives bad search results," not "ccRecall broke my setup."

Non-goals

No Docker, no Electron, no vector database. These are deliberate exclusions, not missing features. Docker adds deployment friction for what should be a pnpm dev experience. Electron is for GUIs — ccRecall has no UI (that's ccRewind's job). Vector databases solve a problem we don't have at this scale.

No LLM dependency for any operation. If ccRecall needs an API key to function, it has failed. The whole point is zero-cost memory that runs locally. Summarization is rule-based. Search is FTS5. The day we need LLM calls is the day we've overscoped.

No "smart" memory injection. ccRecall doesn't decide what Claude should remember. It provides a search API — the injection layer (hooks, MCP) presents results, and Claude integrates them. Opinionated memory selection is a premature optimization that would be wrong in ways we can't predict.

No modification of user data. ccRecall reads ~/.claude/projects/ JSONL files. It never writes to that directory, never modifies session files, never injects itself into Claude Code's config automatically. The user explicitly configures hooks and MCP — ccRecall doesn't install itself.

Changelog

Release notes and version history live in CHANGELOG.md. Every tagged version has a matching entry; the Unreleased section tracks what's landed on main but not yet published to npm.

License

Licensed under the Apache License, Version 2.0 — see LICENSE.

Copyright 2026 tznthou

Author

tznthou — tznthou.com · tznthou@gmail.com