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Melchizedek

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Persistent memory for Claude Code. Automatically indexes every conversation and provides production-grade hybrid search (BM25 + vectors + reranker) via MCP tools. 100% local, zero config, zero API keys, zero invoice.


Why Melchizedek?

Claude Code forgets everything between sessions - and knows nothing about your other projects. Melchizedek fixes both.

It runs silently in the background - indexing your conversations as you work - then gives Claude the ability to search across your entire history, across all projects: past debugging sessions, architectural decisions, error solutions, code patterns.

No cloud. No API keys. No config. Plug and ask.

How it works

~/.claude/projects/**/*.jsonl       (your conversation transcripts - read-only)
        |
        v
  SessionEnd hook                   (auto-triggers after each session)
        |
        v
  +-----------------+
  |  Indexer         |    Parse JSONL -> chunk pairs -> SHA-256 dedup
  |  (better-sqlite3)|    FTS5 tokenize -> vector embed (optional)
  +-----------------+
        |
        v
  ~/.melchizedek/memory.db           (single SQLite file, WAL mode)
        |
        v
  +-----------------+
  |  MCP Server      |    16 search & management tools
  |  (stdio)         |    Hybrid: BM25 + vectors + RRF + reranker
  +-----------------+
        |
        v
  Claude Code                       (searches your history via MCP)

Search pipeline - 4 levels of graceful degradation

Every layer is optional. The plugin works with BM25 alone and gets better as more components are available.

Level Component What it adds Dependency
1 BM25 (FTS5) Keyword search with stemming None (always active)
2 Dual vectors (sqlite-vec) Semantic search - text (MiniLM 384d) + code (Jina 768d) @huggingface/transformers (optional)
3 RRF fusion Merges BM25 + text vectors + code vectors via Reciprocal Rank Fusion Vectors enabled
4 Reranker Cross-encoder re-scoring of top results Transformers.js or node-llama-cpp (optional)

Performance

Measured with npm run bench - 100 sessions, 1 000 chunks, on a single SQLite file.

Metric Result Target
Indexation (100 sessions) ~80 ms < 10 s
BM25 search (mean) ~0.2 ms < 50 ms
DB size (100 sessions) ~1.4 MB < 30 MB
Tokens per search ~125 < 2 000

Quick Start

npm (recommended)

npm install -g melchizedek

Add the MCP server to Claude Code:

claude mcp add --scope user melchizedek -- melchizedek-server

npx (no install)

claude mcp add --scope user melchizedek -- npx melchizedek-server

From source

git clone https://github.com/louis49/melchizedek.git
cd melchizedek && npm install && npm run build
claude --mcp-config .mcp.json

Claude Code plugin marketplace (coming soon)

Plugin review pending. In the meantime, use npm or npx install above.

claude plugin install melchizedek   # not yet available

Setting up hooks (automatic indexing)

The MCP server provides search tools, but hooks trigger automatic indexing. Without hooks, you'd need to manually index sessions.

For marketplace installs, hooks are configured automatically. For npm/npx/source installs, add hooks to ~/.claude/settings.json.

See docs/installation.md for the full JSON configuration, hook reference, and troubleshooting.

After setup, restart Claude Code. Indexing starts automatically.

MCP Tools

Search (start here)

Tool Description
m9k_search Search indexed conversations. Returns compact snippets. Current project boosted. Supports since/until date filters and order (score, date_asc, date_desc).
m9k_context Get a chunk with surrounding context (adjacent chunks in the same session).
m9k_full Retrieve full content of chunks by IDs.

Progressive retrieval pattern - search returns ~50 tokens/result, context ~200-300, full ~500-1000. Start with m9k_search, drill down only when needed. 4x token savings vs loading everything.

Context-aware ranking - results from your current project (×1.5) and current session (×1.2) are automatically promoted. Cross-project results remain visible.

Specialized search

Tool Description
m9k_file_history Find past conversations that touched a specific file.
m9k_errors Find past solutions for an error message.
m9k_similar_work Find past approaches to similar tasks. Prioritizes rich metadata.

Memory management

Tool Description
m9k_save Manually save a memory note for future recall.
m9k_sessions List all indexed sessions, optionally filtered by project.
m9k_info Show memory index info: corpus size, search pipeline, embedding worker, usage metrics.
m9k_config View or update plugin configuration.
m9k_forget Permanently remove a chunk from the index.
m9k_delete_session Delete a session from the index.
m9k_ignore_project Exclude a project from indexing. Future sessions won't be indexed, existing ones optionally purged.
m9k_unignore_project Re-enable indexing for a previously ignored project. Purged data is not restored.
m9k_restart Restart the MCP server to load fresh code after npm run build. Supports force: true for stuck processes.

Usage guide

Tool Description
__USAGE_GUIDE Phantom tool. Its description teaches Claude the retrieval pattern and available tools.

Configuration

Zero config by default. Everything is tunable via m9k_config or environment variables.

Setting Default Env var
Database path ~/.melchizedek/memory.db M9K_DB_PATH
Daemon mode enabled M9K_NO_DAEMON=1 to disable
Log level warn M9K_LOG_LEVEL
Embeddings enabled true M9K_EMBEDDINGS=false to disable
Reranker enabled true M9K_RERANKER=false to disable

See docs/configuration.md for the full settings reference (20+ options, env vars, config file examples).

Enhanced Search

Melchizedek works out of the box with BM25 keyword search. Text embeddings (MiniLM) download automatically on first use for semantic search.

For GPU-accelerated code embeddings (Ollama), cross-encoder reranking (GGUF models), platform-specific setup guides, and the full model reference, see Enhanced Search Setup.

How is this different?

Melchizedek claude-historian-mcp claude-mem episodic-memory mcp-memory-service
GitHub stars npm GitHub stars npm GitHub stars npm GitHub stars GitHub stars PyPI
Philosophy Search engine - indexes everything, you search Search engine - scans JSONL on demand Notebook - AI compresses & saves Search engine Notebook - AI decides what to store
Indexes raw conversations Yes (JSONL transcripts) Yes (direct JSONL read, no persistent index) Compressed summaries Yes (JSONL) No (manual store_memory)
Retroactive on install Yes (backfills all history) Yes (reads existing files) No Yes No (empty at start)
Search BM25 + vectors + RRF + reranker TF-IDF + fuzzy matching FTS5 + ChromaDB Vectors only BM25 + vectors
Progressive retrieval 3 layers (search/context/full) No No No No
100% offline Yes Yes No (needs API for compression) Yes Yes
Single-file storage SQLite None (reads raw JSONL) SQLite + ChromaDB SQLite SQLite-vec
Zero config Yes Yes Yes Yes Yes
MCP tools 16 10 4 2 12
License MIT MIT AGPL-3.0 MIT Apache-2.0
Dual embedding (text + code) Yes (MiniLM + Jina Code) No No No No
Configurable models Yes (Transformers.js or Ollama) No No (Chroma internal) No (hardcoded) Yes (ONNX, Ollama, OpenAI, Cloudflare)
Reranker Cross-encoder (ONNX, GGUF, or HTTP) No No No Quality scorer (not search reranker)
Privacy All local, <private> tag redaction All local Sends data to Anthropic API All local All local
Multi-instance Singleton daemon - N Claude windows share 1 process (Unix socket / Windows named pipe, local fallback) N separate processes Shared HTTP worker (:37777) N separate processes Shared HTTP server

Inspirations

This project stands on the shoulders of others. Key ideas borrowed from:

Project What we took
CASS RRF hybrid fusion, SHA-256 dedup, auto-fuzzy fallback GitHub stars
claude-historian-mcp Specialized MCP tools (file_history, error_solutions) GitHub stars npm
claude-diary PreCompact hook (archive before /compact) GitHub stars

Known issues

  • Session boost inactive - Claude Code currently sends an empty session_id in the SessionStart hook stdin payload, preventing the ×1.2 session boost from working. The ×1.5 project boost is unaffected and provides the primary context-aware ranking. Related upstream issues: #13668 (empty transcript_path), #9188 (stale session_id). Melchizedek's session boost code is tested and ready, and will activate automatically when the upstream fix lands.

Privacy

  • Zero telemetry. No tracking, no analytics, no network calls (except optional lazy model download).
  • Read-only on transcripts. Never writes to ~/.claude/projects/. All data in ~/.melchizedek/.
  • <private> tag support. Content between <private>...</private> is replaced with [REDACTED] before indexing.
  • Local-only. Your conversations never leave your machine.

Requirements

  • Node.js >= 20
  • Claude Code >= 2.0
  • macOS, Linux, or Windows

License

MIT


"Without father, without mother, without genealogy, having neither beginning of days nor end of life."

  • Hebrews 7:3

Built by @louis49

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Persistent memory for Claude Code. Automatically indexes every conversation and provides production-grade hybrid search (BM25 + vectors + reranker) via MCP tools. 100% local, zero config, zero API keys.

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