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Melchizedek MCP server

by louis49·io.github.louis49/melchizedek·v1.0.2·7 stars
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Persistent memory for Claude Code — offline, single-file, hybrid search.

B74/100grade B
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Safety scan
B74/100

full report

Adoption
Growing

7 stars52 downloads/wk

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If you have run it, two minutes of your experience saves the next person an afternoon.

Melchizedek tools (15, 2 write)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

  • m9k_config

    View or update plugin configuration. Changes are saved to ~/.melchizedek/config.json and take effect on next server restart. Without arguments, returns current config.

  • m9k_context

    Get a chunk with surrounding context (adjacent chunks in the same session). Use after m9k_search to understand the conversation flow.

  • m9k_delete_sessionwrite action

    Delete a session from the index. Removes all chunks and search data. Does NOT delete the source JSONL file.

  • m9k_errors

    Find past solutions for an error message. Returns error context + how it was resolved.

  • m9k_file_history

    Find past conversations that touched a specific file. Searches metadata (tool_use file_path) and text content.

  • m9k_forget

    Permanently remove a specific chunk from the memory index. Does NOT delete the source JSONL. Use m9k_search() first to find the chunk ID to forget.

  • m9k_full

    Retrieve full content of chunks by IDs. Use after m9k_search to get complete context.

  • m9k_ignore_project

    Exclude a project from indexing. Future sessions won't be indexed. Optionally purge existing indexed sessions for this project.

  • m9k_info

    Show memory index information: corpus size, search pipeline status, usage metrics, embedding worker state.

  • m9k_restart

    Restart the MCP server. Use after npm run build to load fresh code. The server disconnects; next MCP call auto-reconnects with the new build.

  • m9k_save

    Manually save a memory note for future recall. Use for important decisions, patterns, or context.

  • m9k_search

    Search indexed past conversations. Returns compact results with snippets. Results from the current project and session are boosted by default. Use m9k_context or m9k_full to drill down.

  • m9k_sessions

    List all indexed sessions, optionally filtered by project.

  • m9k_similar_work

    Find past work similar to what you're about to do. Use at the start of a complex task to see previous approaches. Unlike m9k_search, this prioritizes chunks with rich metadata (multiple tools used, multiple files touched).

  • m9k_unignore_projectwrite action

    Remove a project from the ignore list. Future sessions will be indexed again. Previously purged sessions are NOT restored (requires backfill re-indexation).

Public scan report

scanner v0.1.10 · 2026-09-28 · same rubric, same numbers if you re-run it

1 medium
  • Code scan8 source files scanned20/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitylocal package, no credentials required12/15
  • Maintenancelast push 99 days ago8/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10

Findings (1)

  • mediumeval / new Function usedexec.eval
    dist/daemon.js: …ode, sch); const makeValidate = new Function(`${names_1.default.self}`, `${names_1.de…
Overall 74/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How Melchizedek compares

Against every graded Web search MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
74/100
higher than 43% of 3,470 Web search servers
Tools
15
the typical Web search server has 5
Tools that change things
13%
typical: 0%. Fewer write tools means less an agent can break
GitHub stars
7
more than 83% of 1,786 Web search servers
Downloads a week
52
more than 36% of 827 Web search servers with a package

What its tools let an agent do: 13 read · 2 change

Install Melchizedek in Claude Code, Cursor or VS Code

Runs npx -y melchizedek on your machine. Read the scan report first; the gateway never runs local packages.

claude mcp add melchizedek -- npx -y melchizedek
Add to Cursor

What the publisher says

From the Melchizedek repository's README, as published. We do not edit it. Read it on GitHub

Melchizedek

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.

Performance

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

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)

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

Melchizedek: common questions

Is Melchizedek MCP server safe?
Mostly: it is graded B (74/100). Read the Melchizedek safety report
How do I install Melchizedek?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does Melchizedek need an API key?
Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is Melchizedek maintained?
The last commit was 136 days ago (2026-06-21). The latest release is v1.0.2.
What can I use instead of Melchizedek?
Servers from other publishers that do the same job: M3 Memory MCP server, Reverie MCP server and Octobrain MCP server.
How does Melchizedek compare with other Web search MCP servers?
safety score 74/100 (higher than 43% of 3,470 Web search servers); tools 15 (the typical Web search server has 5); tools that change things 13% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.

Alternatives to Melchizedek

Same job from other publishers: the closest match first, then the best rated.

  • M3 Memory
    Local-first, cloud-friendly memory — 100+ tools, 99.2% LongMemEval-S retrieval@8, hybrid search.
    A
  • Reverie
    Graph memory that dreams: Neo4j knowledge-graph memory for AI agents with hybrid search
    B
  • Octobrain
    Persistent memory for AI assistants with semantic search and knowledge graph relationships.
    A
  • Repomix
    Pack local or remote codebases into AI-friendly files that LLMs and coding agents can read or search
    A
  • DocsMint
    Cloud or self-hosted knowledge for AI agents: hybrid search, reranking, GraphRAG, scoped MCP tools.
    A