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mnemonic

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mnemonic

On-device hybrid search for markdown knowledge bases. BM25 + vector + LLM reranking with link graphs, time decay, and HyDE. Designed for pi coding agent.

npm install -g @pi/mnemonic
mne init
mne collection add ~/notes --name notes
mne index
mne embed
mne query "what was the Q4 planning discussion"

Features

  • Hybrid search — BM25 (FTS5) + Vector embeddings + RRF fusion

  • Structured queries — intent:, lex:, vec:, hyde: fields for deliberate retrieval

  • Query expansion — LLM generates alternative phrasings for better recall

  • HyDE — Hypothetical Document Embeddings

  • LLM reranking — Cross-encoder re-ranks top candidates with position-aware blending

  • Link graph — Wikilinks, backlinks, orphan detection, link boosting

  • Time decay — Exponential recency weighting (favor recent notes)

  • Tagging — Manual + frontmatter auto-parse

  • Context tree — Hierarchical metadata (mne:// virtual paths)

  • Smart chunking — Markdown heading-aware boundaries

  • Dual LLM backend — Ollama (default) or node-llama-cpp (self-contained GGUF models)

Related MCP server: Hoard

Pi Integration

Three layers:

Layer

What

How

Pi Skill

SKILL.md

Bash commands via mne search, mne query, mne get

MCP Server

mne mcp

Stdio + HTTP, typed tools: query, get, multi_get, status

Pi Extension

src/pi-extension/index.ts

4 custom tools registered with pi.registerTool()

Configure MCP in ~/.pi/agent/mcp.json:

{
  "mcpServers": {
    "mnemonic": {
      "command": "mne",
      "args": ["mcp"],
      "lifecycle": "keep-alive"
    }
  }
}

Architecture

                    Core SDK (@pi/mnemonic)
    Store (SQLite FTS5 + vec)  |  Search Pipeline  |  Chunker
                    LLM Backend (Ollama <-> node-llama-cpp)
                    Link Graph  |  Time Decay  |  HyDE
Query ──► HyDE ──► Query Expansion ──► BM25 + Vector (per variant)
                   │
                   └──► RRF Fusion ──► Reranking ──► Time Decay ──► Link Boost ──► Results

CLI Commands

mne init                     Initialize index
mne collection add <dir>     Add a collection
mne collection list          List collections
mne index                    Index all collections
mne embed                    Generate vector embeddings
mne search <query>           BM25 full-text search
mne vsearch <query>          Vector semantic search
mne query <query>            Hybrid search (BM25 + vector + reranking)
mne get <#docid|path>        Retrieve a document
mne multi-get <pattern>      Batch retrieve
mne ls [collection]          List files
mne status                   Show index status
mne doctor                   Diagnostic checks
mne context add <path> <txt> Add context metadata
mne tag <#docid> <tag>       Add a tag
mne links <#docid>           Show outgoing links
mne backlinks <#docid>       Show incoming links
mne orphans                  Find orphan documents
mne mcp                      Start MCP server

License

MIT

This server cannot be installed

F
license - not found
-
quality - not tested
C
maintenance

How are these scores calculated?

Maintenance

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

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