Mnemonic
БесплатноНе проверенMCP server for on-device hybrid search over markdown knowledge bases, combining BM25, vector embeddings, and LLM reranking with link graph and time decay.
Описание
MCP server for on-device hybrid search over markdown knowledge bases, combining BM25, vector embeddings, and LLM reranking with link graph and time decay.
README
On-device hybrid search for markdown knowledge bases. BM25 + vector + LLM reranking with link graphs, time decay, and HyDE. Designed for pi coding agent.
Quick Start
Global mode (default)
All collections share one index at ~/.cache/mnemonic/index.sqlite. Search everything at once.
npm install -g @naveenadi/mnemonic
mne init
mne collection add ~/notes --name notes
mne index
mne embed
mne query "what was the Q4 planning discussion"
Project-local mode
Use --db for a per-repo index. Keeps project docs separate.
mne --db .mnemonic/index.sqlite init
mne --db .mnemonic/index.sqlite collection add . --name myproject
mne --db .mnemonic/index.sqlite index
mne --db .mnemonic/index.sqlite embed
mne --db .mnemonic/index.sqlite query "deploy steps"
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)
Pi Integration
Three layers plus an interactive setup command, each installable globally (all projects) or per project.
| Layer | What | Global path | Per-project path |
|---|---|---|---|
| Interactive | /mne init walks through setup |
— | — |
| MCP server | Typed tools: query, get, multi_get, status |
~/.pi/agent/mcp.json |
.pi/mcp.json |
| Pi skill | Bash commands via SKILL.md |
~/.pi/agent/skills/mnemonic/ |
.pi/skills/mnemonic/ |
| Pi extension | 4 tools + /mne command via pi.registerTool/Command |
~/.pi/agent/extensions/mnemonic/ |
.pi/extensions/mnemonic/ |
Interactive setup (extension required)
After installing the extension and running /reload, type:
/mne init
This walks through: scope (global vs project) → add directories → index → embed → configure MCP → install skill.
Other commands: /mne add <path>, /mne status, /mne help.
MCP — global
// ~/.pi/agent/mcp.json
{
"mcpServers": {
"mnemonic": {
"command": "mne",
"args": ["mcp"],
"lifecycle": "keep-alive"
}
}
}
MCP — per project
Same config in .pi/mcp.json (project root).
Skill — global
mkdir -p ~/.pi/agent/skills/mnemonic
cp SKILL.md ~/.pi/agent/skills/mnemonic/
Skill — per project
mkdir -p .pi/skills/mnemonic
cp SKILL.md .pi/skills/mnemonic/
Extension — global
mkdir -p ~/.pi/agent/extensions/mnemonic
cp src/pi-extension/index.ts ~/.pi/agent/extensions/mnemonic/
Extension — per project
mkdir -p .pi/extensions/mnemonic
cp src/pi-extension/index.ts .pi/extensions/mnemonic/
Architecture
Core SDK (@naveenadi/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
References
SKILL.md— Pi skill for agentic workflows (dig loop, cross-reference, setup)references/setup.md— Detailed CLI setup and diagnosticsreferences/pi-integration.md— Pi integration: MCP, skill, extension (both modes)references/link-graph.md— Cross-reference commands and usagesrc/pi-extension/— Pi extension source + standalone package.json
License
MIT
Установка Mnemonic
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/naveenadi/mnemonicFAQ
Mnemonic MCP бесплатный?
Да, Mnemonic MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Mnemonic?
Нет, Mnemonic работает без API-ключей и переменных окружения.
Mnemonic — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Mnemonic в Claude Desktop, Claude Code или Cursor?
Открой Mnemonic на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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