qmd - Quick Markdown Search

Local search engine for Markdown notes, docs, and knowledge bases. Index once, search fast.

When to use (trigger phrases)

"search my notes / docs / knowledge base"
"find related notes"
"retrieve a markdown document from my collection"
"search local markdown files"

Default behavior (important)

Prefer
```
qmd search
```
(BM25). It's typically instant and should be the default.
Use
```
qmd vsearch
```
only when keyword search fails and you need semantic similarity (can be very slow on a cold start).
Avoid
```
qmd query
```
unless the user explicitly wants the highest quality hybrid results and can tolerate long runtimes/timeouts.

Prerequisites

Bun >= 1.0.0
macOS:
```
brew install sqlite
```
(SQLite extensions)
Ensure PATH includes:
```
$HOME/.bun/bin
```

Install Bun (macOS):

brew install oven-sh/bun/bun

Install

bun install -g https://github.com/tobi/qmd

Setup

qmd collection add /path/to/notes --name notes --mask "**/*.md"
qmd context add qmd://notes "Description of this collection"  # optional
qmd embed  # one-time to enable vector + hybrid search

What it indexes

Intended for Markdown collections (commonly
```
**/*.md
```
).
In our testing, "messy" Markdown is fine: chunking is content-based (roughly a few hundred tokens per chunk), not strict heading/structure based.
Not a replacement for code search; use code search tools for repositories/source trees.

Search modes

```
qmd search
```
(default): fast keyword match (BM25)
```
qmd vsearch
```
(last resort): semantic similarity (vector). Often slow due to local LLM work before the vector lookup.
```
qmd query
```
(generally skip): hybrid search + LLM reranking. Often slower than
```
vsearch
```
and may timeout.

Performance notes

```
qmd search
```
is typically instant.
```
qmd vsearch
```
can be ~1 minute on some machines because query expansion may load a local model (e.g., Qwen3-1.7B) into memory per run; the vector lookup itself is usually fast.
```
qmd query
```
adds LLM reranking on top of
```
vsearch
```
, so it can be even slower and less reliable for interactive use.
If you need repeated semantic searches, consider keeping the process/model warm (e.g., a long-lived qmd/MCP server mode if available in your setup) rather than invoking a cold-start LLM each time.

Common commands

qmd search "query"             # default
qmd vsearch "query"
qmd query "query"
qmd search "query" -c notes     # Search specific collection
qmd search "query" -n 10        # More results
qmd search "query" --json       # JSON output
qmd search "query" --all --files --min-score 0.3

Useful options

```
-n <num>
```
: number of results
```
-c, --collection <name>
```
: restrict to a collection
```
--all --min-score <num>
```
: return all matches above a threshold
```
--json
```
/
```
--files
```
: agent-friendly output formats
```
--full
```
: return full document content

Retrieve

qmd get "path/to/file.md"       # Full document
qmd get "#docid"                # By ID from search results
qmd multi-get "journals/2025-05*.md"
qmd multi-get "doc1.md, doc2.md, #abc123" --json

Maintenance

qmd status                      # Index health
qmd update                      # Re-index changed files
qmd embed                       # Update embeddings

Keeping the index fresh

Automate indexing so results stay current as you add/edit notes.

For keyword search (
```
qmd search
```
),
```
qmd update
```
is usually enough (fast).
If you rely on semantic/hybrid search (
```
vsearch
```
/
```
query
```
), you may also want
```
qmd embed
```
, but it can be slow.

Example schedules (cron):

# Hourly incremental updates (keeps BM25 fresh):
0 * * * * export PATH="$HOME/.bun/bin:$PATH" && qmd update
Optional: nightly embedding refresh (can be slow):
0 5 * * * export PATH="$HOME/.bun/bin:$PATH" && qmd embed

If your Clawdbot/agent environment supports a built-in scheduler, you can run the same commands there instead of system cron.

Models and cache

Uses local GGUF models; first run auto-downloads them.
Default cache:
```
~/.cache/qmd/models/
```
(override with
```
XDG_CACHE_HOME
```
).

Relationship to Clawdbot memory search

```
qmd
```
searches your local files (notes/docs) that you explicitly index into collections.
Clawdbot's
```
memory_search
```
searches agent memory (saved facts/context from prior interactions).
Use both:
```
memory_search
```
for "what did we decide/learn before?",
```
qmd
```
for "what's in my notes/docs on disk?".

QMD - Quick Markdown Search

AI Skill Market Insights

Be Part of the 2,506+ Developer Community

qmd - Quick Markdown Search

When to use (trigger phrases)

Default behavior (important)

Prerequisites

Install

Setup

What it indexes

Search modes

Performance notes

Common commands

Useful options

Retrieve

Maintenance

Keeping the index fresh

Optional: nightly embedding refresh (can be slow):

Models and cache

Relationship to Clawdbot memory search

Quick Start

Manual Installation

TEAR & SHARE

Tags

using-git-worktrees

finishing-a-development-branch

test-driven-development

requesting-code-review

receiving-code-review

Channels

Learn

Compare

Company