mahabdalla QMD - Quick Markdown Search
Local search engine for markdown content.
Status
!qmd status 2>/dev/null || echo "Not installed: npm install -g @tobilu/qmd"
MCP: query
{
"searches": [
{ "type": "lex", "query": "CAP theorem consistency" },
{ "type": "vec", "query": "tradeoff between consistency and availability" }
],
"collections": ["docs"],
"limit": 10
}
Query Types
| Type | Method | Input |
|---|---|---|
lex |
BM25 | Keywords — exact terms, names, code |
vec |
Vector | Question — natural language |
hyde |
Vector | Answer — hypothetical result (50-100 words) |
Writing Good Queries
lex (keyword)
- 2-5 terms, no filler words
- Exact phrase:
"connection pool"(quoted) - Exclude terms:
performance -sports(minus prefix) - Code identifiers work:
handleError async
vec (semantic)
- Full natural language question
- Be specific:
"how does the rate limiter handle burst traffic" - Include context:
"in the payment service, how are refunds processed"
hyde (hypothetical document)
- Write 50-100 words of what the answer looks like
- Use the vocabulary you expect in the result
expand (auto-expand)
- Use a single-line query (implicit) or
expand: questionon its own line - Lets the local LLM generate lex/vec/hyde variations
- Do not mix
expand:with other typed lines — it's either a standalone expand query or a full query document
Intent (Disambiguation)
When a query term is ambiguous, add intent to steer results:
{
"searches": [
{ "type": "lex", "query": "performance" }
],
"intent": "web page load times and Core Web Vitals"
}
Intent affects expansion, reranking, chunk selection, and snippet extraction. It does not search on its own — it's a steering signal that disambiguates queries like "performance" (web-perf vs team health vs fitness).
Combining Types
| Goal | Approach |
|---|---|
| Know exact terms | lex only |
| Don't know vocabulary | Use a single-line query (implicit expand:) or vec |
| Best recall | lex + vec |
| Complex topic | lex + vec + hyde |
| Ambiguous query | Add intent to any combination above |
First query gets 2x weight in fusion — put your best guess first.
Lex Query Syntax
| Syntax | Meaning | Example |
|---|---|---|
term |
Prefix match | perf matches "performance" |
"phrase" |
Exact phrase | "rate limiter" |
-term |
Exclude | performance -sports |
Note: -term only works in lex queries, not vec/hyde.
Collection Filtering
{ "collections": ["docs"] } // Single
{ "collections": ["docs", "notes"] } // Multiple (OR)
Omit to search all collections.
Other MCP Tools
| Tool | Use |
|---|---|
get |
Retrieve doc by path or #docid |
multi_get |
Retrieve multiple by glob/list |
status |
Collections and health |
CLI
qmd query "question" # Auto-expand + rerank
qmd query $'lex: X\nvec: Y' # Structured
qmd query $'expand: question' # Explicit expand
qmd query --json --explain "q" # Show score traces (RRF + rerank blend)
qmd search "keywords" # BM25 only (no LLM)
qmd get "#abc123" # By docid
qmd multi-get "journals/2026-*.md" -l 40 # Batch pull snippets by glob
qmd multi-get notes/foo.md,notes/bar.md # Comma-separated list, preserves order
HTTP API
curl -X POST http://localhost:8181/query \
-H "Content-Type: application/json" \
-d '{"searches": [{"type": "lex", "query": "test"}]}'
Setup
npm install -g @tobilu/qmd
qmd collection add ~/notes --name notes
qmd embed
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