MCPInstall

memory-metadata-search

Structured metadata search for Basic Memory: query notes by custom frontmatter fields using equality, range, array, and nested filters. Use when finding notes by status, priority, confidence, or any custom YAML field rather than free-text content.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/basicmachines-co/basic-memory-skills --skill memory-metadata-search
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads memory-metadata-search automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Memory Metadata Search

Find notes by their structured frontmatter fields instead of (or in addition to) free-text content. Any custom YAML key in a note's frontmatter beyond the standard set (title, type, tags, permalink, schema) is automatically indexed as entity_metadata and becomes queryable.

When to Use

  • Filtering by status or priority — find all notes with status: draft or priority: high
  • Querying custom fields — any frontmatter key you invent is searchable
  • Range queries — find notes with confidence > 0.7 or score between 0.3 and 0.8
  • Combining text + metadata — narrow a text search with structured constraints
  • Tag-based filtering — find notes tagged with specific frontmatter tags
  • Schema-aware queries — filter by nested schema fields using dot notation

The Tool

All metadata searching uses search_notes. Pass filters via metadata_filters, or use the tags and status convenience shortcuts. Omit query (or pass None) for filter-only searches.

Filter Syntax

Filters are a JSON dictionary. Each key targets a frontmatter field; the value specifies the match condition. Multiple keys combine with AND logic.

Equality

{"status": "active"}

Array Contains (all listed values must be present)

{"tags": ["security", "oauth"]}

$in (match any value in list)

{"priority": {"$in": ["high", "critical"]}}

Comparisons ($gt, $gte, $lt, $lte)

{"confidence": {"$gt": 0.7}}

Numeric values use numeric comparison; strings use lexicographic comparison.

$between (inclusive range)

{"score": {"$between": [0.3, 0.8]}}

Nested Access (dot notation)

{"schema.version": "2"}

Quick Reference

OperatorSyntaxExample
Equality{"field": "value"}{"status": "active"}
Array contains{"field": ["a", "b"]}{"tags": ["security", "oauth"]}
$in{"field": {"$in": [...]}}{"priority": {"$in": ["high", "critical"]}}
$gt / $gte{"field": {"$gt": N}}{"confidence": {"$gt": 0.7}}
$lt / $lte{"field": {"$lt": N}}{"score": {"$lt": 0.5}}
$between{"field": {"$between": [lo, hi]}}{"score": {"$between": [0.3, 0.8]}}
Nested{"a.b": "value"}{"schema.version": "2"}

Rules:

  • Keys must match [A-Za-z0-9_-]+ (dots separate nesting levels)
  • Operator dicts must contain exactly one operator
  • $in and array-contains require non-empty lists
  • $between requires exactly [min, max]

Warning: Operators MUST include the $ prefix — write $gte, not gte. Without the prefix the filter is treated as an exact-match key and will silently return no results. Correct: {"confidence": {"$gte": 0.7}}. Wrong: {"confidence": {"gte": 0.7}}.

Using search_notes with Metadata

Pass metadata_filters, tags, or status to search_notes. Omit query for filter-only searches, or combine text and filters together.

# Filter-only — find all notes with a given status
search_notes(metadata_filters={"status": "in-progress"})

# Filter-only — high-priority specs in a specific project
search_notes(
    metadata_filters={"type": "spec", "priority": {"$in": ["high", "critical"]}},
    project="research",
    page_size=10,
)

# Filter-only — notes with confidence above a threshold
search_notes(metadata_filters={"confidence": {"$gt": 0.7}})

# Convenience shortcuts for tags and status
search_notes(status="active")
search_notes(tags=["security", "oauth"])

# Text search narrowed by metadata
search_notes("authentication", metadata_filters={"status": "draft"})

# Mix text, tag shortcut, and advanced filter
search_notes(
    "oauth flow",
    tags=["security"],
    metadata_filters={"confidence": {"$gt": 0.7}},
)

Merging rules: tags and status are convenience shortcuts merged into metadata_filters via setdefault. If the same key exists in metadata_filters, the explicit filter wins.

Tag Search Shorthand

The tag: prefix in a query converts to a tag filter automatically:

# These are equivalent:
search_notes("tag:tier1")
search_notes("", tags=["tier1"])

# Multiple tags (comma or space separated) — all must match:
search_notes("tag:tier1,alpha")

Example: Custom Frontmatter in Practice

A note with custom fields:

---
title: Auth Design
type: spec
tags: [security, oauth]
status: in-progress
priority: high
confidence: 0.85
---

# Auth Design

## Observations
- [decision] Use OAuth 2.1 with PKCE for all client types #security
- [requirement] Token refresh must be transparent to the user

## Relations
- implements [[Security Requirements]]

Queries that find it:

# By status and type
search_notes(metadata_filters={"status": "in-progress", "type": "spec"})

# By numeric threshold
search_notes(metadata_filters={"confidence": {"$gt": 0.7}})

# By priority set
search_notes(metadata_filters={"priority": {"$in": ["high", "critical"]}})

# By tag shorthand
search_notes("tag:security")

# Combined text + metadata
search_notes("OAuth", metadata_filters={"status": "in-progress"})

Guidelines

  • Use metadata search for structured queries. If you're looking for notes by a known field value (status, priority, type), metadata filters are more precise than text search.
  • Use text search for content queries. If you're looking for notes about something, text search is better. Combine both when you need precision.
  • Custom fields are free. Any YAML key you put in frontmatter becomes queryable — no schema or configuration required.
  • Multiple filters are AND. {"status": "active", "priority": "high"} requires both conditions.
  • Omit query for filter-only searches. search_notes(metadata_filters={"status": "active"}) works without a text query.
  • Dot notation for nesting. Access nested YAML structures with dots: {"schema.version": "2"} queries the version key inside a schema object.
  • Tags shortcut is convenient but limited. tags and status are sugar for common fields. For anything else, use metadata_filters directly.

FAQ

What does the memory-metadata-search skill do?

Structured metadata search for Basic Memory: query notes by custom frontmatter fields using equality, range, array, and nested filters. Use when finding notes by status, priority, confidence, or any custom YAML field rather than free-text content.

How do I install memory-metadata-search?

Run npx skills add https://github.com/basicmachines-co/basic-memory-skills --skill memory-metadata-search in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/memory-metadata-search/ (personal) or .claude/skills/memory-metadata-search/ (project).

Which AI agents can use memory-metadata-search?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is memory-metadata-search safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains memory-metadata-search?

It is published by basicmachines-co in basicmachines-co/basic-memory-skills. It has 551 recorded installs.

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