Frontmatter MCP

# 3. Use DuckDB for SQL queries Date: 2025-11-28 ## Status Accepted ## Context We needed to decide how to filter and aggregate frontmatter data. Candidates: - pandas: Higher learning curve than SQL, difficult to use from MCP clients - SQLite: Weak array operations, limited JSON function support - jq-style DSL: High implementation cost, also requires learning - DuckDB: Expressive SQL, array operations, in-memory execution ## Decision Adopted DuckDB as the in-memory SQL engine. ## Consequences - Complex queries possible with WHERE, GROUP BY, JOIN, etc. - Easy array expansion with `UNNEST` and `from_json()` - Fast in-memory execution - No server process required, embeddable as a Python library - Depends on DuckDB's SQL dialect