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MCP Autodiscovery

ProxySQL v4.0 features a deterministic "Two-Phase Discovery" mechanism that allows LLMs to understand the database structure with high accuracy.

How it works​

The discovery process is typically triggered by an AI agent using the discovery.run_static tool. This process iterates through the backend MySQL/PostgreSQL servers and populates the MCP Catalog.

Phase 1: Static Harvesting​

ProxySQL connects to the configured backend servers and extracts:

  • Schema names.
  • Table and View definitions.
  • Column metadata (types, nullability, defaults).
  • Index definitions.
  • Foreign key relationships.

Phase 2: Metadata Enrichment​

Once the basic structure is harvested, ProxySQL (optionally with LLM assistance) can:

  • Inferred relationships between tables.
  • Generate summaries for complex views or tables.
  • Track "Agent Runs" to maintain context between different LLM sessions.

Deterministic Run IDs​

Every discovery execution is assigned a unique run_id. This allows ProxySQL to maintain a history of the schema state. AI agents can bind themselves to a specific run_id to ensure consistency even if the schema changes while they are processing a request.

Storage (The MCP Catalog)​

The harvested metadata is stored in a local SQLite database named mcp_catalog.db, located in ProxySQL's data directory. This catalog powers the search and retrieval tools used by the MCP server.

For a detailed look at the catalog structure, see the MCP Catalog documentation.