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MCPg - Production-grade PostgreSQL MCP Server

List indexes

list_indexes
Read-only

Retrieve indexes defined on a table, including method, CREATE INDEX definition, and partition status. Set fresh=true to bypass cache and re-read live schema changes.

Instructions

List the indexes defined on a table. Set fresh=true to bypass the cache and re-read live (e.g. after a schema change). Returns a list of objects with name, method (btree / gin / gist / brin / hash / spgist / hnsw / ivfflat / …), definition (the CREATE INDEX statement), and partitioned.

Example: list_indexes(schema='public', table='users')

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
freshNo
tableYes
schemaYes
databaseNoOptional: target a configured secondary (read-only) database by name; omit for the primary. Call list_databases to see the configured ids.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations declare readOnlyHint=true, and the description adds behavioral details: it can bypass cache via fresh=true, and it returns a structured list of index objects. This adds value beyond annotations by explaining the caching behavior and exact return fields.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short, front-loaded with purpose, includes an illustrative example, and succinctly explains the return structure. Every sentence earns its place with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the output schema (implied), the description covers return fields and caching behavior. It lacks parameter descriptions for schema and table, but the schema partially covers them. For a list tool with moderate complexity, it is mostly complete but could be slightly more thorough.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With only 25% schema description coverage, the description should compensate but only explains fresh in context; schema, table, and database are not described in the description. The database parameter has a schema description but is absent from the tool description. This leaves meaning unclear for three of four parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action (list) and the resource (indexes on a table), specifying required parameters schema and table. It distinguishes the tool from siblings by focusing on indexes, which is a unique purpose among many database introspection tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a specific usage scenario for the fresh parameter (bypass cache after schema change) and includes an example call. However, it does not explicitly compare with alternatives like describe_table or list_constraints, which might also expose index information, leaving some ambiguity about when to choose this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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