Skip to main content
Glama
ncejda-g2

Snowflake MCP Server

by ncejda-g2
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Refresh Catalog

refresh_catalog

Refresh the Snowflake schema catalog by scanning all accessible databases to index tables, schemas, and columns. Use after schema changes or cache expiry to ensure accurate metadata.

Instructions

Refresh the schema catalog by scanning all accessible Snowflake databases.

This tool queries INFORMATION_SCHEMA across all databases to build a comprehensive
index of tables, schemas, and columns. The cache has a 5-day TTL.

Use this tool when:
- First connecting to Snowflake
- Schema changes have been made
- Cache has expired (after 5 days)

Parameters:
- force: Force refresh even if cache is not expired (default: false)
- resume: Resume from checkpoints if they exist (default: true)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
forceNo
resumeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.0.3
    • addedInput schema / additionalProperties
      Added value: +false
    • removedInput schema / properties / force / title
      Removed value: -"Force"
    • removedInput schema / properties / resume / title
      Removed value: -"Resume"
  2. Changed1 schema field changedv1.0.0
    • changedOutput schema / (root)
      Previous value: -{
-  "additionalProperties": true,
-  "type": "object"
-}New value: +null
  3. First observedv0.2.3

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals that the tool queries INFORMATION_SCHEMA, maintains a cache with a 5-day TTL, supports force refresh, and can resume from checkpoints—useful operational context beyond the schema. It does not mention runtime cost or whether the operation is synchronous, but it covers the core behavioral traits.

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 well-structured and front-loaded: the core action is stated first, followed by mechanism, TTL, use cases, and parameter explanations. Every sentence adds useful information, with no filler or redundancy.

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?

For a tool with two optional boolean parameters, no output schema, and no annotations, the description provides enough context to invoke it correctly: what it does, when to use it, and what the parameters control. It does not specify the return value or expected response, but that is not critical for a catalog refresh operation.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate, and it does. Both parameters are explained with meaningful semantics: 'force' means refresh even if cache is not expired, and 'resume' means continue from existing checkpoints. This goes well beyond the bare boolean schema definitions.

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 states a specific verb ('refresh') and resource ('schema catalog') and clarifies the scope ('scanning all accessible Snowflake databases'). This clearly differentiates it from sibling tools like execute_query or find_tables, which handle querying and table discovery rather than catalog maintenance.

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 explicit when-to-use scenarios: first connecting to Snowflake, after schema changes, or when the cache has expired after 5 days. It does not explicitly describe when not to use it or name alternatives, so it falls just short of a 5.

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

Deploy Server

Other Tools