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snowflake-analytics-mcp-server

snowflake-analytics-mcp-server

by Analytics-model-LTD
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TypeScript
Remote

Execute query

execute_query

Run SQL queries on Snowflake and retrieve results as JSON. Read-only by default for SELECT, SHOW, DESCRIBE, and WITH statements.

Instructions

Run a SQL query and return rows as JSON. Read-only by default (SELECT/SHOW/DESCRIBE/WITH). Set SNOWFLAKE_READ_ONLY=false to allow writes/DDL.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "execute_query"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesThe SQL statement to execute.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses the read-only default behavior and the mechanism to allow writes/DDL, which is critical for an agent to understand the tool's safety profile. It also mentions the output format (rows as JSON). It does not detail error handling or performance implications, but the key behavioral trait (read-only vs. write) is clearly disclosed.

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 two sentences long, front-loaded with the primary purpose, and every sentence adds value. The first sentence states the core function and output, the second provides a critical behavioral detail (read-only default and how to override). 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 tool's complexity (a general SQL executor), the description is complete enough. It covers the main purpose, output format, and the read-only/write behavior. It does not explain return value structure, but since there is no output schema, the description could have added a bit more about the JSON structure, but the core information is sufficient for an agent to use the tool correctly.

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

Parameters3/5

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

The schema description coverage is 100% for the single parameter 'query', which is described as 'The SQL statement to execute.' The description adds minimal extra meaning beyond the schema, but it does clarify that the query is a SQL statement and implies it can be any valid SQL. Since the schema already covers the parameter, a baseline of 3 is appropriate.

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 tool's purpose: 'Run a SQL query and return rows as JSON.' It specifies the verb (run), the resource (SQL query), and the output format (JSON). It also distinguishes itself from sibling tools like list_databases and list_tables by being the general query execution tool, while siblings are for metadata listing.

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 clear context on when to use the tool: for running SQL queries. It also gives a usage guideline by stating the default read-only behavior and how to enable writes (setting SNOWFLAKE_READ_ONLY=false). However, it does not explicitly mention when not to use it or name alternative tools for specific tasks, though the sibling tools' purposes are implied.

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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