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database-analytics-mcp

database-analytics-mcp

by khuyentran1401
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

list_tables

Retrieve the names of all tables in the connected SQLite database to understand its schema and structure for further analysis.

Instructions

List all tables in the connected database.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_tables"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It adds the context that the tool operates on the 'connected database', which hints at a prerequisite state, but it does not explicitly state that it is read-only, how errors are handled, or what happens if no connection exists. This is minimal but acceptable for a simple listing operation.

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 a single, front-loaded sentence with no unnecessary words. It delivers the essential purpose clearly and directly.

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?

The tool is simple, has no parameters, and an output schema exists, so the description does not need to explain return values. The description captures the core function, but could optionally mention that it requires a prior connect_db call for full completeness. Still, it is sufficient for its simplicity.

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

Parameters4/5

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

The input schema has zero parameters, and the baseline for 0 params is 4. The description adds no parameter-specific details because there are none, and no additional context is needed beyond what the schema already indicates.

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 'List all tables in the connected database' with a specific verb (List), a resource (tables), and a context (connected database). This distinguishes it from sibling tools like execute_query and connect_db by focusing specifically on enumerating tables.

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

Usage Guidelines3/5

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

The description implies usage after establishing a database connection (via 'connected database'), but it does not explicitly state when to use this tool versus alternatives like execute_query. There are no exclusions or alternative recommendations, so the usage guidance is implied rather than explicit.

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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