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Read-only SQLite MCP

Read-only SQLite MCP

by Deependra12349
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

list_tables

Lists all tables and views in a specified allow-listed SQLite database so you can inspect available data structures before querying.

Instructions

List tables and views in a database.

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": {
      "database": "<database>"
    },
    "name": "list_tables"
  }
}

Input Schema

NameRequiredDescriptionDefault
databaseYesDatabase alias or path given at server startup

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations supplied, the description must carry the behavioral burden. It does disclose one useful trait beyond the name: that views are included alongside tables. However, it says nothing about system-table filtering, result ordering, result size, or the fact that this is a non-mutating read, which an agent would want to know.

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?

A single short sentence with the resource front-loaded and no wasted wording. Nothing could be removed without losing information.

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

Completeness3/5

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

For a one-parameter read tool this is close to adequate, but with no output schema and no annotations, the description omits what the listing returns (names only, schema-qualified names, views mixed in) and any guidance on following up with describe_table. It is minimum viable rather than complete.

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?

Schema description coverage is 100% and the single parameter 'database' is documented in the schema as an alias or path given at server startup. The description adds no meaning beyond that, which meets the baseline for high coverage but earns no extra credit.

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

Purpose4/5

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

The description gives a specific verb and resource ('List tables and views') and scopes it to 'a database', which distinguishes it from list_databases in the sibling set. It stops short of naming or contrasting with siblings like describe_table or table_stats, so it is clear but not fully differentiated.

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

Usage Guidelines2/5

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

There is no explicit when-to-use guidance, no prerequisites, and no mention of alternatives such as list_databases or describe_table. The agent must infer from the name that this is a discovery step before describing or querying tables.

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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