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Read-only SQLite MCP

Read-only SQLite MCP

by Deependra12349
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

list_databases

Lists the SQLite databases the server is allowed to access, so clients can identify available data sources before inspecting schemas or running read-only queries.

Instructions

List the SQLite databases this server is allowed to access.

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_databases"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations supplied, the description does the minimum: it discloses that results are permission-scoped to what the server may access, which is genuinely useful context. It does not say whether the call is read-only (obvious from 'List'), what shape the output takes (names vs. paths), or whether access can be restricted further.

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?

One sentence, front-loaded with the verb and resource, with no redundant or filler wording. Nothing in it fails to earn its place.

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 zero-argument discovery tool this is nearly sufficient, but with no output schema and no annotations the description should still hint at what comes back (database identifiers usable in list_tables) and how it fits the workflow. That relational guidance is the main gap.

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 tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. Schema coverage is complete and consistent with the empty properties object.

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?

States a specific verb and resource ('List the SQLite databases') plus a scope constraint ('this server is allowed to access'), which cleanly separates it from siblings like list_tables or describe_table. It stops short of explicitly naming the sibling relationship, but the resource noun is unambiguous.

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?

Usage is only implied: an agent can infer this is a discovery step before list_tables or read_query, but the description never says so, nor does it mention prerequisites or when not to call it. No alternative is named.

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

Deploy Server

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