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kenb38291-tech

fastmcp-sqlite

query

Execute SQL against SQLite with parameter binding, choosing table, vertical, or JSON output. Includes safety limits via opcode watchdog and cell truncation.

Instructions

Execute a SQL query against a SQLite database with parameter binding and token-efficient formatting. Returns results as Markdown table, vertical record view, or JSON. Protected by opcode execution watchdog and cell truncation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dbNoOptional path to SQLite database file. Defaults to configured default database.
sqlYesThe SQL query to execute in SQLite engine.
formatNoOutput format: 'table' (compact Markdown), 'vertical' (wide records), or 'json'.table
paramsNoOptional query parameters (positional list, named dict, or JSON string).
readonlyNoEnforce read-only mode via PRAGMA query_only and AST authorizer.
cell_max_charsNoMaximum characters per cell before truncation (default: 200, 0 = unlimited).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full disclosure burden. It usefully mentions parameter binding, token-efficient formatting, and protections like opcode watchdog and cell truncation. However, it does not disclose whether writes can occur when readonly=false, nor does it describe side effects, failures, or error behavior.

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?

Three tight sentences, front-loaded with the verb and resource, followed by output-format variety and safety protections. No filler, no redundant restatement of the schema.

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 rich input schema, output schema, and protective details in the description, an agent has enough to invoke the tool correctly. The main missing piece is guidance on when to choose this over sibling tools, which prevents a higher score.

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%, so the schema already documents all six parameters. The description's mention of parameter binding and output formats is consistent but adds little meaning beyond the parameter descriptions already present. Baseline 3 applies.

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 opens with a specific verb and resource: 'Execute a SQL query against a SQLite database.' It also names output formats, making the tool's core function clear. It does not explicitly distinguish itself from siblings like explain or export_query, though the function is inferable.

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 intended use is implied by 'Execute a SQL query,' but there is no explicit when-to-use guidance or mention of alternatives such as explain, export_query, or schema. An agent gets no direct help choosing among sibling tools.

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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