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CASDA MCP Server

CASDA MCP Server

by jbwod
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Validate CASDA ADQL

casda_validate_adql
Read-onlyIdempotent

Validate ADQL SELECT statements locally to check compliance with the SELECT-only policy before submitting to CASDA.

Instructions

Validate ADQL against the SELECT-only policy without contacting CASDA.

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": "casda_validate_adql"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesCandidate ADQL SELECT statement to validate locally.

Output Schema

NameRequiredDescriptionDefault
errorNo
queryYes
validNo
max_rowsYes
provenanceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already note readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds that validation occurs locally without contacting CASDA, which is valuable behavioral context.

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 wasted words.

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

Completeness5/5

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

Given the single parameter, high schema coverage, and presence of an output schema, the description fully covers the tool's purpose and behavior.

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

Parameters5/5

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

The only parameter 'query' has a description that clarifies it is a candidate ADQL SELECT statement for local validation, adding meaning beyond the schema property name.

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 validates ADQL against a SELECT-only policy and does so without contacting CASDA. This distinguishes it from siblings like casda_tap_query or casda_build_adql.

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 implies when to use (local validation before submission), but does not explicitly state alternatives or when not to use. However, given the sibling tool names, the use case is clear.

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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