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bbaw-dse-mcp

bbaw-dse-mcp

by telota
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

sd_list_collections

List sub-collections in a database to explore its structure and identify collection names for querying digital scholarly editions.

Instructions

List available sub-collections in the database.

PURPOSE: Explore the database structure and find available collections.

WHEN TO USE:

  • User wants to know what data is available

  • Exploring the database structure

  • Finding the correct collection name for other queries

Args: parent: Parent collection path (relative to data_path). Empty = root.

Returns: Collection object with path, collections list, and document_count

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": "sd_list_collections"
  }
}

Input Schema

NameRequiredDescriptionDefault
parentNo

Output Schema

NameRequiredDescriptionDefault
pathYesFull path to the collection
collectionsNoList of subcollections
document_countYesNumber of documents in the collection

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the return structure (collection object with path, collections list, document_count) and the parent path meaning. However, it stops short of explicitly stating read-only behavior or any limitations, which would strengthen it. Since it's a simple list tool, this is adequate but not exceptional.

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 well-structured with clear labels (PURPOSE, WHEN TO USE, Args, Returns) and front-loads the main purpose. No redundant text; each sentence serves a function.

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 tool's simplicity, one parameter, and existing output schema, the description covers purpose, usage, parameter, and return shape. It fully equips the agent to select and invoke the tool correctly.

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 single parameter 'parent' is fully explained in the description: 'Parent collection path (relative to data_path). Empty = root.' This adds semantics beyond the bare schema, compensating for 0% schema coverage.

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 opens with 'List available sub-collections in the database' — a specific verb and resource. It explicitly states PURPOSE to explore database structure, which distinguishes it from sibling sd_list_collection_contents that lists contained items.

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?

Provides a dedicated WHEN TO USE section with clear scenarios such as 'User wants to know what data is available' and 'Finding the correct collection name for other queries.' While it doesn't explicitly name alternatives or exclusions, the context is well-defined.

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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