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MCP JSON Document Collection Server

by jimpick

list_json_doc_databases

Discover available JSON document databases to identify which collections you can access for document management and querying operations.

Instructions

Returns the list of JSON document databases. Use this to understand which databases are available before trying to access JSON documents.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Handler implementation for the 'list_json_doc_databases' tool. Queries the localJsonDbCollection by 'name' index, extracts database names from documents, and returns them as a JSON string in the tool response.
    case "list_json_doc_databases": {
      const results = await localJsonDbCollection.query<string, JsonDocDb>("name", {
        includeDocs: true,
        descending: true,
      })
      const dbNames = results.rows.flatMap(row => row.doc ? [row.doc.name] : []);
    
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(dbNames)
          }
        ]
      }
    }
  • src/index.ts:117-127 (registration)
    Registration of the 'list_json_doc_databases' tool in the ListTools response, specifying name, description, and input schema (no required parameters).
    {
      name: "list_json_doc_databases",
      description:
        "Returns the list of JSON document databases. " +
        "Use this to understand which databases are available before trying to access JSON documents.",
      inputSchema: {
        type: "object",
        properties: {},
        required: [],
      },
    },
  • Input schema for the 'list_json_doc_databases' tool, defining an empty object with no properties or required fields.
    inputSchema: {
      type: "object",
      properties: {},
      required: [],
    },
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It implies a read-only operation by stating 'Returns the list,' but does not disclose behavioral traits such as whether it requires authentication, has rate limits, returns paginated results, or includes metadata. The description adds basic context (it's for understanding available databases) but lacks details on how the list is formatted or any constraints.

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 appropriately sized and front-loaded: the first sentence states the core purpose, and the second provides usage guidance. Both sentences earn their place by adding value—clarifying the action and when to use it—with no wasted words or redundancy.

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?

Given the tool's low complexity (0 parameters, no annotations, no output schema), the description is somewhat complete but has gaps. It explains the purpose and usage context adequately, but without annotations or output schema, it should ideally describe the return format (e.g., list of names, IDs, or metadata) and any prerequisites. The description is minimal but functional for a simple listing tool.

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 has 0 parameters, and schema description coverage is 100% (since there are no parameters to describe). The description does not need to add parameter semantics, but it implicitly confirms there are no inputs by not mentioning any. This meets the baseline of 4 for zero parameters, as no compensation is required.

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 clearly states the tool's purpose: 'Returns the list of JSON document databases.' It specifies the verb ('Returns') and resource ('JSON document databases'), making the action and target explicit. However, it does not distinguish this tool from its siblings (e.g., 'create_json_doc_database' or 'delete_json_doc_database'), which would require mentioning it's a read-only listing operation versus mutation tools.

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 provides clear context for when to use this tool: 'Use this to understand which databases are available before trying to access JSON documents.' This implies it should be used as a preliminary step before operations like loading or querying documents. However, it does not explicitly state when not to use it or name alternatives among siblings (e.g., 'query_json_docs_from_db' might also list databases indirectly), missing full differentiation.

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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