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Insight Digger MCP

Insight Digger MCP

by sandsiv
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

list_sources

Discover and filter available data sources to begin analysis. Search by name to find relevant datasets with details like type, columns, and update dates.

Instructions

šŸ”’ [Requires Authentication] List available data sources. This is typically the FIRST interactive step in data analysis. Ask user to provide a search term to filter the sources. šŸ”„ Auto-Cached: apiUrl and jwtToken are automatically provided from your authentication session. Only provide 'search', 'page', and 'limit' parameters as needed. Ask the user for a source name to search first. Returns: {{'count': int, 'data': [{'id': str, 'title': str, 'type': str, 'updated': str, 'numberOfColumns': int}]}}.

āš ļø Please authenticate first by calling the setup_authentication tool above. This tool will become fully functional after authentication.

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_sources"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
pageNo
searchNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations provided, the description carries full burden and discloses key behavioral traits: authentication requirement ('Requires Authentication'), auto-caching behavior ('šŸ”„ Auto-Cached'), and guidance to ask users for search terms. It doesn't mention rate limits or error handling, but covers essential operational context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with purpose and authentication requirements, but contains some redundancy (e.g., 'Ask user to provide a search term' and 'Ask the user for a source name to search first') and could be more streamlined. The emojis and formatting help readability but add visual clutter.

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?

For a 3-parameter tool with no annotations and no output schema, the description provides good context: authentication prerequisites, parameter guidance, and detailed return format. It lacks information about error cases or rate limits, but covers the essential operational flow adequately.

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?

With 0% schema description coverage, the description compensates by explaining parameter usage: 'search' for filtering sources, 'page' and 'limit' for pagination, and clarifies that 'apiUrl and jwtToken are automatically provided'. It doesn't detail default values or constraints, but adds meaningful context beyond the bare schema.

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's purpose with a specific verb ('List') and resource ('available data sources'), and distinguishes it from siblings by emphasizing it's the 'FIRST interactive step in data analysis' rather than analysis or configuration tools like 'analyze_charts' or 'create_configuration'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use ('typically the FIRST interactive step in data analysis') and when not to use ('Please authenticate first by calling the `setup_authentication` tool above'), with clear prerequisites and named alternatives for authentication.

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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