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LiveDataLink

by io.github.blackboxfoundry

list_tool_groups

Read-onlyIdempotent

List every tool group (category) available on LiveDataLink with its domain count and tool count. Use this to discover which groups exist, then connect to https://livedatalink.ai/mcp?groups=<comma,separated> (or send the header X-Tool-Groups: <comma,separated>) to load ONLY those groups. Filtering keeps the tool list small so an agent selects tools accurately and uses less context. Free to call, no credits consumed. Optional 'query' filters group names.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoOptional substring to filter group names (case-insensitive).

Schema Changelog

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

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

The annotations already establish readOnly, idempotent, and non-destructive behavior. The description adds meaningful behavioral context beyond the annotations: it is 'Free to call, no credits consumed,' and it returns domain counts and tool counts for every group. No contradictions with annotations.

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 front-loaded with the core purpose, then gives a concise usage workflow, the context-efficiency rationale, the cost note, and the optional parameter. Every sentence serves a clear purpose with no repetition or filler.

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?

For a simple list tool with one optional parameter and no output schema, the description fully covers what the tool returns, how to use the result, when to call it, the cost, and the filtering behavior. Nothing essential is missing for correct selection and invocation.

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?

Schema coverage is 100%, so the schema already documents the 'query' parameter. The description adds the clarifying detail that the query is an 'Optional substring' and, combined with the schema, that filtering is case-insensitive. This is enough for correct invocation.

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 states a specific verb and resource: 'List every tool group (category) available on LiveDataLink with its domain count and tool count.' It clearly identifies the output and distinguishes this discovery/metadata tool from the many domain-specific sibling 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 gives explicit guidance on when to use the tool: 'Use this to discover which groups exist,' followed by concrete next steps for loading only the desired groups via URL or header. It also explains the benefit of filtering for context efficiency, though it does not explicitly contrast with an alternative discovery tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All LiveDataLink toolsInspect
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TDQS

B3.3/5.0
Disambiguation2/5

Several tool clusters overlap heavily—company due-diligence and risk tools (counterparty_risk_score, company_trust_check, entity_dossier, issuer_diligence_dossier, resolve_entity, entity_resolve), carrier vetting tools, sanctions screening tools, and recall tools all have subtle boundary distinctions. While descriptions are detailed, an agent navigating 294 tools will frequently struggle to pick the right one.

Naming Consistency3/5

Most tools follow a readable snake_case domain-prefix pattern (fdic_, edgar_, sanctions_, congress_), which helps. However, verb placement is inconsistent—search_available_datasets vs cdc_dataset_query, resolve_entity vs entity_resolve—and synonyms like search, lookup, get, detail, fetch, and status are used interchangeably.

Tool Count1/5

294 tools is an extreme number for a single MCP server, far beyond what an agent can reliably hold in context or select from accurately. The presence of tool-group discovery helpers mitigates but does not solve the fundamental scale problem.

Completeness4/5

The data breadth is genuinely extensive, covering finance, health, legal, real estate, transportation, energy, cyber, education, and many other domains, often with generic query fallbacks. Still, some capabilities are shallow or incomplete—package tracking stops at a link, property tools are demo-only in places, and caselaw coverage is limited—so it is not a fully complete surface.

Resources