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Glama

Discover Tools

discover_tools
Read-onlyIdempotent

Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real estate, ClinicalTrials, USPTO patents, weather, news, crypto, stocks. Returns the top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly, no second schema lookup needed. Call this FIRST when you have many tools available and want to see the option set (not just one answer).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoAlias for query.
taskNoAlias for query.
limitNoMaximum number of tools to return (default 20, max 50)
queryYesNatural language description of what you want to do (e.g., "analyze housing market trends", "look up FDA drug approvals", "find trade data between countries"). Accepts task, q, description, search as aliases.
searchNoAlias for query.
descriptionNoAlias for query.

Schema Changelog

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

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already provide readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description adds valuable behavior: 'Returns the top-N most relevant tools with names, descriptions, and full input schemas — each result is ready to call directly'. No contradictions.

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

Conciseness4/5

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

Description is moderately concise, front-loads purpose, and provides enough detail without excessive redundancy. Could be slightly shorter but effectively structured.

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 discovery tool with 6 params (mostly aliases) and no output schema, the description covers purpose, usage, output format, and sample queries. Provides complete context for an agent to use correctly.

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

Parameters3/5

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

Schema has 100% coverage with descriptions. Description adds minimal value beyond schema: mentions 'top-N' implying limit parameter, but schema already explains limit. Baseline 3 is appropriate.

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?

Description clearly states the verb 'Find tools' and resource 'tools', lists numerous specific domains (SEC filings, financials, etc.), and distinguishes from siblings by advising to call this FIRST to see available options.

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?

Explicitly states when to use: 'when you need to browse, search, look up, or discover what tools exist' and advises 'Call this FIRST when you have many tools available'. Clear context but no explicit when-not to use or alternatives.

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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TDQS

A4.2/5.0
Disambiguation4/5

Most tools have distinct purposes with detailed descriptions; however, the family of ask_pipeworx tools (beta, grounded) and deep_research could cause selection ambiguity despite clear documentation.

Naming Consistency3/5

Tool names lack a consistent pattern; they mix imperatives, descriptive nouns, and domain prefixes. While overall readable, the lack of uniformity makes it harder to predict naming conventions.

Tool Count4/5

34 tools is on the higher side but still within reasonable range given the broad scope (data queries, prediction markets, scraping, subscriptions, memory). Each tool appears purposeful, though some consolidation (e.g., ask_pipeworx variants) could reduce count.

Completeness4/5

The tool set covers a wide range of tasks from data querying to prediction market analysis and entity management. Minor gaps might exist (e.g., no direct social media data), but the overall coverage is extensive and sufficient for the platform's purpose.