Skip to main content
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. Changed5 schema fields changed
    • addedInput schema / properties / description
      Added value: +{
      +  "description": "Alias for query.",
      +  "type": "string"
      +}
    • addedInput schema / properties / q
      Added value: +{
      +  "description": "Alias for query.",
      +  "type": "string"
      +}
    • changedInput schema / properties / query / description
      Previous value: -"Natural language description of what you want to do (e.g., \"analyze housing market trends\", \"look up FDA drug approvals\", \"find trade data between countries\")"New value: +"Natural 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."
    • addedInput schema / properties / search
      Added value: +{
      +  "description": "Alias for query.",
      +  "type": "string"
      +}
    • addedInput schema / properties / task
      Added value: +{
      +  "description": "Alias for query.",
      +  "type": "string"
      +}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "query": "look up FDA drug approvals"
      +  },
      +  {
      +    "query": "analyze housing market trends"
      +  }
      +]
  3. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Beyond the annotations (read-only, idempotent, non-destructive), the description discloses the return format: top-N tools with names, descriptions, full schemas, and curated examples, and that results are directly callable without further lookup. This adds useful behavioral context about output and integration.

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?

The description is three sentences, front-loaded with the core purpose, then listing domains and return behavior. While the domain list is lengthy, it is informative and each sentence earns its place. Slight redundancy with schema examples exists, but overall structure is efficient.

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 discovery tool with no output schema, the description compensates well by explaining what is returned (names, descriptions, schemas, examples) and when to use it first. It covers usage context and result readiness, making it largely complete despite minor omissions like error behavior.

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 coverage is 100% with descriptions for all parameters, including aliases. The description adds only minimal semantic value (e.g., 'describing the data or task') but does not detail parameter formats or edge cases beyond the schema, aligning with the baseline 3 for high 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 clearly states the verb+resource: 'Find tools by describing the data or task.' It distinguishes itself from siblings by specifying its role as a discovery meta-tool ('Call this FIRST when you have many tools available') and gives a concrete list of covered domains, making its purpose unmistakable.

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 explicitly says 'Use when you need to browse, search, look up, or discover what tools exist' and 'Call this FIRST when you have many tools available...' providing clear context for when to invoke. It lacks explicit when-not conditions or named alternatives, but the 'not just one answer' phrase adds nuance.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.5/5.0
Disambiguation2/5

The set mixes several unrelated domains (LibriVox, Pipeworx data lookup, Polymarket betting, memory, subscriptions), and within those domains there is heavy overlap: ask_pipeworx/ask_pipeworx_beta/ask_pipeworx_grounded/deep_research all route to the same 5,798 tools, and polymarket_edges/polymarket_arbitrage/polymarket_edge_tracker/polymarket_fill_risk/bet_research all scan prediction-market opportunities. An agent can easily pick the wrong tool when the same question fits several of them.

Naming Consistency3/5

Names are mostly lowercase snake_case, but the patterns are inconsistent across domains: some are verb-first (ask_pipeworx, compare_entities, generate_llms_txt), some are noun-first (audiobook, tracks, polymarket_edges), and pluralization varies (audiobook vs audiobooks, authors vs tracks). The Pipeworx family is internally consistent, but the overall set has no unified convention.

Tool Count2/5

35 tools is heavy for a server named Librivox, and only 4 of them (audiobook, audiobooks, authors, tracks) actually relate to LibriVox. The remaining ~31 tools (Pipeworx, Polymarket, memory, subscriptions, AI visibility) make the count far exceed what the server name and apparent purpose suggest.

Completeness2/5

For a LibriVox-focused server, the tool surface is thin: search and fetch audiobooks, search authors, and list tracks, but no browse by genre, no reader/search-by-reader, no language filter, no author detail endpoint. The Pipeworx side is quite comprehensive, but it does not make up for the gap relative to the server's stated identity.