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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. Added

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds value by explaining the return format: 'top-N most relevant tools with names, descriptions, and full input schemas' and the convenience of no second lookup. This gives the agent insight into what the tool actually does beyond static annotations.

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 two sentences long and front-loaded with the core purpose. It includes a lengthy list of domains, which is useful for the agent to understand scope, but the list is somewhat long. Every sentence serves a purpose, with no redundant phrases.

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?

The description covers the tool's purpose, when to use it, and what it returns, which is particularly important since there is no output schema. It omits details like pagination or error handling, but given the tool's simplicity and the strong annotations, it is sufficiently complete for an agent to select and invoke it 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 description coverage is 100%, so the schema fully documents the `query` parameter and its aliases. The description adds no additional parameter details beyond 'describing the data or task,' which is already captured in the schema. Baseline 3 is appropriate; the description does not go beyond the structured information.

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: 'Find tools by describing the data or task.' It specifies the resource (tools) and the action (browse, search, look up, discover), and distinguishes itself from siblings by emphasizing it returns a list of tools rather than performing a single task. The phrase 'Call this FIRST when you have many tools available' differentiates it as a meta-tool.

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 clear usage context: 'Use when you need to browse, search, look up, or discover what tools exist' and lists example domains. It also provides an exclusion: 'not just one answer.' However, it does not explicitly name alternative tools, so it stops short of a full 5.

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

A3.5/5.0
Disambiguation1/5

Several tools are effectively indistinguishable or near-duplicates: ask_pipeworx_beta is explicitly an identical copy of ask_pipeworx with no active experimental changes, and ask_pipeworx_grounded is a variant of the same router. discover_tools, suggest_questions, deep_research, and the ask_pipeworx family also heavily overlap as discovery/answer surfaces, while bet_research, polymarket_edges, polymarket_arbitrage, and polymarket_fill_risk create a dense prediction-market cluster with fuzzy boundaries.

Naming Consistency3/5

Everything is snake_case and many names follow a readable verb_noun pattern (search_works, resolve_entity, validate_claim, suggest_questions), but conventions are mixed: noun-first domain-prefixed names (polymarket_edges, pipeworx_feedback, pipeworx_trending), bare verbs (remember, forget, recall), and adjective_noun names (deep_research, recent_changes) coexist. The inconsistency is not chaotic, but it is not a unified scheme.

Tool Count2/5

36 tools is well over the 25-tool threshold for a heavy toolset, and the count is inflated by many tangential concerns: memory, subscriptions, feedback, trending, npm dependency scanning, AI visibility, and llms.txt generation. Only a small subset actually serves the stated OpenAlex/scholarly purpose, so the size feels bloated rather than well-scoped.

Completeness2/5

For a server named openalex, the scholarly surface is incomplete: works support search and fetch, but authors and institutions only support search with no get-by-ID, concepts support get but no search, and major OpenAlex resource types like sources, publishers, funders, and topics are absent. The many non-OpenAlex tools do not fill these gaps and instead dilute the domain coverage.