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Glama

Attom

by io.github.pipeworx-io

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds beyond this by detailing the return format: 'top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly.' 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.

Conciseness4/5

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

The description is concise at three sentences, front-loading purpose and usage. It efficiently covers the tool's function, when to use it, and what it returns. Every sentence adds value, though it could be slightly tighter by removing the list of domains.

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?

Given the tool's simplicity (no output schema, straightforward input), the description provides sufficient context: return format, parameter aliases, and usage guidance. It could mention the default limit explicitly, but overall it is complete for a discovery tool.

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 all 6 parameters described in the schema. The description adds context about query aliases and provides example queries ('look up FDA drug approvals', 'analyze housing market trends'), but this is marginal value beyond the schema descriptions. 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?

The description clearly states the tool's purpose: 'Find tools by describing the data or task.' It lists specific data domains (SEC filings, FDA drugs, etc.), making it distinct from sibling tools that target individual domains. As a meta-discovery tool, it differentiates itself effectively.

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 includes explicit guidance: 'Use when you need to browse, search, look up, or discover what tools exist' and 'Call this FIRST when you have many tools available and want to see the option set.' This provides clear context for when to use the tool, though it does not explicitly state when not to use it or name 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

A3.7/5.0
Disambiguation2/5

Several tools are nearly indistinguishable without deep reading: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded all route the same universal query, and the beta currently behaves identically. The prediction-market clister (polymarket_arbitrage, pollymarket_edges, pollymarket_edge_tracker, pollymarket_fill_risk, pollymarket_kalshi_spread) and value-estimation tools (attom_avm, attom_assessment, attom_rental_avm) have fuzzy boundaries that will cause misselection.

Naming Consistency4/5

The vast majority of tools follow a consistent lower_snake-case convention with clear prefixes (attom_*, polymarket_*, pipeworx_*) and verb-noun forms (generate_llms_txt, list_subscriptions, resolve_entity). Minor deviations exist like the bare memory verbs remember, recall, forget and domain-noun names entity_profile, bet_research, but the overall pattern is predictable and readable.

Tool Count2/5

39 tools is well above the comfortable 3-15 range and signals scope creep: the server bundles real-estate, prediction markets, company research, memory, subscriptions, web utilities, and a universal data router. Many of these could be grouped into a smaller number of composite tools, as the descriptions themselves already suggest (e.g. ask_pipeworx as the default entry point).

Completeness3/5

Coverage is deep for prediction markets, company financials, and real-estate, with complete memory and subscription lifecycles (remember/recall/forgeet, subscribe/list/unsubscribe/recent_alerts). However, many advertised domains (weather, clinical trials, news, government records) are only reachable through the generic ask_pipeworx router rather than dedicated tools, and scan_dependency is npm-only, leaving obvious gaps for other ecosystems.

Resources