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Glama

econdata

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. Added

TDQS

A4.3/5.0
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, so the safety profile is covered. The description adds valuable behavioral context by disclosing that results include full input schemas with curated examples and are ready to call directly, eliminating a second schema lookup. It also advises calling this tool first, which is a useful process hint. No contradiction 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 front-loaded with the core purpose and includes a comprehensive list of domains, which is informative but slightly lengthy. The structure flows logically from purpose to usage to return details to strategic advice. Every sentence contributes value, though the domain enumeration could be trimmed without losing essential meaning.

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 adequately covers the tool's role as a discovery mechanism, listing covered domains, return details (top-N tools with schemas and examples), and the recommendation to use it early in the exploration process. Given there is no output schema, the description does not need to detail return structures. Minor omissions like pagination or query phrasing guidance are compensated by the schema examples and the overall clarity.

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% per context signals, so the schema fully documents all six parameters, including aliases for 'query' and the 'limit' parameter. The description adds minimal parameter semantics beyond the schema, only implicitly referencing the query via 'describing the data or task' and the limit via 'top-N'. This matches the baseline of 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 tool's purpose: 'Find tools by describing the data or task.' It enumerates the covered domains (SEC filings, financials, FDA drugs, etc.) and distinguishes itself from sibling tools by acting as a discovery layer rather than a domain-specific data retrieval tool. The verb 'find' and the resource 'tools' are specific and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage guidance: 'Use when you need to browse, search, look up, or discover what tools exist for...' and 'Call this FIRST when you have many tools available and want to see the option set (not just one answer).' This clearly indicates when to use the tool and contrasts with using specific tools for direct answers, fulfilling the 'when/when-not' requirement.

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

A3.9/5.0
Disambiguation4/5

Most tools have distinct purposes due to detailed descriptions. Some overlap exists, especially among research tools (ask_pipeworx, ask_pipeworx_grounded, deep_research) and prediction market tools, but boundaries are clear enough for an agent to differentiate.

Naming Consistency4/5

The majority follow a consistent verb_noun pattern with underscores (e.g., get_cpi, list_subscriptions). A few deviations exist (e.g., forget, recall, pipeworx_feedback using a prefix), but overall the pattern is predictable.

Tool Count2/5

With 34 tools, the server exceeds the typical well-scoped range of 3-15 tools. While it covers many domains, the high number makes the set feel heavy and harder to navigate, warranting a score of 2 according to calibration.

Completeness4/5

The tool set is comprehensive for its broad scope, covering economic data, company research, prediction markets, and utilities. Minor gaps exist (e.g., missing explicit GDP or stock quote tools), but the powerful ask_pipeworx meta-tool fills many gaps.

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