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Glama

Epa Echo

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

A4.5/5.0
Behavior4/5

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

Annotations already indicate readOnly, idempotent, and non-destructive behavior. The description adds valuable behavioral details: it returns top-N most relevant tools with full schemas and curated examples, ready to call directly without a second lookup. This goes beyond the annotations without contradicting them.

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

Conciseness5/5

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

The description is three sentences, starting with the core purpose, followed by usage guidance and return value details. No redundant or extraneous content. Every sentence earns its place.

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?

Given the tool's complexity (discovery among many siblings) and the absence of an output schema, the description is complete. It explains what it does, when to use it, and what it returns (names, descriptions, schemas, examples). No gaps for an AI agent to misinterpret.

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% (all 6 parameters described in schema). The description does not add significant new meaning beyond the schema; it mentions accepting natural language queries and aliases, which are already documented. Baseline score of 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 numerous specific domains (SEC filings, FDA drugs, etc.), making the scope obvious. It distinguishes itself from sibling tools by being a discovery/lookup tool rather than a specific data source tool.

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 explicitly recommends using this tool when browsing or discovering available tools: '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.' This provides clear context and excludes scenarios where the user already knows the target tool.

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
Disambiguation2/5

ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded form a tight cluster, and the beta variant is explicitly identical to ask_pipeworx today. Several meta-tools like discover_tools, suggest_questions, and deep_research also overlap in discovery-oriented usage, so an agent must read carefully to pick the right one.

Naming Consistency3/5

Names are uniformly lowercase with underscores and mostly descriptive, but the conventions are mixed: verb_noun tools like validate_claim and list_subscriptions sit alongside noun_phrase tools like entity_profile and polymarket_arbitrage, plus bare verbs like remember and subscribe. It is readable but not a single predictable pattern.

Tool Count2/5

36 tools is well above the 25+ threshold, and the surface spans unrelated domains: EPA ECHO data, general Pipeworx research, Polymarket betting, memory, npm scanning, and AI visibility checks. For a server named 'Epa Echo', most tools feel out of scope and the collection seems like several separate servers merged together.

Completeness4/5

The EPA ECHO subset provides a solid facility-search, violations, compliance-history, and enforcement-action lifecycle. The broader Pipeworx surface also covers lookups, grounded answers, deep research, entity profiling, subscriptions, and memory, with only minor workaround-level gaps such as no dedicated ECHO permit/emissions detail tool.

Resources