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Glama

nvd

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

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive. The description adds valuable behavioral context: returns top-N tools with names, descriptions, full input schemas, and curated examples, and notes results are ready to call directly without a second schema lookup. It also clarifies the 'discover' nature. While it doesn't cover pagination or error cases, it adds meaningful context beyond 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 then provides useful detail about return format and use-case timing. The domain list is long but valuable for guiding the agent. While two sentences are efficient, the domain enumeration makes it slightly verbose, but every element 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?

The description is complete for a discovery tool: it explains what the tool returns (top-N tools with schemas and examples), how to invoke it (natural language query), when to use it first, and what domains it covers. No output schema exists, but the description fully describes the return value. The list of example queries in the schema complements this. Given the tool's simplicity and richness of annotations, nothing essential is missing.

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 parameters, including aliases, have descriptions). The description adds the natural-language examples and 'top-N' scalability, but substantially the schema already explains the query/limit semantics. Since coverage is high, a baseline of 3 is appropriate; the description doesn't need to compensate.

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 differentiates from siblings by positioning itself as a discovery meta-tool, with a specific verb ('find') and resource ('tools') and a list of covered domains (SEC filings, financials, FDA drugs, etc.). This makes it distinct from SIBLING tools like deep_research or search_cves.

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?

Explicitly states when to use: '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 (not just one answer).' This provides clear context and prioritization relative to alternatives, even though it doesn't explicitly name rejected 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

A4/5.0
Disambiguation4/5

Most tools have distinct purposes, but some overlap exists (e.g., ask_pipeworx and ask_pipeworx_grounded, deep_research and ask_pipeworx). The Polymarket tools are numerous but clearly differentiated.

Naming Consistency3/5

Mixed naming conventions: some tools start with verbs (ask_pipeworx, search_cves), others with nouns (entity_profile, recent_changes). Prefixes (pipeworx_, polymarket_) help but the pattern is not uniform.

Tool Count2/5

33 tools is excessive for a single server, covering too many domains (NVD, Pipeworx, Polymarket, SEC, memory). This reduces coherence and makes it hard for agents to navigate.

Completeness4/5

Core workflows are covered: CVE lookup, company research, prediction market analysis, and data querying. However, there are minor gaps (e.g., no tool for editing stored data, no CVE metrics beyond search).

Resources