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Glama

Nass

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 mark the tool as readOnly, idempotent, and non-destructive. The description adds value by stating it returns 'top-N most relevant tools with names, descriptions, and full input schemas (with curated examples)' and that results are 'ready to call directly, no second schema lookup needed.' This clarifies the output behavior beyond what annotations provide.

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 efficient and front-loaded. The first sentence states the core purpose, followed by a list of domains, then details on returns and usage guidance. Every sentence serves a purpose with no fluff.

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 complexity (many sibling tools, no output schema), the description fully covers what the tool does, when to use it, what it returns, and how results can be used. It leaves no major gaps for an 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%, so baseline is 3. The description mentions that query accepts aliases (task, q, description, search), but this is already documented in the schema's query description. No additional semantic details beyond the schema are provided.

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 explicitly states 'Find tools by describing the data or task.' It includes a broad list of domains and clearly distinguishes this as a discovery tool for browsing available tools, differentiating it from sibling tools like entity_profile or deep_research.

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 advises: 'Call this FIRST when you have many tools available and want to see the option set (not just one answer).' This provides clear when-to-use guidance and implicitly suggests not using it when a single answer is needed.

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 clearly distinct purposes, especially the specialized ones like nass_crop_progress and bet_research. However, there is potential confusion between ask_pipeworx, ask_pipeworx_grounded, deep_research, and bet_research, as they all involve querying structured data. The descriptions do attempt to differentiate them, but the overlap could still cause misselection.

Naming Consistency4/5

Tool names consistently use lowercase with underscores and follow patterns like descriptive prefixes (nass_, pipeworx_, polymarket_) and action verbs (generate_, resolve_, validate_). Minor inconsistencies exist, such as 'search_within' versus 'discover_tools', but overall the naming is predictable and clear.

Tool Count3/5

With 36 tools, the server is on the heavier side but still fits within a reasonable range for a comprehensive data platform. The tools cover a wide variety of domains (agriculture, finance, prediction markets, memory, etc.), and each tool appears to add value. However, the count is borderline high, and some tools like ask_pipeworx could potentially replace many specialized ones.

Completeness4/5

The tool surface is comprehensive for its purpose: answering questions over structured data with support for analysis, comparison, monitoring, and feedback. There are minor gaps, such as the lack of a direct update mechanism for subscriptions beyond canceling, but the core CRUD operations are covered. The inclusion of meta-tools like ask_pipeworx and deep_research fills many potential gaps.

Resources