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Glama

Gtex

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

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true. Description adds valuable behavioral context: that results are 'ready to call directly' and include 'full input schemas (with curated examples).' This goes 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.

Conciseness4/5

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

The description is somewhat lengthy but front-loaded with core purpose. Every sentence adds value, though could be slightly more concise. Still well-structured for an AI agent.

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?

No output schema, but description adequately explains return format (top-N tools with names, descriptions, schemas) and that results are callable directly. This 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 description coverage is 100%, so the schema already documents all parameters. Description mentions aliases but adds little beyond the schema. Baseline 3 is appropriate as no significant extra semantics 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 clearly states the tool's purpose: 'Find tools by describing the data or task.' It specifies the output (top-N tools with names, descriptions, and schemas) and distinguishes itself from siblings by focusing on discovery rather than specific data retrieval.

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?

Provides explicit when-to-use 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.' This clarifies context and prioritization.

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

B3.3/5.0
Disambiguation2/5

ask_pipeworx and ask_pipeworx_beta are currently described as functionally identical, which is a direct ambiguity, and ai_visibility_check/scan_competitor_ai_presence plus the polymarket_* tools create several overlapping boundaries. The long descriptions help, but an agent still has to read deep into each one to avoid selecting the wrong tool.

Naming Consistency3/5

Most tools use readable lowercase snake_case verb_noun names like discover_tools, resolve_entity, and validate_claim, but the set also includes bare nouns like gene and tissues, verb-only memory tools like remember/recall/forget, and noun-phrase names like entity_profile, recent_changes, and pipeworx_trending. The style is not chaotic, but no single convention is sustained.

Tool Count2/5

36 tools exceeds the 25+ threshold and the surface is heavily padded with overlapping meta-tools, near-duplicate routers, and unrelated clusters such as Polymarket arbitrage, AI-visibility checks, and GTEx expression queries. For a server named Gtex, most of these tools are outside the apparent domain, making the count feel overgrown rather than well-scoped.

Completeness2/5

The GTEx-specific subset has only five tools and lacks obvious endpoints like multi-issue eQTLs, isoform expression, or sample-level querying, while the remaining 31 tools belong to unrelated Pipeworx, Polymarket, memory, and subscription domains. There is no coherent single purpose against which the surface can be considered complete, so agents will often hit dead ends or spend calls figuring out what the server is actually for.

Resources