Skip to main content
Glama

translate

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

A4.1/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds valuable behavioral context by disclosing the return format (top-N tools with names, descriptions, full input schemas, curated examples) and that results are directly callable without a second lookup. 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?

Purpose is front-loaded in the first sentence. The domain list is lengthy but directly supports usage guidance, and the output format is explained in a single, information-dense sentence. Slightly verbose but effectively structured, and every part earns its place.

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 covers purpose, usage conditions, return format, and actionable guidance. It also explains what results look like in the absence of an output schema. Combined with a thorough input schema and safety annotations, it is sufficiently complete for a discovery tool. Missing only edge-case details like ranking methodology, which are not essential.

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%, with all parameters and aliases thoroughly documented. The description does not add significant meaning beyond the schema's parameter descriptions; it only reiterates that query is a natural language description. Baseline 3 is appropriate because the schema carries the parameter burden.

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 function: 'Find tools by describing the data or task.' It lists supported domains and explicitly positions itself as a tool-discovery meta-tool, distinguishing it from sibling tools that perform specific tasks. The instruction to 'Call this FIRST' further reinforces its unique role.

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

Usage Guidelines4/5

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

Provides clear when-to-use guidance: browse, search, look up, or discover tools, and 'Call this FIRST when you have many tools available'. It also hints at a when-not-to-use condition ('not just one answer'), but does not explicitly name alternative tools or exclusions, preventing a top score.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All translate toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0
Disambiguation2/5

Several groups of tools are hard to tell apart in practice: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and bet_research all route natural-language questions to similar data sources, and the polymarket_* family plus bet_research heavily overlaps. Individual descriptions are detailed, but an agent navigating this surface will frequently struggle to choose the correct entry point.

Naming Consistency3/5

The naming is readable and mostly snake_case, but conventions are mixed: some tools are verb+noun commands (resolve_entity, validate_claim), some are noun phrases (entity_profile, bet_research), and others use product prefixes inconsistently (ask_pipeworx vs pipeworx_feedback vs polymarket_edges). The polymarket_* cluster is consistent, but no clear pattern holds across the whole server.

Tool Count2/5

34 tools is past the 25-tool threshold and is especially excessive for a server named 'translate', where only three tools relate to translation. Most of the surface belongs to a broad Pipeworx data/analytics/prediction-market platform that would be better split into separate focused servers.

Completeness3/5

The Pipeworx-related workflows are fairly well-covered: lookup, grounded research, company profiling, prediction-market analysis, subscriptions, and memory all have usable tool clusters. However, the translation domain implied by the server name is thin and references a deepl_translate tool that is not actually exposed, so there is no single domain that feels fully complete.

Resources