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Glama

Brapi

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

A4.7/5.0
Behavior5/5

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

Annotations already mark the tool read-only, idempotent, and non-destructive. The description adds valuable behavior beyond that: it returns top-N tools with names, descriptions, and full input schemas, and each result is ready to call directly—no second schema lookup. This describes the output contract not present in annotations.

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 front-loaded with the core purpose and packs useful information into two sentences: supported domains, return format, and usage priority. The long domain list is justified for a discovery tool and each clause 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?

Despite having no output schema, the description clearly states what is returned (names, descriptions, schemas, curated examples) and that results are directly callable. This fully covers the return behavior for a simple 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% with all aliases and limit documented. The description's mention of 'top-N' adds slight relevance-ranking context not fully explicit in the schema, but this is marginal; baseline 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 opens with 'Find tools by describing the data or task,' clearly identifying the verb (find) and resource (tools). It distinguishes this discovery tool from the long sibling list by framing it as the entry point for browsing available capabilities across listed domains.

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 instructs 'Use when you need to browse, search, look up, or discover what tools exist' and 'Call this FIRST when you have many tools available.' This provides clear context and differentiates from direct-answer tools.

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
Disambiguation3/5

Several tool clusters overlap: ask_pipeworx/ask_pipeworx_beta/ask_pipeworx_grounded/deep_research all route to the same source catalog, the six Polymarket tools have fuzzy boundaries between research, edge scanning, arbitrage, and fill checking, and available vs quote_list both enumerate B3 tickers. The descriptions are detailed and try to differentiate, but an agent could still easily pick the wrong meta-tool.

Naming Consistency4/5

The overwhelming majority follow lower_snake_case verb_noun naming (ask_pipeworx, resolve_entity, scan_dependency, validate_claim, list_subscriptions). Deviations like available, quote, crypto, currency, inflation, and prime_rate are bare nouns, and forget is a lone verb, but the convention remains readable and largely predictable.

Tool Count2/5

38 tools is excessive for what the server name (Brapi) suggests, and the set spans unrelated domains: Brazilian market data, a 5,798-tool universal data router, Polymarket betting analytics, memory, subscriptions, AI visibility, npm dependency scanning, and llms.txt generation. The count crosses the 25+ threshold and dilutes the server's focus.

Completeness4/5

Within each sub-domain the surface is fairly complete: brapi.dev quotes/directory/rates, Pipeworx routing/grounding/research/entity resolution/validation, prediction-market arbitrage/fill checks, memory CRUD, and subscription lifecycle all cover their core workflows. Minor gaps exist, such as no dedicated historical stock-price series beyond quote's OHLC window and deep_research requiring an account, but agents can work around them.

Resources