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Glama

Currencyformat

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. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already indicate read-only and idempotent. The description adds that results include full schemas with curated examples, and each result is ready to call directly without a second lookup. This adds useful behavioral 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?

Front-loaded with key purpose and usage. The list of domains is verbose but helpful. Overall efficient, though could be slightly more concise.

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 6 parameters, full schema coverage, no output schema, the description explains what is returned (top-N tools with names, descriptions, schemas) and usage guidance. Completely adequate for selection and invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

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 adds context about the limit parameter (top-N) and mentions multiple aliases for query. It also provides examples, adding value beyond the schema.

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 finds tools by describing data or task, listing many domains. It distinguishes from siblings like deep_research or search_within by being a general discovery tool, not a specific query tool.

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 says 'Call this FIRST when you have many tools available and want to see the option set'. Also lists scenarios like browsing, searching, looking up. Provides clear usage context.

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

A3.7/5.0
Disambiguation2/5

Multiple tool clusters have overlapping functions: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are nearly interchangeable, deep_research overlaps with the ask_pipeworx family, and the six Polymarket tools all analyze the same domain with subtle differences. discover_tools and suggest_questions also both serve as discovery entry points, making it difficult for an agent to confidently select the correct tool.

Naming Consistency3/5

All names are snake_case, but there is no uniform structural pattern. Verb_object names like format_currency and resolve_entity coexist with noun_phrases like entity_profile and polymarket_arbitrage, bare verbs like remember and forget, and adjective_noun forms like recent_alerts. Cluster-specific prefixes are consistent, but the overall convention is mixed.

Tool Count2/5

With 33 tools, the set is substantially over-scoped and exceeds the suggested 3-15 range. Many tools could be consolidated, such as the three ask_pipeworx variants, the six Polymarket tools, and the two formatting utilities. The broad domain justifies some size, but the count feels inflated and will burden agents with excessive choice.

Completeness3/5

The server covers many areas thoroughly: memory has remember/recall/forget, subscriptions have subscribe/unsubscribe/list/recent_alerts, and research tools span lookup, profiling, comparison, and verification. However, there are notable gaps: pipeworx:// citation URIs are returned but no tool explicitly fetches or reads a record by URI, and there is no direct way to manage account-level settings beyond memory. These missing operations force agents to work around limitations.

Resources