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Glama

Digimon

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

A4.2/5.0
Behavior3/5

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

Annotations already provide readOnlyHint, idempotentHint, destructiveHint. Description adds confirmation of search behavior and return schema, but no new behavioral traits 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 purpose, then usage, then details. Slightly lengthy but every sentence adds value. Could be marginally tighter.

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?

Completely covers purpose, usage, and output (tools with schemas). No output schema needed; description explains what is returned. Sufficient 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 coverage 100% with detailed parameter descriptions. Description adds examples but does not compensate beyond schema. 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?

Description clearly states tool finds tools by describing data/task. Lists specific domains (SEC, FDA, etc.) and distinguishes from sibling tools which are domain-specific. Verb+resource clear.

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 'Call this FIRST when you have many tools available and want to see the option set (not just one answer).' Provides clear context and timing.

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

All Digimon toolsInspect
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TDQS

A3.9/5.0
Disambiguation2/5

Multiple tools overlap significantly: the three ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) are near-identical routers, and the six polymarket_* tools plus bet_research cover overlapping prediction-market territory. The server name 'Digimon' adds confusion since almost all tools are unrelated to Digimon, making it hard for an agent to tell what this server is actually for.

Naming Consistency3/5

All names use snake_case, which is consistent, but the pattern is mixed: some tools start with verbs (get_digimon, search_digimon, list_subscriptions, validate_claim), others with nouns (entity_profile, polymarket_arbitrage, pipeworx_trending), and a few are bare verbs (remember, recall, forget). This irregularity makes the naming less predictable than a uniformly verb-first set.

Tool Count2/5

With 33 tools, the server exceeds the 'too many' threshold and feels bloated. The tools span Digimon data, Pipeworx research, Polymarket betting, memory, subscriptions, and even llms.txt generation—an incoherent grab-bag that doesn't form a focused, well-scoped toolkit.

Completeness4/5

For the broad data-research and prediction-market domain implied by the majority of the tools, the surface is impressively comprehensive: universal routing, grounded answers, deep research, entity resolution, company/drug profiles, comparisons, claim validation, memory, subscriptions, discovery, and multiple specialized Polymarket tools. Minor gaps exist (e.g., no direct order execution on Polymarket), but ask_pipeworx routes to thousands of sources, covering most needs.

Resources