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Glama

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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so no safety surprises. The description adds useful context: returns top-N tools with full schemas and curated examples ready for direct invocation, and lists covered domains. It does not contradict 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?

Concise and well-structured: front-loaded purpose, then usage, then return details, then strategic guidance. The domain list is long but purposeful. No fluff or redundancy with the schema.

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?

No output schema exists, but the description fully explains the return value: top-N tools with names, descriptions, full input schemas, and curated examples, ready to call directly. It also provides critical usage strategy with 'Call this FIRST' and a domain scope, making it complete for an agent to decide when and how to use it.

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 a list of searchable domains (SEC filings, FDA drugs, BLS jobs, etc.) and example query forms, helping agents understand how to formulate the `query` parameter. This goes beyond the schema's generic 'natural language description'.

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 'Find tools by describing the data or task' with a specific verb and resource. It differentiates itself from siblings by framing itself as a discovery/meta-tool, explicitly listing covered domains and positioning itself as the first step when many tools are available.

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 'Use when you need to browse, search, look up, or discover what tools exist' and 'Call this FIRST when you have many tools available and want to see the option set (not just one answer).' This gives clear contexts for use and subtly distinguishes 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

B3.4/5.0
Disambiguation2/5

Multiple tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all answer data questions, while discover_tools and suggest_questions both serve discovery. The three ArcGIS tools are distinct but are drowned out by the unrelated Pipeworx and prediction-market tools, making it hard to pick the right one.

Naming Consistency3/5

Tool names are mostly snake_case but mix verb_noun (query_layer, search_datasets, remember), noun_noun (layer_info, entity_profile), and less conventional forms (search_within, generate_llms_txt). The naming is readable and not chaotic, but there is no single consistent pattern across the set.

Tool Count1/5

34 tools is excessive for a server named 'Arcgis Palmbeach'. Only 3 tools are GIS-related (search_datasets, query_layer, layer_info); the other 31 are unrelated Pipeworx data, prediction-market, and memory utilities. The count grossly mismatches the server's apparent purpose.

Completeness1/5

For the stated ArcGIS/Palm Beach County GIS purpose, the tool surface is severely incomplete: only search, query, and layer-schema lookup exist, with no data editing, feature operations, or map-service management. While the Pipeworx domain is heavily covered, that is not what the server name promises, so the surface is a poor fit.