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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

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds behavioral context by specifying that the tool returns top-N relevant tools with full input schemas and curated examples, ready to call directly. This goes beyond the annotations by detailing the return format.

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?

The description is front-loaded with the core purpose but contains a lengthy list of domains. While this list is informative, it could be slightly more concise. However, every sentence serves a purpose, and the structure is logical.

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 the tool's simplicity (single required parameter, no output schema), the description fully explains its function, expected input, return value (top-N tools with schemas), and usage context. It is complete for an agent to understand 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 3. The description adds value by providing example queries ('look up FDA drug approvals', 'analyze housing market trends') and explaining that aliases are accepted. This helps the agent understand the query parameter's usage beyond the schema's definition.

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 purpose: finding tools by describing the data or task. It provides a comprehensive list of domains (SEC filings, FDA drugs, etc.) and explicitly distinguishes from siblings by advising to 'Call this FIRST when you have many tools available and want to see the option set.'

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?

The description gives explicit usage scenarios ('Use when you need to browse, search, look up, or discover what tools exist for') and recommends calling this tool first. It lacks explicit when-not-to-use instructions but implies it's for discovery rather than direct data retrieval.

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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Glama MCP Gateway

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TDQS

A3.5/5.0
Disambiguation2/5

The server mixes Medicare-specific tools with many unrelated general-purpose tools (e.g., bet_research, polymarket_arbitrage, remember), and there are multiple similar ask_pipeworx variants. This makes it difficult for an agent to distinguish which tool is appropriate for a given task without confusion.

Naming Consistency2/5

Tool names follow no consistent pattern. Some use a medicare_ prefix with underscores, others use generic verbs like forget, recall, or compound names like ask_pipeworx, deep_research. There is no uniform verb_noun or noun_verb structure.

Tool Count2/5

57 tools is excessive for a server ostensibly focused on 'Medicare Coverage'. Many tools (e.g., bet_research, polymarket_edge_tracker, scan_dependency) are unrelated to Medicare and should be in separate servers, inflating the count and diluting focus.

Completeness4/5

The Medicare-specific tools cover a broad range: NCDs, LCDs, NCAs, enrollment, DME, Part D, hospital, outpatient, post-acute, and provider data. Minor gaps include Medicare Advantage (Part C) and Medicare Supplement, but the coverage is largely comprehensive.