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Glama

Google_search_console

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
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds useful behavioral context: returns 'top-N most relevant tools with names, descriptions, and full input schemas (with curated examples)' and states 'each result is ready to call directly, no second schema lookup needed.' This goes 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?

The description is a single paragraph but packs purpose, domain list, output format, and usage guidance efficiently. It is front-loaded with the core action. However, it could benefit from clearer structure (e.g., bullet points) for quick scanning, losing one point.

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 no output schema, the description fully explains the output (list of tools with schemas). It covers purpose, when to use, examples, and readiness to call. For a tool with 6 parameters (many aliases), the description provides sufficient context for proper use.

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 parameters documented. The description mentions 'top-N' implying 'limit' but does not add new semantic meaning beyond the schema's field descriptions. Without additional clarification, the score is baseline 3.

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 starts with 'Find tools by describing the data or task' and lists specific domains (SEC filings, FDA drugs, etc.). It clearly identifies the tool as a meta-discovery tool that returns ready-to-call tools, differentiating it from sibling tools by advising '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 states when to use: 'Use when you need to browse, search, look up, or discover what tools exist for:' with examples. It also advises using it first for exploring options. However, it does not explicitly name sibling tools as alternatives or state when not to use it, which would strengthen guidelines.

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

A3.8/5.0
Disambiguation3/5

Most tools have distinct purposes within their own clusters, and the GSC tools are clearly separated. However, ask_pipeworx_beta is explicitly identical to ask_pipeworx right now, and the several Polymarket tools (arbitrage, edges, fill_risk, kalshi_spread) can be confused without reading each description closely.

Naming Consistency3/5

Names are broadly snake_case and readable, with some useful prefixes (gsc_, polymarket_, pipeworx_). But conventions are mixed: some are verb_noun (list_subscriptions, resolve_entity), some are noun_compound (bet_research, entity_profile), and some are bare verbs (forget, recall), which prevents a predictable pattern.

Tool Count2/5

35 tools is heavy for any single server, but it is especially problematic given the server is named Google_search_console while only 4 of the 35 tools actually relate to Search Console. The rest form a sprawling Pipeworx/Polymarket research toolkit that would be far more coherent as its own server.

Completeness2/5

Relative to the stated Google Search Console purpose, the set is missing common operations such as submitting/removing sitemaps, requesting indexing, or managing URL inspections. The unrelated Pipeworx tools are extensive in their own domains but do not fill these gaps, leaving the GSC surface incomplete.