Skip to main content
Glama

search_web

Search the web and get real-time results with snippets. Set includeContent to also fetch the top result pages as markdown (+$0.0015/result). Price: $0.015

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of results (default: 10)
queryYesSearch query
contentCharsNoPer-page content character cap (default 8000)
contentResultsNoHow many top results to fetch content for (1-10, default: 5)
includeContentNoAlso fetch top result pages as markdown (+$0.0015/result)

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It adds useful context like real-time results, snippets, and the extra cost of fetching content, but it does not mention potential rate limits, timeouts, or failure modes. The standalone 'Price: $0.015' is vague, and the description omits details about content-fetching reliability, leaving gaps in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences long, front-loaded with the core purpose, and includes cost information without unnecessary fluff. Each sentence earns its place: the first defines functionality, the second explains an optional feature and its cost.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (optional content-fetching feature and costs), the description explains the primary function, the optional behavior, and pricing in a concise way. It lacks an output schema and does not detail result format, but mentioning snippets gives adequate context. The ambiguous standalone price is a minor gap, yet overall the description is sufficiently complete.

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%, meaning the schema already documents all parameters. The description only repeats the includeContent behavior (also in the schema) and adds general context instead of parameter-level details. Since the schema handles parameters, 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?

The description clearly states the tool's function: 'Search the web' and mentions 'real-time results with snippets', which is specific and distinguishes it from targeted siblings like search_news or search_images. The verb+resource combination is unambiguous and directly conveys the tool's purpose.

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 provides clear context that this tool handles general web searches with real-time snippets, and describes an optional content-fetching mode that expands its utility. However, it does not explicitly mention when to prefer this over sibling tools (e.g., search_news), nor does it state exclusions, so it falls short of full explicit guidance.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

B3.2/5.0
Disambiguation2/5

Several tool clusters have near-overlapping purposes: fetch_webpage/fetch_webpage_pro/fetch_resilient and batch_fetch/get_contents are hard to distinguish, and answer_question/research/deep_research differ mainly in price and depth. The search_* and intel_* families are clearer, but the core fetching and research overlap creates ambiguity.

Naming Consistency3/5

Most tools follow a verb_noun snake_case pattern (fetch_webpage, search_web, extract_data), but there are notable exceptions like domain_intel, package_intel, youtube_transcript, memory_set, and intel_company, where the prefix/suffix convention is inconsistent. Still, the naming is broadly readable.

Tool Count2/5

35 tools is a large surface, far beyond the typical 3-15 range. The server covers many research verticals, but the number feels bloated, especially with multiple fetch and research variants that could be consolidated.

Completeness4/5

The tool set covers a wide range of web research needs: searching, fetching, crawling, extracting, screenshots, domain/tech/package intelligence, and market/competitive analysis. It lacks obvious lifecycle operations for monitors (list/delete/update) and memory (get/delete), but core workflows are well covered.