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bing_search

Search Bing and retrieve normalized web results, including organic listings, related queries, and people-also-ask. Returns clean JSON with pagination, locale options, and low-confidence alerts.

Instructions

Search Bing web results. Returns normalized Bing web search results for a query string, including organic results, optional context panel data, related queries, people-also-ask questions, news modules, video modules, and page-based pagination. Empty optional blocks are omitted from the JSON response. Locale defaults to country=us and lang=en-us. Results are fetched with a Chrome-impersonated request client and return 503 on a genuine transport failure or challenge page. Bing occasionally serves a well-formed page whose results share no significant term with the query; when every hedged attempt hits this, the response is still returned as 200 with data.low_confidence set to true (and the X-Low-Confidence header) instead of being withheld, so callers get Bing's real answer plus an honest signal to double-check it rather than nothing. Queries that use the site: operator (for example site:gov.hu) are not supported: Bing serves a bot-verification challenge for them, so they are rejected with 400 before any request is made. Use the Google search endpoint (/api/v1/google/search) for domain-restricted searches.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesSearch query
langNoBing UI language; defaults to en-us
pageNo1-based page number; defaults to 1
countNoResults per page; defaults to 10, clamped to 1..50
countryNoTwo-letter country code; defaults to us

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv1.6.0
  2. Removedv1.6.0
  3. First observedv1.0.0

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations present, the description carries the full burden and handles it thoroughly: it discloses Chrome impersonation, 503-on-challenge behavior, omission of empty optional blocks, locale defaults, and the low_confidence 200 fallback with its header. This is unusually honest and useful behavioral context.

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 long but every sentence earns its place: core behavior is front-loaded, followed by failure modes, low-confidence handling, and an explicit routing rule. There is no filler or redundant restatement of schema fields.

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 having no output schema, the description enumerates the returned module types, explains pagination, error codes, the low-confidence edge case, and an unsupported operator. For a search tool with quirky failure behavior, nothing critical is missing for an agent to select and invoke it correctly.

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%, so the schema already documents all five parameters and their defaults. The description adds general behavior and result structure but does not add meaningful per-parameter semantics beyond what the schema states, so the 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?

States a specific verb and resource ('Search Bing web results') and enumerates concrete outputs: organic results, context panel, related queries, people-also-ask, news, video, and pagination. This clearly separates bing_search from sibling tools like bing_images, bing_news, and bing_suggest.

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 states that site: queries are not supported and will be rejected with 400, and directly routes the agent to the Google search endpoint for domain-restricted searches. This gives a clear when-not-to-use condition and a named alternative.

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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