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Server Quality Checklist

92%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of confusing it with another operation. The tool's purpose is clearly stated as fetching Bing search results.

    Naming Consistency4/5

    The single tool name follows a readable provider-prefix plus action pattern, but it mixes snake_case segments with camelCase. Since there is only one tool, the inconsistency is minor and does not create practical confusion.

    Tool Count3/5

    One tool is at the thin end of the spectrum. It is acceptable for a narrowly scoped Bing SERP endpoint, but a server named 'Bing MCP Server' feels minimal with only a single operation.

    Completeness4/5

    The tool covers core Bing web search well with geo, language, safe search, and pagination options. However, it lacks separate tools for news, image, video, or other Bing verticals, leaving some broader search use cases uncovered.

  • Average 4.2/5 across 1 of 1 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 2 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

  • This repository includes a glama.json configuration file.

  • This server has been verified by its author.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior4/5

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

    With no annotations provided, the description carries the burden of explaining behavior. It discloses what the tool returns: organic results with title, URL, snippet, displayed URL, position, related searches, answer boxes/knowledge panels, and pagination metadata. It does not mention rate limits, authentication, or error behavior, but for a read-only search fetch the disclosed behavior is reasonably complete.

    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 compact and front-loaded, starting with the tool's core purpose and then covering capabilities, return values, and use cases without redundancy. Every sentence adds value, and the structure is easy for an agent to parse quickly.

    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?

    For a tool with 11 parameters and no output schema, the description does well by summarizing return fields and listing all major parameter groups. It does not detail exact response structures or edge cases, but the combination of full schema coverage and the return-value overview gives an agent enough context to select and invoke the tool 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 every parameter individually. The description adds grouping context (e.g., 'geo targeting (location/lat/lon), market (mkt), country (cc)') but does not introduce semantic detail beyond the schema. 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 'Fetches Bing SERPs for a query' with a specific verb and resource, and enumerates the key capabilities like geo targeting, market, safesearch, and pagination. It also names concrete use cases (SEO rank tracking, Bing-specific visibility audits), making it easy to distinguish from the many sibling search tools for Google, DuckDuckGo, and other engines.

    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 clear application contexts: 'Use for SEO rank tracking, SERP feature monitoring, Bing-specific visibility audits, and training/eval data for search agents.' This implies when to choose Bing SERP over alternatives, though it does not explicitly name sibling tools or state when not to use it.

    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 performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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Bing MCP Server MCP server – quality and maintenance score on Glama

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