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L-Chris

Parallel Search MCP

by L-Chris
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JavaScript

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    parallel_search and parallel_fetch have clearly distinct purposes: one performs web searches, the other extracts content from known URLs. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    Both tool names follow a consistent parallel_<verb> pattern (search, fetch). The naming is predictable and uniform.

    Tool Count3/5

    With only 2 tools, the server feels minimal, but the tools cover the two core actions for a search/retrieval service. The count is on the low end but not unreasonable.

    Completeness4/5

    The server provides search and fetch capabilities, covering the primary workflow of searching the web and extracting content from specific URLs. Minor gaps like pagination or result filtering are not explicit, but the core surface is complete for a focused search tool.

  • Average 3.5/5 across 2 of 2 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
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

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  • This repository includes a README.md file.

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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

  • Behavior2/5

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

    Annotations already declare readOnly/openWorld/idempotent/non-destructive, so the safety profile is covered. The description adds mode selection context, but it also makes a misleading claim: 'Defaults to turbo' whereas the schema explicitly states that Chinese uses basic when mode is omitted. This inaccuracy reduces transparency and could mislead an agent, plus no other behavioral traits (rate limits, pagination) are disclosed.

    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 and extremely concise, front-loading the purpose and then providing mode guidance. Every word earns its place with no filler or redundant information.

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

    Completeness3/5

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

    Given the presence of a rich input schema, annotations, and an output schema, the description is adequate but not complete. It clearly states the tool is for web search, but it fails to clarify the language-dependent default behavior (contradicting the schema), and does not mention how this tool relates to parallel_fetch. The gaps are notable but not severe because the schema covers most operational details.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters2/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 56%, but the tool description adds minimal value beyond the schema. It mentions mode names ('turbo', 'basic', 'advanced') and a default, but these are already documented in the mode parameter. Undocumented parameters like session_id, max_results, exclude_domains, and include_domains receive no clarification from the description, so it does not compensate for the coverage gap.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly identifies the tool's purpose: 'Search the web through Parallel Search API.' This is a specific verb+resource pairing that makes the primary function obvious. It does not explicitly distinguish itself from the sibling tool parallel_fetch, but the word 'Search' versus 'fetch' implies a distinction.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines3/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides some usage context by explaining the default mode and suggesting to 'select basic or advanced when needed.' However, it gives no explicit guidance on when to use this tool versus the sibling parallel_fetch, nor does it mention any exclusions or prerequisites. The usage context is implied but not fully developed.

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

  • Behavior3/5

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

    Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, which cover the safety profile. The description adds context about the output format (Markdown excerpts/full content) and the underlying API, but does not disclose caching behavior, rate limits, or other operational details that could matter for an agent.

    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 a single sentence that is front-loaded with the verb and core purpose. Every word earns its place; there is no filler or repetition of schema details.

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

    Completeness3/5

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

    With 11 parameters and an output schema, this is a moderately complex tool. The description covers the core use case but omits important behaviors such as caching, objective-based relevance filtering, and output limits. Annotations and output schema mitigate some gaps, but the description alone is thin for such a parameter-rich tool.

    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 64%, so the schema handles most parameter explanations. The description mentions 'Markdown excerpts or full content' which loosely maps to full_content and related limits, but it does not elaborate on key parameters like objective, session_id, timeout_seconds, or disable_cache_fallback, nor compensate for the undocumented params.

    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 uses a specific verb 'Extract' with a clear resource ('Markdown excerpts or full content') and scope ('from up to 20 known URLs'). The phrase 'known URLs' clearly contrasts with the sibling tool parallel_search, which presumably searches for URLs rather than fetching from provided ones.

    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 clearly implies the tool is for fetching content from URLs the user already knows, giving contextual use case. It does not explicitly mention alternatives or when not to use it, but the 'known URLs' phrasing provides enough guidance to differentiate from search-based tools.

    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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