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spences10

MCP JinaAI Search Server

by spences10
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JavaScript
Remote

Server Quality Checklist

67%
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 ambiguity or overlap between tools. The tool 'search' has a clear and singular purpose, making it impossible for an agent to misselect among non-existent alternatives.

    Naming Consistency5/5

    A single tool inherently has perfect naming consistency, as there are no other tools to compare against. The name 'search' follows a simple verb pattern, which is appropriate and unambiguous for its function.

    Tool Count2/5

    A single tool is too few for a server named 'MCP JinaAI Search Server', which suggests a broader search functionality scope. While the tool covers basic web search, the server lacks additional tools for advanced operations like filtering, pagination, or domain-specific searches, making it feel thin and under-scoped.

    Completeness2/5

    The server is severely incomplete for a search domain. It only offers a basic search tool without any supporting operations such as refining queries, handling multiple result pages, or accessing search history. This creates significant gaps that could lead to agent failures when more complex search tasks are required.

  • Average 3.1/5 across 1 of 1 tools scored.

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

  • This repository is archived. Archived repositories automatically receive an F maintenance tier.

  • 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.

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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?

    With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the tool returns 'clean, LLM-friendly content' and 'top 5 results with URLs and clean content,' which gives some behavioral context. However, it lacks critical information about rate limits, authentication requirements, error conditions, or what constitutes 'clean' content, leaving significant gaps for a tool with 12 parameters.

    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 perfectly concise and front-loaded: a single sentence that communicates the core functionality, method, and output format. Every word earns its place with zero redundancy or unnecessary elaboration.

    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?

    For a search tool with 12 parameters and no output schema, the description provides basic purpose and output format but lacks sufficient behavioral context. Without annotations covering safety, limits, or authentication, and with no output schema to explain return values, the description should do more to compensate for these gaps, especially given the tool's complexity.

    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 fully documents all 12 parameters. The description doesn't add any parameter-specific information beyond what's already in the schema descriptions. According to guidelines, when schema coverage is high (>80%), the baseline score is 3 even with no parameter information in the description.

    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 states the tool's purpose: 'Search the web and get clean, LLM-friendly content using Jina.ai Reader.' It specifies the action (search), resource (web content), and processing method (Jina.ai Reader). However, without sibling tools, it cannot demonstrate differentiation from alternatives, preventing a score of 5.

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

    Usage Guidelines2/5

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

    The description provides no guidance on when to use this tool versus alternatives, prerequisites, or contextual constraints. It mentions returning 'top 5 results' but doesn't explain when this limitation is appropriate or when other search tools might be better suited.

    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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