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baranwang

MCP Deep Research

by baranwang
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JavaScript
Remote

Server Quality Checklist

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

  • Latest release: v1.1.0

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined as deep web information search, making it impossible for an agent to confuse it with other tools.

    Naming Consistency5/5

    A single tool inherently has perfect naming consistency, as there are no other tools to compare it against. The tool name 'deep-research' follows a clear and descriptive pattern.

    Tool Count2/5

    A single tool is too few for a server named 'MCP Deep Research', which suggests a research-focused domain that would typically require multiple tools (e.g., for searching, analyzing, summarizing, or managing research data). This minimal toolset limits functionality and scope.

    Completeness2/5

    The tool surface is severely incomplete for a deep research domain. While 'deep-research' handles search, there are obvious gaps such as tools for analyzing results, saving findings, comparing sources, or generating reports, which are essential for comprehensive research workflows.

  • Average 2.9/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

  • This repository is licensed under MIT License.

  • 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?

    The description notes multi-round capability but does not explain what multi-round entails or any behavioral details. No annotations are provided, so the description should carry the burden, but it only gives a high-level overview. No disclosure of side effects, auth requirements, or error handling.

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

    Conciseness4/5

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

    The description is a single sentence, concise and front-loaded with the main purpose. It avoids unnecessary words but could be slightly more informative without increasing length significantly.

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

    Completeness2/5

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

    The tool has 5 parameters, no output schema, and no annotations. The description only gives a high-level purpose but does not explain the return format, result structure, or how to use the tool effectively. It lacks completeness for a research tool with multi-round capability.

    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 coverage is 100%, so parameters are well-documented in the schema. The tool description mentions 'keywords and topics' but does not add new information beyond the schema. It does not explain parameter usage or constraints further.

    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 it is a deep web information search tool capable of multi-round research. It mentions keywords and topics, providing a clear purpose. However, it does not differentiate from siblings (none present) and could elaborate on the output or scope.

    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?

    No usage guidance is provided. The description does not specify when to use this tool over others, nor does it mention any prerequisites or limitations. It only describes the tool's function.

    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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  • Evaluate tool definition quality.

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