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chatmcp

mcp-server-collector

by chatmcp
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

50%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose with no overlap: extracting servers from content, extracting from a URL, and submitting to a directory. The descriptions make it unambiguous which tool to use for each scenario, preventing misselection.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with hyphens (e.g., extract-mcp-servers-from-content, extract-mcp-servers-from-url, submit-mcp-server). This predictable naming scheme enhances readability and usability for agents.

    Tool Count5/5

    With 3 tools, the server is well-scoped for its purpose of collecting and submitting MCP servers. Each tool earns its place by covering distinct aspects of the workflow, avoiding bloat or thinness.

    Completeness4/5

    The tool set covers the core workflow of extraction (from content and URLs) and submission, with no obvious dead ends. A minor gap might be the lack of tools for managing or listing already submitted servers, but agents can work around this with the existing tools.

  • Average 2.8/5 across 3 of 3 tools scored.

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

    • 0 of 1 issues responded to in the last 6 months
    • No commit activity data available
    • 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?

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states what the tool does ('extract MCP servers') without explaining how it behaves: e.g., what format the extraction outputs, whether it's read-only or has side effects, error handling, or performance considerations. This is inadequate for a tool with no annotation coverage, as it leaves critical behavioral traits unspecified.

    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 extremely concise with a single sentence: 'Extract MCP Servers from given content'. It is front-loaded and wastes no words, making it easy to parse. Every part of the sentence earns its place by stating the action and target, though it could benefit from more detail for clarity.

    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?

    Given the complexity of extraction tasks, lack of annotations, and no output schema, the description is incomplete. It doesn't explain what 'extract' entails (e.g., parsing, formatting, or validation), what the output looks like, or how it differs from sibling tools. For a tool with no structured support beyond the input schema, this leaves significant gaps in understanding its full context and usage.

    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?

    The description adds no meaning beyond what the input schema provides. The schema has 100% coverage with one parameter 'content' described as 'content containing mcp servers', which the description implicitly references but doesn't elaborate on. With high schema coverage, the baseline is 3, as the schema already documents the parameter adequately, and the description doesn't compensate with additional context like examples or constraints.

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

    Purpose3/5

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

    The description states the tool's purpose as extracting MCP servers from content, which is clear but vague. It specifies the verb 'extract' and resource 'MCP servers', but doesn't differentiate from sibling tools like 'extract-mcp-servers-from-url' or 'submit-mcp-server' beyond the input source. The purpose is understandable but lacks specificity about what constitutes 'extraction' versus other operations.

    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. It doesn't mention when to prefer this tool over 'extract-mcp-servers-from-url' (e.g., for direct content vs. URL fetching) or 'submit-mcp-server' (e.g., for extraction vs. submission). There's no context on prerequisites, exclusions, or typical use cases, leaving the agent to infer usage from the tool name alone.

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

  • Behavior2/5

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

    No annotations are provided, so the description carries full burden. It states what the tool does but lacks behavioral details: no information on permissions needed, rate limits, error handling, output format, or whether it's read-only/destructive. 'Extract' suggests read-only, but this isn't explicitly confirmed.

    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, efficient sentence with zero waste. It's appropriately sized for a simple tool and front-loaded with the core action, making it easy to parse quickly.

    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?

    Given no annotations, 0% schema coverage, and no output schema, the description is incomplete. It lacks details on behavior, parameters, and return values, which are essential for a tool with one parameter and potential complexity in URL processing and MCP server extraction.

    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 0% with 1 parameter ('url'), and the description doesn't add any parameter semantics beyond the name. It doesn't explain what type of URL is expected (e.g., HTTP, file path), format constraints, or examples, leaving the parameter meaning unclear.

    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 'Extract MCP Servers from a URL' clearly states the verb ('extract'), resource ('MCP Servers'), and source ('from a URL'). It distinguishes from sibling 'extract-mcp-servers-from-content' by specifying URL vs. content, but doesn't differentiate from 'submit-mcp-server' which has a different action.

    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 explicit guidance on when to use this tool vs. alternatives. The description implies usage for URL-based extraction, but doesn't specify scenarios, prerequisites, or exclusions compared to siblings like 'submit-mcp-server' for submission operations.

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

  • Behavior2/5

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

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool submits to a directory 'like mcp.so', implying a public listing or registration, but doesn't clarify permissions required, rate limits, whether the submission is reversible, or what happens on success/failure. This is inadequate for a tool that likely involves external API calls.

    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, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy to parse quickly.

    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?

    Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns, error conditions, or behavioral details like authentication needs. For a submission tool with external dependencies, this leaves significant gaps in understanding how to use it effectively.

    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 both parameters ('url' and 'avatar_url') with clear descriptions. The description adds no additional meaning about parameters beyond what the schema provides, such as format examples or constraints, meeting the baseline for high schema coverage.

    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 action ('Submit') and resource ('MCP Server to MCP Servers Directory like mcp.so'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'extract-mcp-servers-from-content' or 'extract-mcp-servers-from-url', which appear to be extraction tools rather than submission tools.

    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. It doesn't mention prerequisites, context for submission, or how it differs from sibling tools, leaving the agent to infer usage based on tool names alone.

    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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