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FuzzyCZX

MCP Communication Server

by FuzzyCZX
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Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have completely distinct purposes: one performs a mathematical operation (adding numbers), while the other handles web page interaction (opening a URL and managing WebSocket data). There is no overlap or ambiguity between these functions, making tool selection straightforward for an agent.

    Naming Consistency2/5

    The naming is inconsistent: 'add' uses a simple verb without a noun, while 'open_web_page' follows a verb_noun pattern. This mixed convention lacks a predictable structure, though both names are readable. The inconsistency could cause minor confusion in a larger set.

    Tool Count2/5

    With only 2 tools, the server feels thin for a 'Communication Server' domain, which typically implies broader functionality like messaging, notifications, or data exchange. The tools cover basic math and web display but lack operations for communication workflows, making the count insufficient for the apparent scope.

    Completeness1/5

    The server is severely incomplete for a communication domain. It lacks core operations such as sending/receiving messages, managing connections, or handling events. The existing tools (add and open_web_page) do not align with communication tasks, leaving significant gaps that would cause agent failures in typical use cases.

  • Average 3.1/5 across 2 of 2 tools scored. Lowest: 2.4/5.

    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
    • No stable releases found
    • 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

  • Behavior1/5

    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. The description 'Add two numbers' reveals nothing about behavioral traits such as error handling, performance characteristics, side effects, or return format. It's a minimal statement that doesn't add any context beyond the basic operation.

    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 'Add two numbers' that directly states the purpose without any waste. It's front-loaded and appropriately sized for a simple tool, though this conciseness comes at the cost of completeness.

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

    Completeness1/5

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

    Given the tool's simplicity (2 parameters, no annotations, no output schema), the description is incomplete. It doesn't cover behavioral aspects, parameter semantics, or usage guidelines. While the operation is straightforward, the description lacks necessary context for an AI agent to understand how to invoke it effectively beyond the basic schema.

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

    Parameters1/5

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

    The schema description coverage is 0%, meaning the input schema provides no descriptions for parameters 'a' and 'b'. The description 'Add two numbers' adds no meaning beyond what the schema already implies from property names and types. It doesn't explain what 'a' and 'b' represent, their constraints, or usage examples.

    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 'Add two numbers' clearly states the tool's purpose with a specific verb ('Add') and resource ('two numbers'). It's unambiguous about what the tool does, though it doesn't explicitly distinguish from the sibling tool 'open_web_page' since they serve completely different domains (mathematics vs. web navigation).

    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 any context, prerequisites, or exclusions for usage. The sibling tool 'open_web_page' is unrelated, so no comparison is needed, but there's still no usage context provided.

    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?

    With no annotations provided, the description carries full burden and partially succeeds. It discloses that the tool opens a web page in an IDE and waits for WebSocket data, which are key behavioral traits. However, it doesn't mention potential side effects, error conditions, or what happens after timeout/WebSocket receipt.

    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 front-loads the core functionality (opening web pages) and adds the WebSocket waiting behavior. Every word earns its place with no 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 tool with 3 parameters, no annotations, and no output schema, the description provides adequate basic functionality explanation but lacks details about return values, error handling, or IDE-specific constraints. It's minimally viable but has clear gaps in behavioral context.

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

    Parameters4/5

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

    With 67% schema description coverage (2 of 3 parameters documented in schema), the description adds meaningful context by explaining that the tool '自动等待接收页面发送的WebSocket数据' which clarifies the purpose of the waitForData parameter. This compensates well for the partial schema coverage.

    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 the specific action ('在IDE中打开一个新的网页窗口显示指定的URL') and distinguishes it from the sibling tool 'add' by specifying it opens web pages in an IDE environment. It goes beyond the title by adding the WebSocket data waiting functionality.

    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 guidance is provided about when to use this tool versus alternatives. The description doesn't mention any prerequisites, constraints, or comparison with other tools that might open web pages or handle WebSocket data differently.

    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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