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TencentEdgeOne

EdgeOne Pages MCP

Official
by TencentEdgeOne
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TypeScript
Remote

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one deploys a folder or zip file for a built frontend, while the other deploys raw HTML content. There is no overlap or ambiguity between them, making it easy for an agent to select the correct tool based on the input type.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern with 'deploy' as the verb, and the nouns ('folder_or_zip', 'html') clearly indicate the target. The naming is uniform and predictable across the set.

    Tool Count2/5

    With only 2 tools, the server feels thin for a deployment service. While the tools cover basic deployment scenarios, typical MCP servers for such domains (like GitHub or cloud services) offer more operations (e.g., list deployments, update, delete, monitor status), suggesting this set is under-scoped and may leave gaps in agent workflows.

    Completeness2/5

    The server lacks essential operations for a deployment domain, such as listing existing deployments, updating or deleting them, checking status, or managing projects. This creates significant gaps that could cause agent failures when trying to perform full lifecycle management, as agents cannot retrieve or modify past deployments.

  • Average 2.9/5 across 2 of 2 tools scored.

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

    • 0 of 3 community issues answered or closed 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

  • 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 states this is a deployment operation (implying a write/mutation) and mentions return values, but doesn't cover critical aspects like authentication requirements, rate limits, error conditions, whether deployment is reversible, or what happens to existing deployments. For a mutation tool with zero annotation coverage, this leaves significant gaps.

    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 appropriately concise with two sentences: one stating the action and one stating the return values. It's front-loaded with the core purpose. While efficient, it could be slightly more structured by separating usage guidance from return information.

    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?

    For a deployment/mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'deploy' entails operationally, what permissions are needed, how deployments are managed, or what the return metadata includes. The mention of return values is helpful but insufficient given the tool's complexity and lack of structured documentation.

    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 fully documents the single parameter. The description adds marginal value by reinforcing that it accepts 'built frontend folder (or zip file)' but doesn't provide additional syntax, format details, or constraints beyond what's in the schema. Baseline 3 is appropriate when schema does the heavy lifting.

    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 ('Deploy'), the resource ('built frontend directory (or zip file)'), and the target ('EdgeOne Pages'). It distinguishes from the sibling tool 'deploy_html' by specifying it handles directories/zip files rather than HTML content. However, it doesn't explicitly contrast with the sibling, keeping it at a 4 rather than a 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 like 'deploy_html'. It mentions the return values but doesn't explain prerequisites, constraints, or appropriate contexts for deployment. There's no explicit when/when-not usage advice.

    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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool deploys HTML content and returns a public URL, but does not cover critical aspects like authentication requirements, rate limits, whether the deployment is permanent or temporary, error handling, or what happens to previous deployments. This leaves significant gaps in understanding the tool's behavior.

    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 key action and outcome without any wasted words. It is appropriately sized for a tool with one parameter and clear functionality, making it easy for an agent 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 for a deployment tool. It does not explain the return value format beyond 'public URL', nor does it address potential errors, side effects, or integration details. For a tool that modifies external resources, more context is needed to ensure safe and correct 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 input schema has 100% description coverage, with the parameter 'value' clearly documented as 'full HTML markup' for publishing. The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline of 3 for adequate but not enhanced 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 ('Deploy HTML content') and target resource ('to EdgeOne Pages'), with a specific outcome ('return the public URL'). It distinguishes from the sibling tool 'deploy_folder_or_zip' by specifying HTML content deployment rather than folder/zip deployment, though it could be more explicit about the distinction.

    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 the sibling 'deploy_folder_or_zip' or other alternatives. It mentions the outcome but lacks context about prerequisites, limitations, or typical use cases, leaving the agent without explicit usage instructions.

    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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