Skip to main content
Glama

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.0.15

  • Disambiguation5/5

    The two tools have clearly distinct purposes: deploy_folder_or_zip handles directory or zip file deployments for built frontends, while deploy_html handles direct HTML content deployments. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern starting with 'deploy_' and clearly indicate their target (folder_or_zip vs. html). The naming is uniform and predictable throughout the set.

    Tool Count2/5

    With only 2 tools, the server feels thin for a deployment service. It lacks essential operations like listing deployments, updating or deleting them, or managing projects, which limits agent workflows and creates dead ends.

    Completeness2/5

    The toolset is severely incomplete for a deployment domain. It provides create-like operations (deploy) but lacks read, update, delete, or management functions (e.g., list_deployments, get_deployment_status, delete_deployment), making it difficult for agents to handle full lifecycle tasks.

  • Average 3/5 across 2 of 2 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
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • 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.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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 a public URL, which is helpful, but doesn't describe important behavioral aspects like authentication requirements, rate limits, whether deployment is permanent or temporary, error conditions, or what happens to previous deployments. For a deployment 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.

    Conciseness5/5

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

    The description is extremely concise at just 8 words, front-loading the core purpose and outcome with zero wasted language. Every word earns its place in communicating essential 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?

    Given this is a deployment tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what 'deploy' entails operationally, what EdgeOne Pages is, whether there are size limits or content restrictions, or what format the returned URL takes. For a tool that presumably creates publicly accessible content, more context is needed.

    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 doesn't add any parameter-specific information beyond what's in the schema, maintaining the baseline score of 3 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 HTML content') and target resource ('EdgeOne Pages'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from its sibling tool 'deploy_folder_or_zip' beyond mentioning 'HTML content' versus potentially folders/ZIP files.

    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 any alternatives. It states what the tool does but offers no context about appropriate use cases, prerequisites, or exclusions.

    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 mentions the return values (deployment URL and project metadata), which is helpful, but lacks critical details: it doesn't specify whether this is a destructive operation (e.g., overwrites existing deployments), authentication requirements, rate limits, or error conditions. For a deployment tool with zero annotation coverage, this is insufficient.

    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 two sentences, front-loaded with the core purpose and followed by return values. Every word earns its place with zero waste or redundancy. It's appropriately sized for a single-parameter tool.

    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?

    Given the tool's complexity (deployment operation), lack of annotations, and no output schema, the description is minimally adequate. It covers the purpose and return values but misses behavioral context like side effects or error handling. The 100% schema coverage helps, but for a mutation tool without annotations, more completeness would be expected.

    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 the single parameter 'builtFolderPath' with its description. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't clarify format expectations like supported file types or size limits). Baseline 3 is appropriate when the 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 ('a built frontend directory (or zip file)'), and the target ('to EdgeOne Pages'). It distinguishes from the sibling '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 4 instead 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 the sibling 'deploy_html' or other alternatives. It mentions the resource type (directory/zip) but doesn't explain when this is preferred over HTML deployment or other deployment methods. No exclusions or prerequisites are stated.

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

GitHub Badge

Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

edgeone-pages-mcp MCP server

Copy to your README.md:

Score Badge

edgeone-pages-mcp MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/BACH-AI-Tools/edgeone-pages-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server