Skip to main content
Glama
ezequiel-da-silva

erickwendel-contributions-mcp

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.1.4

  • Disambiguation5/5

    Each tool targets a distinct content type (talks, posts, videos) or a health check, with no overlap in purpose. Agents can easily choose the right tool based on the resource they need.

    Naming Consistency5/5

    All tool names follow a clear verb_noun pattern: get_talks, get_posts, get_videos, and check_status. The use of 'get' for content retrieval and 'check' for status is consistent and predictable.

    Tool Count5/5

    Four tools is well-scoped for a contributions server that retrieves talks, posts, videos, and API status. Each tool earns its place without redundancy or excess.

    Completeness4/5

    The server covers the main content types (talks, posts, videos) with list retrieval and filtering, plus a health check. A minor gap is the lack of single-item retrieval, but filtering likely covers that need.

  • Average 3.6/5 across 4 of 4 tools scored.

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

    • No community issues in the last 6 months
    • 1 commit 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.

  • 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, the description carries the full burden, but it only says "Get a list of posts" and mentions filtering/pagination. It does not disclose whether the operation is read-only, requires authentication, has rate limits, or what the response structure is.

    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 concise sentence that is front-loaded with the core action and resource. It avoids redundancy and is appropriately sized for a simple list operation.

    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 6 optional parameters and no output schema, this description is minimal but functionally adequate. It lacks context on filtering semantics (e.g., exact vs partial match), ordering, or intended use cases, but the core purpose is clear.

    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 baseline is 3. The description echoes the schema by mentioning "optional filtering" but adds no new detail about parameter values, defaults already in the schema, or filtering behavior.

    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 tool gets a list of posts, using a specific verb ("Get") and resource ("posts"), and distinguishes it from siblings like get_talks and get_videos by the resource type.

    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 on when to use this tool versus alternatives. It does not mention that get_talks or get_videos should be used for other content types, or any conditional context for choosing this tool.

    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?

    No annotations are provided, so the description carries the burden. It mentions optional filtering and pagination, adding some behavioral context. However, it doesn't disclose details like whether count_only changes the response shape, how group_by interacts with filters, or any rate limits. It's acceptable but not rich.

    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 concise sentence that captures the core functionality without waste. It is front-loaded with the main purpose and includes key capabilities (filtering, pagination) in an efficient way.

    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 has 10 parameters, no output schema, and no annotations, the description is minimal. It covers the basic purpose and mentions pagination/filtering, but it does not explain return values, edge cases, or how parameters combine. The schema descriptions help, but the overall context is not fully complete for a complex tool.

    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%, meaning every parameter has a description in the schema. The tool description itself lists no parameter details, but since the schema already documents all ten parameters, the description does not need to repeat them. The baseline of 3 is appropriate because 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 states the tool lists talks with optional filtering and pagination, which is clear and specific. It does not explicitly distinguish it from sibling tools like get_posts or get_videos, but the resource 'talks' is unique enough that it's not misleading. The verb 'get a list' is clear.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines3/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description implies this is for retrieving talk data, but it does not provide explicit when-to-use guidance or contrast with alternatives. Sibling tools are present, but no exclusions or preferred scenarios are given, so usage context is only implied.

    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?

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It conveys that the tool is read-only and supports filtering and pagination, but it does not disclose return format, default values, ordering, or other behaviors. This is acceptable for a simple list tool but leaves room for ambiguity.

    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 sentence that is concise, front-loaded with the core purpose, and contains no filler or redundant information. Every word earns its place.

    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?

    With five parameters and no output schema, the description is simplistic. It covers the basic functionality but omits return structure and parameter behaviors (e.g., exact vs. partial matching, default pagination values). For a straightforward list tool, this is adequate but not complete, especially given the lack of annotations or output schema.

    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%, with each parameter (id, skip, limit, title, language) described in the schema. The description adds a high-level mention of 'optional filtering and pagination' but no additional detail beyond the schema, so the baseline 3 applies.

    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 tool lists videos, using the verb 'Get' with the resource 'videos', and mentions optional filtering and pagination. It is specific enough to distinguish from sibling tools by resource name, though it does not explicitly differentiate itself from get_talks or get_posts beyond that.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines3/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description implies when to use this tool: when listing videos with optional filters or pagination. However, it provides no explicit guidance on when not to use it or mention of alternatives like get_talks or get_posts, leaving usage context implied rather than explicit.

    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?

    No annotations are provided, so the description carries the full burden. It states the tool performs a liveness check, implying a read-only operation, but it does not disclose what response to expect, error behavior, or whether any side effects occur. This is adequate for a zero-parameter tool but lacks depth.

    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 sentence, perfectly concise and front-loaded. It conveys the tool's purpose without any extraneous information or repetition of the tool name.

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

    Completeness4/5

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

    Given the tool's simplicity (zero parameters, no output schema, no annotations), the description adequately conveys the core purpose. It could be improved by mentioning the expected return value or how to interpret 'responding,' but for a basic health check, the description is sufficiently complete.

    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?

    The tool has zero parameters, so the input schema fully covers any parameter semantics. The description adds no parameter details because none are necessary. Per the rubric, 0 parameters warrants a baseline score of 4.

    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 uses a specific verb 'check' and clearly identifies the resource ('the API'), making the tool's purpose unambiguous. It is distinctly different from sibling tools like get_talks, get_posts, and get_videos, which retrieve content rather than verify API health.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines3/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description implies usage: if you need to verify the API is alive, use this tool. However, there is no explicit guidance on when to use it versus alternatives, nor any mention of prerequisites or exclusions. The context of sibling get_* tools suggests a read-only health check, but this is not 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

erickwendel-contributions-mcp MCP server

Copy to your README.md:

Score Badge

erickwendel-contributions-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/ezequiel-da-silva/erickwendel-contributions-mcp'

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