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niklaserik

effect-mcp

by niklaserik
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.7

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one fetches and returns the actual documentation content, while the other returns resource links for the client to load. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    Both tools follow the same 'effect-[noun]' naming pattern with descriptive, hyphenated names. The convention is consistent and predictable.

    Tool Count3/5

    With only two tools, the server feels thin and borderline for a documentation-focused MCP. The tools are useful, but the count is at the low end of what is considered appropriate.

    Completeness4/5

    The server covers the two primary operations for documentation access: fetching content and obtaining links. However, it lacks discovery tools (e.g., listing available libraries) which represents a minor gap depending on the client's needs.

  • Average 3.5/5 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 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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    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

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How to sync the server with GitHub?

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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 full responsibility for behavioral disclosure. It states that docs are fetched and concatenated, but omits important traits such as whether authentication is needed, any rate limits, output size or format, and whether the operation is read-only. The minimal behavior described is too shallow for an external-fetching tool.

    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 efficiently conveys the core purpose. There is no unnecessary detail, redundancy, or fluff. It is concise and front-loaded with the most important action.

    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?

    The tool has a simple one-parameter schema, but there is no output schema and no annotations. The description does not explain what the concatenated output looks like, which could be critical for agents expecting to parse docs. It also does not clarify the relationship with the sibling tool. Given the overall simplicity, the description is minimally adequate but leaves gaps.

    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% coverage for its single parameter 'libraries' with a clear description and examples. The tool description adds context that the libraries refer to Effect libraries but does not add any additional parameter meaning beyond what the schema already provides. Therefore a baseline score of 3 is appropriate.

    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's verb ('Fetches and concatenates') and resource ('latest docs for the specified Effect libraries'). It includes a specific scope ('Effect libraries') and differentiates from the sibling 'effect-doc-links' by emphasizing concatenation of documents rather than just providing links.

    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 vs. the sibling 'effect-doc-links' or any alternative. The description does not mention prerequisites, intended scenarios, or exclusions. Usage must be inferred entirely from the tool's name and description.

    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 the full burden. It conveys that it is a read-only operation returning links, but does not disclose details like return format, potential side effects, or limitations. The description adds some context about client-side selective loading, 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, front-loaded sentence with no redundant wording. It efficiently communicates the tool's purpose.

    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?

    The description covers the essential behavior of returning links, which is sufficient for a simple query tool with one parameter. However, it does not detail the return structure or explicitly address the sibling tool, leaving minor gaps in completeness.

    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 fully describes the 'libraries' parameter with examples, giving 100% coverage. The description adds no additional meaning about parameters, so it remains at the baseline for schema-covered parameters.

    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 returns resource links for specified libraries, with a specific verb and resource. However, it does not explicitly distinguish itself from the sibling tool 'effect-documentation', which would merit 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 Guidelines3/5

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

    The phrase 'so the client can load only what's needed' implies a use case for selective loading, but there is no explicit guidance on when to use this tool instead of the sibling. No alternatives or exclusions are mentioned.

    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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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.

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