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HappyMonkeyAI

devto-mcp-server

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.0

  • Disambiguation2/5

    Tools `search_devto_posts` and `search_by_tech` both search articles with overlapping functionality (tag filtering, top results), causing ambiguity. An agent may struggle to choose the appropriate one.

    Naming Consistency4/5

    Most tools follow a `verb_noun` pattern (`search_devto_posts`, `get_devto_article`, etc.), but `search_by_tech` breaks the pattern with a preposition, and inconsistent pluralization (`posts` vs `article`).

    Tool Count5/5

    With 5 tools covering search, retrieval, creation, and update, the count is well-scoped for a dev.to article management server, neither too sparse nor too heavy.

    Completeness4/5

    Basic CRUD operations are present except deletion, and search covers multiple query patterns. Minor gap in missing delete or listing all user articles, but core workflows are covered.

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

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

    • No community issues in the last 6 months
    • 5 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.

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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

  • Behavior3/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations provided, so description must cover behavioral traits. It discloses partial update semantics and authentication but does not mention error handling, rate limits, or side effects. Adequate but not comprehensive.

    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?

    Two sentences front-load the key purpose and behavior. No superfluous words, but could benefit from additional structure if more detail were needed.

    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?

    Output schema exists (though not shown), so return values don't need description. However, given the large number of parameters (11) and 0% schema coverage, the description is insufficient to fully guide parameter usage. It covers the basic flow but lacks completeness.

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

    Parameters2/5

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

    Schema description coverage is 0%, so description should compensate for 11 parameters. It only mentions that non-null fields are sent, without explaining any individual parameter's meaning or constraints. Most parameter semantics remain undocumented.

    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 verb (update) and resource (existing dev.to article) with a specific identifier (numeric article id). It distinguishes from siblings like create_devto_article (which creates) and get_devto_article (which retrieves).

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

    Usage Guidelines4/5

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

    The description explains partial update behavior ('Only fields provided as non-null arguments are sent') and authentication method ('Pass api_key or set DEVTO_API_KEY'). It lacks explicit when-not-to-use guidance but provides enough context for appropriate invocation.

    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?

    No annotations provided; description only mentions it returns a list of articles but omits whether the tool is read-only, requires authentication, or any side effects.

    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?

    Description is concise (5 lines), well-structured with clear argument descriptions, and no superfluous text.

    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?

    Explains purpose, parameters, and return value, but lacks explicit differentiation from siblings and does not cover error cases or edge effects. Output schema exists but is not detailed.

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

    Parameters5/5

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

    With 0% schema description coverage, the description adds significant meaning: explains tech with examples, per_page as result count, and top_days with conditional behavior (None triggers text search).

    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 searches articles by technology/tag and identifies itself as a convenience wrapper, distinguishing it from sibling tools like search_devto_posts.

    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?

    Provides parameter-level guidance (e.g., top_days behavior) but does not explicitly state when to use this tool over sibling search_devto_posts or when not to use it.

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

  • Behavior4/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations, description carries full burden. It discloses that query searches multiple fields, tag filters, and top changes behavior to return top articles. Missing details on authentication or rate limits, but acceptable for a search tool.

    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?

    Well-structured with Args and Returns sections, but slightly verbose. Could be more concise while retaining clarity.

    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?

    Covers all 5 parameters with clear explanations and mentions return type. Output schema is indicated. No major gaps for a search tool.

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

    Parameters5/5

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

    Schema has 0% description coverage, but description explains each parameter's purpose (query searches title/body/tags, tag optional filter, per_page max 30, page pagination, top switches mode). Adds significant meaning beyond property names.

    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?

    Clearly states 'Search dev.to articles' with a list of arguments and return type. Distinguishes from sibling tools like get_devto_article but does not explicitly mention alternatives (e.g., search_by_tech).

    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?

    Implied usage through description of arguments, but lacks explicit guidance on when to use this vs. alternatives. No when-not or context for choosing over search_by_tech.

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

  • Behavior4/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations are provided, so the description carries full burden. It discloses the return object's contents (body_markdown, tags, reactions) and implies read-only behavior. There is no contradictory information.

    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 two short paragraphs: one for purpose and parameter, one for return value. It front-loads the key action and contains zero superfluous text.

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

    Completeness5/5

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

    For a simple retrieval tool with one parameter and an existing output schema, the description provides all necessary context. It explains what the tool does, what input is needed, and what the output contains.

    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?

    Schema description coverage is 0%, but the description adds meaning by explaining that article_id is 'the numeric ID of the article.' This compensates for the missing schema descriptions and clarifies the parameter's purpose.

    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 action ('Retrieve a full dev.to article') and the identifier ('by its ID'). This distinguishes it from sibling tools like search_devto_posts (which searches) and create/update (write operations).

    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 when you have the article_id, but lacks explicit guidance on when not to use or when to prefer alternatives like search_devto_posts. The context is clear but not exclusionary.

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

  • Behavior4/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    Without annotations, the description discloses creation of draft vs published, authentication method, and default safety. Does not mention rate limits or idempotency but covers major behavioral traits.

    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?

    Well-structured with a lead sentence, parameter list, and return description. Each sentence adds value, though slightly verbose for the number of parameters.

    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 10 parameters and an output schema, the description covers all inputs, behavior, and return. Missing error handling details but adequate for standard usage.

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

    Parameters5/5

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

    Despite 0% schema description coverage, the tool description explains every parameter (title, body_markdown, published, tags, etc.) with sufficient detail, adding meaning beyond the bare schema.

    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 states 'Create a dev.to article or draft using the authenticated DEV API.' This clearly identifies the verb (create), resource (article/draft), and distinguishes from sibling tools (search, get, update).

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

    Usage Guidelines4/5

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

    Provides clear context: 'using the authenticated DEV API,' default published=false for safety, and fallback to environment variable for API key. No explicit when-not-to-use, but sufficient guidance for typical usage.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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