devto-mcp
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool targets a distinct resource and action: browsing the public feed, fetching a single article, listing personal articles, getting profile info, creating, updating, and fetching comments. The descriptions clearly separate the public vs. authenticated scopes, so no ambiguity exists.
Naming Consistency5/5All tool names follow a consistent `devto_verb_noun` pattern in snake_case, with verbs like list, get, create, update. This makes the set predictable and easy to navigate.
Tool Count5/5Seven tools is well-scoped for a Dev.to server covering article retrieval, management, profile, and comments. Each tool has a clear purpose, and the count is neither sparse nor bloated.
Completeness4/5The set covers the core article lifecycle (create, read, update, list) and comments, plus profile access. The only notable gap is a missing delete operation for articles, which agents might need for full content management but can work around.
Average 3.3/5 across 7 of 7 tools scored. Lowest: 2.7/5.
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
- Last stable release on
- 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.
This repository includes a glama.json configuration file.
This server has been verified by its author.
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?
No annotations are provided, so the description carries full responsibility for behavioral disclosure. It only reveals that the feed is 'public' (implying no auth), but says nothing about pagination behavior, response format, rate limits, or potential side effects. This is insufficient for a tool with no structured annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence without fluff. It effectively communicates the core function, though additional details about filtering could be condensed without losing clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 5 parameters, no annotations, and no output schema, the description is too sparse. It lacks usage context, behavioral details, and does not address the pagination parameters or how it differs from sibling tools. This leaves the agent under-informed for invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 40%, with tag, page, and perPage lacking descriptions. The description mentions 'tag, author, or top-of-period' which adds some meaning to tag, username, and top, but it does not clarify page/perPage semantics or defaults. It partially compensates but leaves significant gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Browse the public Dev.to feed' clearly identifies the tool as listing public articles, with a specific verb and resource. It partially distinguishes from siblings like devto_get_article (single article) by implying a feed/list context, though it could be more explicit about it being a listing operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 devto_get_my_articles or devto_get_article. It implies usage for browsing the public feed but does not state exclusions or recommend sibling tools for other use cases.
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, the description must carry the full burden of behavioral disclosure. It indicates the result (threaded comments) but does not explain authentication requirements, pagination, error behavior, or read-only nature beyond the verb 'get'. This is insufficient for full transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, front-loaded with the key action, and contains no redundant or filler content. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite low complexity (one parameter), the description lacks essential context: no output format, response structure, or error handling. Since there is no output schema and no annotations, the description should provide at least a basic expectation of what the tool returns, which it does only vaguely with 'threaded comments'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It does not provide any additional meaning for 'articleId'—no format, examples, or source for the ID. The phrase 'for an article' only repeats the parameter name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('threaded comments for an article'), clearly distinguishing it from sibling tools like devto_get_article or devto_list_articles. The term 'threaded' adds specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. There are no explicit use cases, prerequisites, or exclusions. The description simply states the action without contextualizing it among the sibling tools.
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, the description carries the full burden. It discloses partial-update behavior ('Only the fields you provide are changed') and ownership requirement ('you own'), but omits details about authentication, error handling, or response format. This is useful but incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences, every word earns its place. It is front-loaded with the key operation and adds the important partial-update caveat without waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with six parameters, no annotations, and no output schema, the description is underspecified. It lacks usage guidance, return-value expectations, error behavior, and any parameter details, leaving the agent to infer too much from the schema alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description adds no parameter-specific meaning. It only generically refers to 'fields you provide' without explaining any of the six parameters (id, tags, title, series, published, bodyMarkdown) or how they interact.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Edit') and resource ('existing article you own'), clearly distinguishing it from the sibling create tool. It immediately conveys the operation and scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 create_article or other alternatives. The description does not mention that this should be used only for modifying existing articles, nor does it exclude scenarios like creating new articles.
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 must disclose behavioral traits. It only mentions the public/draft dichotomy, which largely mirrors the `published` schema field. It fails to mention authentication requirements, rate limits, return values, or side effects like persisting the article. This is insufficient for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one concise sentence, front-loading the core purpose. It has no wasted words, but it is so short that it sacrifices informative content. Still, conciseness is appropriate for the minimal information provided.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 8 parameters, no annotations, no output schema, and sibling actions, the description is incomplete. It does not explain what happens on success (e.g., returns an article object), how it handles validation, or when publishing is immediate. The tool is a complex create operation yet the description oversimplifies it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50%, so the description should compensate for the undocumented params (tags, title, description, canonicalUrl). It does not. It only hints at the published param by saying 'public post or private draft.' Other parameters receive no elucidation, leaving a clear gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create') and the resource ('a new article'), and distinguishes between public and private drafts. This uniquely identifies the tool's function among siblings like update_article, which modifies existing articles.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for creating new articles and mentions the two publishing states, but it does not explicitly contrast with update_article or outline when to use which tool. There are no direct alternatives or exclusions mentioned, so guidance is 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.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. 'List' implies a read-only operation, but it does not disclose any additional behavioral traits such as pagination, default state filtering, or authentication requirements. This is minimal and leaves significant gaps for an agent to infer.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that is front-loaded and free of unnecessary words. It is appropriately concise, though it could arguably contain more detail without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and three optional parameters, yet the description does not explain return values, pagination behavior, or how the state parameter affects results. Given the minimal description and lack of structured output metadata, the description is not complete enough for an agent to use the tool confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no explanation of the page, state, or perPage parameters. The agent must rely entirely on the schema's property names and constraints, which is insufficient for clear parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'List' and clearly identifies the resource as 'the authenticated account's own articles.' This distinguishes it from sibling tools like devto_list_articles, which likely lists all articles, and devto_get_article, which fetches a single article.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use this tool: when you need the authenticated user's articles rather than public articles or a specific article. However, it does not explicitly mention alternatives or exclusions, so it stops short of full guidance.
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. The verb 'Fetch' implies a safe read, and 'full content' adds some behavioral context. However, it does not describe return format, error behavior, or rate limits, which would be helpful for a tool with no annotations and no output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It is front-loaded with the verb and resource, making it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one required parameter, no output schema, no annotations), the description covers the core function. However, it lacks details about error cases (e.g., not found) and the structure of the returned content, which would make it more complete for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has zero description coverage for the 'id' parameter. The description adds 'numeric id', which clarifies the expected input beyond the schema's 'string' or 'number' type. This partially compensates for the lack of schema documentation, but it does not fully explain the parameter's role beyond being an identifier.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Fetch') with a clear resource ('a single article') and a scope ('by its numeric id'). It clearly distinguishes this from sibling tools like 'list' or 'get_my_articles'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool (when you have a numeric id and need full content), but it does not explicitly state alternatives or exclusions. No mention of when not to use it is provided.
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, the description carries the full transparency burden. It discloses a read operation and the requirement for authentication, but does not describe the response structure or behavior on failure. For a simple read-only tool, this is minimal but sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, straightforward sentence that fully conveys the tool's purpose. It is concise and front-loaded, with no unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, so the description could ideally explain what 'profile info' includes. However, the tool's low complexity (zero parameters, simple read operation) makes the current description nearly complete, with only minor ambiguity about return fields.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema coverage is effectively complete (empty properties). The baseline for no parameters is 4; the description adds nothing further because there are no parameters to clarify.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves the authenticated account's profile info, using a specific verb ('Get') and resource ('profile'). It distinguishes from sibling tools that focus on articles and comments, and the title reinforces the 'my profile' scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit usage guidance or comparisons to alternatives are provided. The intended use is implied by the tool's name and description, but it does not state when to use this tool versus the sibling tools.
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
Copy to your README.md:
Score Badge
Copy to your README.md:
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
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/AhmadTariq1337/devto-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server