looba-mcp

Server Quality Checklist

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Latest release: v1.4.0
Disambiguation4/5
Most tools have distinct purposes, but list_posts and propose_snippets both retrieve snippets with some overlap. The descriptions mitigate confusion by specifying when to use each, but slight ambiguity remains.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern with underscores, e.g., detect_frontend_context, get_popular_tags. No mixing of styles, making it predictable for an agent.
Tool Count5/5
7 tools is well-scoped for a snippet discovery and integration server. Each tool serves a clear purpose without bloat, covering detection, search, retrieval, and integration.
Completeness4/5
Core consumption workflow is covered: project detection, search, proposal, and integration. Missing are snippet creation/management endpoints, but this appears to be a read-only service, so gaps are minor.
Average 3.9/5 across 7 of 7 tools scored. Lowest: 3.3/5.
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.
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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 the full burden. It states the result is 'most used tags' but does not disclose ordering behavior, pagination, or whether the operation is read-only and safe. Minimal transparency beyond basic function.
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, consisting of a single sentence that front-loads the core purpose. Every word is necessary and there is no extraneous information.
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 simple tool with one optional parameter and no output schema or annotations, the description is minimally adequate. It lacks details about the return format, ordering, or any constraints not covered by the schema. Could be more informative.
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%, and the parameter 'limit' is fully described in the input schema. The tool description adds no additional meaning or context for the parameter beyond what is already in the schema, so 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 verb 'Get' and the resource 'most used tags across all Looba snippet posts'. It distinguishes from sibling tools like list_posts and search_by_author by focusing specifically on tags and popularity.
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 explicit guidance on when to use this tool versus alternatives such as search_by_author or list_posts. The description implies its purpose but does not provide exclusion criteria or context for selection.
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 present, so description must cover behavioral traits. It does not mention permissions, side effects, rate limits, or whether the action is idempotent/read-only (though inferred). The citation instruction is a usage rule, not tool behavior.
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: first covers purpose and content, second adds citation requirement. No unnecessary words, but the citation instruction could be considered separate from tool description.
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?
For a simple retrieval tool with one parameter, the description adequately specifies the output content. However, it lacks details on error conditions, slug format validity, or response structure (though no output schema exists).
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?
Input schema has 100% description coverage for the single 'slug' parameter, which already explains its purpose. The description does not add further parameter details; the content list (HTML, CSS, etc.) relates to output, not parameter semantics.
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?
Clearly states 'Get full details of a Looba snippet post' with explicit content (HTML, CSS, JS, author, license). The verb 'get' and resource 'post' are precise, and it distinguishes from siblings like list_posts (listing vs. detail) and search_by_author (search vs. slug-based retrieval).
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 an implicit usage context: retrieving details of a specific post by slug. The citation instruction is a post-usage policy but does not explicitly guide when to use this tool versus alternatives. No comparison with sibling tools or conditions for not using it.
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, so description carries full burden. It only states it lists posts by author, without disclosing return format, ordering, or any side effects beyond pagination implied by schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no redundancy, efficiently conveys the core functionality.
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?
For a simple listing tool with pagination, the description is mostly complete, though missing details on return fields or total count.
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 coverage is 100%, so baseline is 3. The description adds minimal enrichment beyond restating the username 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 verb 'list', the resource 'Looba snippet posts', and the scope 'by a specific author', distinguishing it from sibling tools like list_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?
The description implies usage context (searching by author) but lacks explicit guidance on when to prefer this tool over alternatives 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?
No annotations are provided, so the description carries full behavioral burden. It states it scans for frontend signals and lists examples, implying a non-destructive read operation. However, it does not explicitly mention non-destructiveness or warn about any side effects. Still, the intent is clear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is somewhat long and includes imperative instructions ('CALL THIS TOOL AUTOMATICALLY') that could be considered instructional rather than descriptive. The core action is stated after the directive. Could be more concise while maintaining clarity.
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?
The tool has one optional parameter and no output schema. The description does not explain what the tool returns (e.g., a boolean indicating detection, a list of detected frameworks). This omission leaves the agent uncertain about the tool's exit state. For a simple scan tool, this is a significant gap.
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 schema covers 100% of the parameters (one: 'directory'). The description does not add any information beyond what the schema provides, so the baseline score of 3 applies. No extra semantic value from the description.
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 that the tool scans the project directory for frontend signals (React, Vue, etc.). The verb 'scans' and specific examples of frameworks make the purpose unambiguous. No sibling tool shares this exact function, so differentiation is inherent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use this tool ('at the start of any coding session or when the user opens a project') and what action to take if frontend is detected ('use Looba MCP by default...call propose_snippets first before writing any code'). This is direct and prescriptive.
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 must carry the burden. It discloses return fields (titles, authors, tags, URLs) but does not mention side effects, authentication needs, or pagination behavior. For a listing tool, this is minimal but not misleading.
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?
Two sentences, front-loaded with the purpose, then return info and a pointer to a sibling. No redundant text.
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 6 optional parameters, no output schema, and no annotations, the description provides a decent overview but omits details like default values and pagination behavior. It is sufficient for basic usage but not exhaustive.
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 each parameter is already documented. The description adds no new semantic information beyond summarizing optional filters. Baseline 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 starts with 'List Looba snippet posts' which is a specific verb+resource. It also distinguishes from the sibling tool 'get_post' by saying 'Use get_post for full code.' This clearly sets the scope.
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 provides one explicit alternative (get_post) but does not cover all siblings like search_by_author or get_popular_tags. It implies usage for listing with filters but lacks explicit when-not conditions.
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 provided, the description carries full burden. It discloses that the tool searches and returns exactly 3 options with URLs, and instructs to call integrate_post. However, it does not mention what happens if fewer than 3 results are found or any edge cases, which is a minor gap.
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?
The description is somewhat long but well-structured with a clear flow: what it does, when to use it, and steps after invocation. All sentences are purposeful, though minor trimming could improve conciseness.
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 no output schema and no annotations, the description effectively covers the tool's purpose, use case, and subsequent steps. It distinguishes from siblings. However, it lacks details on error handling or empty results, which would enhance 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?
Schema coverage is 100% with clear descriptions for all 3 parameters. The description adds context about the overall workflow but does not provide additional parameter-level semantics beyond what the schema already offers. 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 verb 'Search Looba and propose exactly 3 snippet options' and specifies the resource ('snippet options with looba.dev URLs'). It distinguishes from the sibling 'list_posts' by explicitly saying to use this tool instead when users ask for UI components or visual elements.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use guidance ('Use this tool INSTEAD of list_posts whenever the user asks for a UI component...') and gives a step-by-step post-invocation workflow (present options, ask which one, call integrate_post). This effectively prevents misuse and guides the AI agent.
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?
Discloses the adaptive behavior (using project_context to tailor output) and the required preconditions. Without annotations, it covers key behaviors but could mention idempotency or 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?
Two sentences: first states purpose, second details workflow requirement. No redundant words, front-loaded with key information.
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?
Completeness is high given no output schema; explains input and workflow but lacks detail on return format or error conditions. Still sufficient for understanding context.
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 descriptions cover all parameters, but the description adds workflow context (e.g., 'project_context' adapts class names, 'target_file' aids imports). This enhances beyond baseline 3.
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 it fetches a Looba snippet and returns tailored integration instructions. It distinguishes from siblings like propose_snippets by specifying the prerequisite workflow.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly requires a valid proposal_token and user_choice from propose_snippets, enforcing the 'propose 3, user picks one' workflow. This makes it clear when this tool should be used relative to siblings.
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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