DOOR Knowledge MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: get_door_document retrieves a specific document by ID, list_door_categories lists categories with counts, and search_door_knowledge searches for documents using keywords or categories. There is no overlap in functionality, making it easy for an agent to select the right tool.
Naming Consistency5/5All tool names follow a consistent snake_case pattern with a clear verb_noun structure (get_door_document, list_door_categories, search_door_knowledge). The naming is predictable and enhances readability across the tool set.
Tool Count3/5With only 3 tools, the server feels thin for a knowledge base domain, as it lacks operations like creating, updating, or deleting documents or categories. While the tools cover basic retrieval and listing, the count is borderline for comprehensive coverage.
Completeness2/5The tool surface is significantly incomplete for a knowledge base server. It only supports read operations (get, list, search) with no ability to create, update, or delete documents or categories. This will cause agent failures when full lifecycle management is needed.
Average 3.8/5 across 3 of 3 tools scored. Lowest: 3.2/5.
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
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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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool lists categories with document counts, but doesn't describe return format, pagination, error conditions, or performance characteristics. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
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, efficient sentence in Spanish that communicates the core functionality without unnecessary words. It's appropriately sized for a simple listing tool and front-loads the essential information.
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 (0 parameters, no annotations, no output schema), the description provides adequate basic information about what the tool does. However, without annotations or output schema, it should ideally describe the return format more explicitly to help the agent understand what to expect from the response.
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 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and it adds value by explaining what the tool returns (categories, subcategories, and document counts).
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 clearly states the tool's purpose: listing all categories and subcategories with document counts from the DOOR Knowledge Base. It uses specific verbs ('Lista todas') and identifies the resource ('categorías y subcategorías'), though it doesn't explicitly differentiate from sibling tools like 'get_door_document' or 'search_door_knowledge'.
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. The description doesn't mention sibling tools or suggest scenarios where this listing tool would be preferred over 'search_door_knowledge' or 'get_door_document', leaving the agent without contextual usage direction.
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 describes the tool as retrieving full content, which implies a read-only operation, but lacks details on permissions, rate limits, error handling, or output format. The description adds basic context but misses key 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences with zero waste: the first states the purpose, and the second provides usage guidance. It is front-loaded and every sentence earns its place by adding value.
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 low complexity (one parameter, no output schema, no annotations), the description is adequate but incomplete. It covers purpose and usage well but lacks details on output format, error cases, or behavioral constraints, which are important for a tool without annotations.
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?
Schema description coverage is 100%, so the schema already documents the single parameter 'document_id' with its description. The description adds no additional meaning beyond what the schema provides, such as format examples or constraints, meeting the baseline for high schema coverage.
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 specific action ('Obtiene el contenido completo') and resource ('un documento específico de la DOOR Knowledge Base'), distinguishing it from sibling tools like list_door_categories and search_door_knowledge by focusing on retrieving full content of a single document rather than listing categories or searching.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly states when to use this tool ('Usa el ID obtenido de search_door_knowledge'), providing a clear prerequisite and distinguishing it from the sibling tool search_door_knowledge, which is used to obtain the ID needed here.
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 the full burden and adds valuable behavioral context: it discloses that the tool is 'MUY RÁPIDO porque usa un índice pre-generado' (performance characteristic) and describes the return format ('lista de documentos relevantes con resúmenes'). It doesn't cover aspects like error handling or authentication needs, but provides useful operational insights.
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 efficiently structured in two sentences: the first states purpose and methods, the second adds performance context and return format. Every sentence earns its place with no wasted words, and key information is front-loaded.
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?
For a search tool with no annotations and no output schema, the description is reasonably complete: it covers purpose, methods, performance, and return format. However, it doesn't specify what 'documentos relevantes' entails (e.g., ranking criteria) or error scenarios, leaving some gaps in operational context.
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?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain how 'query' interacts with 'category' or provide search syntax examples). Baseline 3 is appropriate when the schema does the heavy lifting.
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 specific action ('Busca documentos') and resource ('en la DOOR Knowledge Base'), with distinct search methods ('por palabras clave, categorías o contenido') that differentiate it from sibling tools like 'get_door_document' (which presumably retrieves a specific document) and 'list_door_categories' (which lists categories).
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 provides clear context for when to use this tool (searching documents by keywords, categories, or content) and implicitly references 'list_door_categories' for available categories in the input schema. However, it lacks explicit guidance on when NOT to use it or direct alternatives to sibling tools.
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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