mcp-diagrama-iterativo-mermaid
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation4/5
Las herramientas se diferencian principalmente por su entrada y propósito: analizar_proyecto solo inspecciona, crear_diagrama_proyecto incluye análisis pero produce HTML final, y las dos de Mermaid se distinguen por aceptar código o archivo. La única posible confusión es entre analizar y crear, pero sus salidas son claramente distintas.
Naming Consistency4/5Todos los nombres usan snake_case en español y siguen un patrón verbo + objeto con nombres descriptivos. Las variantes con frases más largas para indicar la entrada son coherentes, aunque no mantienen una estructura sintáctica idéntica.
Tool Count5/5Cuatro herramientas cubren de forma compacta el propósito del servidor: análisis previo, generación integral, generación desde código y conversión desde archivo. No hay herramientas redundantes ni faltan funciones básicas para el flujo esperado.
Completeness5/5El conjunto cubre el ciclo principal del dominio: inspeccionar un proyecto, obtener un diagrama completo, compilar código Mermaid y convertir ficheros .mmd/.mermaid en HTML interactivo. No se detectan huecos significativos para el propósito declarado.
Average 4.2/5 across 4 of 4 tools scored.
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
Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.
If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.
MCP servers without a LICENSE cannot be installed.
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.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add
glama.jsonto the root of your repository:{ "$schema": "https://glama.ai/mcp/schemas/server.json", "maintainers": [ "your-github-username" ] }Then . Browse examples.
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
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the behavioral disclosure burden and does it well: it states the generated artifact is a single-file HTML app, reveals the air-gapped/no-CDN behavior, and lists concrete runtime features like drag-and-drop, zoom, minimap, and layered filters. It does not mention overwrite behavior or validation failures, but the key behavioral contract 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The core purpose is front-loaded and the feature bullets are informative rather than filler. The list is slightly long, but each bullet conveys meaningful behavioral details that help an agent predict output quality and constraints.
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?
Given there is an output schema, the description does not need to detail return values. It covers inputs, output format, key interaction features, and the air-gapped constraint. It is slightly incomplete on edge cases like file overwriting, unsupported Mermaid diagram types, or when to prefer a sibling tool, but it is sufficient for correct invocation in the common case.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain the parameters, and it does. It clarifies mermaid_code with an example, specifies that output_path must be an absolute path ending in .html, and explains titulo as the visual title in the top bar. This goes well beyond the bare parameter names.
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 a concrete verb ('Compila'), a specific resource (Mermaid textual specs), and a definite output (single-file interactive HTML5+SVG+Vanilla JS app). It is easy to understand what the tool does, though it does not explicitly contrast itself with the sibling tools like convertir_archivo_mermaid.
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 intended use case is implied: use this when you have Mermaid DSL and want an interactive, self-contained web diagram. However, there is no explicit guidance about when NOT to use it or which sibling tool should be chosen instead, such as convertir_archivo_mermaid.
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 behavioral burden. It discloses that the tool reads an existing file and generates an HTML file, including the default output location. It does not describe overwrite behavior, permission needs, or failure modes, which would strengthen 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 concise and well-structured: a one-sentence purpose followed by a focused Args section. No filler or redundant content; every sentence adds useful information.
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 simple two-parameter conversion tool, the description covers purpose, input requirements, output format, and default output behavior. The presence of an output schema means return values do not need explanation. Minor gaps like overwrite behavior and validation details prevent a perfect score.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description fully compensates by explaining each parameter: input_file as an absolute path to .mmd/.mermaid and output_path as optional, with the default behavior of generating next to the original file. This adds clear meaning beyond the bare schema titles.
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 states a specific action: converts an existing .mmd or .mermaid file into an interactive HTML5 web application. It clearly identifies the resource type and output type, and the phrase 'archivo existente' helps differentiate it from siblings like generar_diagrama_desde_mermaid.
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 an existing .mmd or .mermaid file to convert. However, it does not explicitly mention alternatives, exclusions, or when not to use this tool compared to the sibling tools.
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 hay anotaciones, así que la descripción asume toda la carga, y revela el comportamiento esencial: lee el proyecto, sintetiza su arquitectura y escribe un archivo .html autónomo e interactivo, incluyendo la ubicación por defecto (docs/diagrama_interactivo.html), lo que transparenta el efecto secundario de escritura. No obstante, omite comportamientos ante casos límite como rutas inválidas, proyectos no soportados o tiempos de análisis en proyectos grandes.
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?
Aproximadamente 70 palabras: una frase principal que promete el valor clave (análisis + generación directa) seguida de una lista Args consistente y escaneable. Cada oración aporta información no redundante y el contenido más importante está al frente.
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?
Existe output schema, por lo que los valores de retorno están cubiertos, y los parámetros quedan totalmente aclarados en la descripción. Faltan elementos relevantes para una herramienta de análisis compleja: criterios de selección frente a los hermanos, tipos de proyecto/lenguajes soportados, y comportamiento ante errores o proyectos no analizables.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Con 0% de cobertura en el esquema, la descripción compensa completamente documentando los tres parámetros con significado, opcionalidad y valores por defecto: project_path como ruta absoluta, output_path con su destino y default, y titulo con su fallback al nombre de la carpeta del proyecto. Esto supera ampliamente la línea base exigible cuando el esquema no aporta nada.
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?
La descripción usa un verbo específico ('genera') sobre un recurso claro (diagrama interactivo .html) y detalla el flujo completo: analiza, detecta capas, sintetiza arquitectura y produce el archivo. El calificativo 'Todo en Uno' y la generación 'directamente' la diferencian de los hermanos analizar_proyecto (solo análisis), generar_diagrama_desde_mermaid (requiere mermaid) y convertir_archivo_mermaid (solo conversión).
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?
La etiqueta 'Herramienta integral Todo en Uno' y el adverbio 'directamente' transmiten por implicación que esta herramienta es para obtener el diagrama completo desde una ruta de proyecto, en contraste con las herramientas hermanas que cubren pasos aislados. Sin embargo, no hay criterios explícitos de cuándo usarla ni exclusiones del tipo 'si ya tienes mermaid, usa generar_diagrama_desde_mermaid'; el agente debe inferir la ruta de decisión.
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, the description carries the full burden. It clearly communicates a read-only inspection action ('Inspecciona') and enumerates what will be examined (stack, layers, files, diagram files). It does not mention side effects or return format in detail, but for an analysis tool the disclosed scope is strong and contains no contradictions.
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?
Three concise sentences: purpose, detection details, and parameter explanation. The information is front-loaded and each sentence earns its place, with no filler or repetition of schema content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter inspection tool with no annotations and no output schema, the description is sufficiently complete. The agent knows the input format, what the tool will analyze, and what it will detect, so it can invoke the tool correctly without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description fully compensates for the single parameter: it explains project_path as the absolute path to a project or repository and provides a concrete example ('D:/2026/MiProyecto'). This adds real meaning beyond the bare schema property.
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 opens with a specific verb and resource: 'Inspecciona la estructura de un proyecto en el disco local o repositorio'. It then names concrete detection targets (stack, architectural layers, representative files, existing .mmd/.puml diagrams), which makes its purpose unmistakable and distinguishes it from sibling tools that create or convert diagrams.
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 inspection workflow is implied by the phrase 'busca si ya existen diagramas', suggesting the tool is a precursor to diagram creation. However, it never explicitly states when to prefer this tool over the sibling diagram tools or when not to use it, so the guidance remains implicit rather than explicit.
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/martincrespo77/MCP-Diagrama-Iterativo-Mermaid'
If you have feedback or need assistance with the MCP directory API, please join our Discord server