MCP-TUPAD

by brujoh88

Overview Schema Related Servers Score Discussions

JavaScript

Local

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.1.0
Disambiguation5/5
Cada herramienta tiene un propósito claramente distinto: listar materias, ver contenido, vencimientos, trabajos prácticos, notas, foros y descargar archivos. No hay superposición entre ellas.
Naming Consistency4/5
La mayoría sigue el patrón verbo_sustantivo (listar_materias, ver_contenido_materia, ver_trabajos_practicos, ver_notas, leer_avisos_foro, descargar_archivo). Una excepción es 'proximos_vencimientos', que es un sustantivo sin verbo.
Tool Count5/5
Con 7 herramientas, la cantidad es adecuada para un asistente de gestión universitaria. Cubre las consultas principales sin ser excesivo.
Completeness3/5
Las herramientas son principalmente de consulta, faltan operaciones de creación o modificación (como entregar trabajos o publicar en foros). Para un asistente informativo es suficiente, pero hay ausencias notables para completar el ciclo de vida del estudiante.
Average 4.4/5 across 7 of 7 tools scored. Lowest: 3.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 3 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
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.json to 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

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 tool returns data but does not disclose any behavioral traits such as idempotency, side effects, permissions, or rate limits. The word 'Devuelve' implies a read operation, but that is not explicitly confirmed.
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 describes the output, second gives usage guidance. Both are front-loaded and to the point. No redundant or irrelevant 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?
Given the tool has 2 parameters and no output schema, the description mentions the output fields (consigna, fecha de entrega, delivery status) but does not provide a concrete structure or format. For a simple retrieval, it is adequate but could specify the exact output format or any limitations.
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 the baseline is 3. The tool description does not add any extra meaning beyond what the parameter descriptions already provide (courseid from listar_materias, solo_pendientes for filtering). It merely mentions output fields but not parameter details.
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 'Devuelve' (returns) and the resource 'trabajos prácticos' (practical works), specifying the key output fields: assignment, due date, and delivery status. This distinguishes it from sibling tools like 'listar_materias' or 'ver_contenido_materia' which serve different purposes.
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 provides usage scenarios: 'Usá esta herramienta cuando pregunten por un TP puntual, por la consigna de una entrega o por qué les falta entregar en una materia.' This gives clear guidance on when to use the tool.
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 full burden. It states the tool downloads a file, returns the local path, and for plain text files returns the content. It notes the default save directory and that the destination folder is created if missing. However, it does not disclose whether the tool overwrites existing files, handles errors, or has any rate limits. This is adequate but leaves some 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two short paragraphs. The first sentence states the core action and return value. The second paragraph adds defaults and optional parameter guidance. Every sentence serves a purpose with no fluff, and the key information is front-loaded.
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, the description covers the return values (local path, optional content for plain text). It explains default behavior and optional parameters. However, it omits potential errors, permissions, and file size limits. For a straightforward download tool, it is largely complete but could be more thorough.
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 100%, baseline is 3. The description adds value: for 'url' it clarifies it must come from ver_contenido_materia; for 'destino' it explains absolute/relative paths and that the folder is created if needed. For 'nombre' it only mentions default, matching schema. Overall, the description enriches the schema beyond the baseline.
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 downloads a file from the campus (apunte, PDF, presentación) using the URL from ver_contenido_materia. The verb 'baja' (download) and resource 'archivo del campus' are specific, and it distinguishes from sibling tools like listar_materias and ver_contenido_materia which are for listing and viewing, not downloading.
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 explicitly says to use this tool with the URL from ver_contenido_materia, providing clear usage context. It also explains the default save location and the optional 'destino' parameter. However, it does not mention when not to use it (e.g., for non-downloadable files or large downloads) or provide explicit alternatives.
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 provided; description adds behavioral context (returns per-item grades and teacher feedback) but lacks details on side effects or error handling.
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?
Three sentences, no wasted words, front-loaded with purpose and usage guidance.
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?
No output schema, but description explains what is returned. Adequate for a simple read tool with two parameters.
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 coverage is 100%. Description adds helpful cross-reference: courseid obtained from listar_materias. Optional parameter clearly explained in 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 clearly states the tool returns grades per item with teacher feedback, distinct from siblings like listing courses or assignments.
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?
Explicitly tells when to use: when asked about grades, course progress, or submission corrections. Does not mention when not to use, but context is clear.
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 carries the full burden and effectively discloses behavior: listing all subjects' assignments and quizzes ordered by date, plus fallback. It does not mention potential limitations like pagination, but for a simple list it is transparent enough.
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 concise paragraphs: the first states purpose and usage, the second provides fallback behavior. Every sentence adds value and the structure is front-loaded with core information.
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?
Given the simplicity (one optional parameter, no output schema), the description fully covers what the tool does, when to use it, and its behavior, making it complete for an agent.
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 parameter (dias), so the baseline is 3. The description adds no extra semantics beyond the schema's definition; it does not mention the parameter at all.
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 uses specific verbs ('Lista qué se vence') and resources (entregas de trabajos prácticos y cierres de cuestionarios), clearly distinguishing it from sibling tools like listar_materias or ver_trabajos_practicos, which focus on other aspects.
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 states when to use the tool (when asked about pending tasks, due this week, or study organization) and provides fallback behavior (informs next upcoming deadline if none in range), offering clear guidance on usage.
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 the full burden. It transparently explains the two modes (index vs detail), that detail includes file URLs for later downloading with 'descargar_archivo', and implies a read-only operation. It does not explicitly state the tool is non-destructive, but the context strongly suggests it.
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 two tightly written paragraphs plus a standalone guiding sentence. Every sentence adds value: first paragraph states purpose, second paragraph explains two modes and mentions file URLs, third sentence gives usage advice. No wasted words, front-loaded with core purpose.
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?
Given two parameters and no output schema, the description is remarkably complete. It covers the tool's dual behavior, the relationship with sibling tools (especially 'descargar_archivo'), and provides a best-practice invocation strategy. An agent can use this tool correctly without needing additional context.
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 coverage is 100% (both parameters described in schema). The description adds extra meaning: for 'unidad', it explains it accepts a name or partial name and that omitting it changes behavior to returning only the index. For 'courseid', it mentions it comes from 'listar_materias', providing valuable contextual sourcing. This goes beyond the schema descriptions.
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 explores course material (apuntes, PDFs, videos, tareas, foros) organized by unit. It distinguishes two modes: returning just the index when 'unidad' is omitted, and returning the full detail including file URLs when 'unidad' is provided. This differentiates it from siblings like 'descargar_archivo' or 'ver_trabajos_practicos'.
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 explicit guidance: 'Empezá siempre por el índice: las materias suelen tener decenas de unidades y pedir todo junto es innecesario.' This tells the agent to first call without 'unidad' to get an index, then optionally with 'unidad' for details. It could be more explicit about when not to use this tool versus siblings, but the guidance is clear and practical.
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 covers default behavior (only news forums) and the effect of 'todos_los_foros', noting that student forums are numerous. It does not detail return format or side effects, but for a read tool this is adequate.
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 concise with two clear sentences plus usage instructions. It is front-loaded with purpose and contains no redundant information.
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?
Given no output schema, the description sufficiently explains what the tool returns (latest posts) and covers the key parameter behavior. It is complete for its simplicity.
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 has 100% description coverage, so baseline is 3. The description adds context: default forum scope, association of courseid with 'listar_materias', and guidance on 'todos_los_foros'. This extra information justifies a score of 4.
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 returns the latest forum posts of a subject, specifying default behavior (news and announcements) and optional all forums. It distinguishes from sibling tools by focusing on forums.
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 advises to use when asked about news or teacher announcements, and describes when to use the 'todos_los_foros' parameter (only if student consultation forums are desired). Provides explicit usage scenarios.
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 discloses the tool's behavior: returns enrolled subjects with ID and progress. It doesn't mention any side effects, but none are expected for a read-only list operation.
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 only two sentences, front-loaded with the purpose, and every sentence adds value. No wasted words.
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 no-parameter tool, the description completely covers what the tool does and when to use it. It compensates for the lack of output schema by naming the return fields.
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?
The input schema has no parameters (100% coverage), so baseline is 3. The description adds value by specifying the returned fields (ID and progress), which helps the agent understand the output.
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 'Devuelve' (returns) and the resource 'materias en las que estás inscripto', with specific details (ID and progress). It distinguishes from sibling tools that likely require a subject ID.
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 says 'Usá esta herramienta primero cuando necesites el ID de una materia para cualquier otra consulta', providing clear guidance on when to use this tool versus alternatives.
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:

[![MCP-TUPAD MCP server](https://glama.ai/mcp/servers/brujoh88/MCP-TUPAD/badges/card.svg)](https://glama.ai/mcp/servers/brujoh88/MCP-TUPAD)

Score Badge

Copy to your README.md:

[![MCP-TUPAD MCP server](https://glama.ai/mcp/servers/brujoh88/MCP-TUPAD/badges/score.svg)](https://glama.ai/mcp/servers/brujoh88/MCP-TUPAD)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

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/brujoh88/MCP-TUPAD'

If you have feedback or need assistance with the MCP directory API, please join our Discord server