codex_canvas_mcp
Codex Canvas MCP
Un servidor MCP local y portátil que permite a clientes compatibles leer Canvas y, solo después de varias comprobaciones de seguridad independientes, crear contenido común de curso.
Modelo de seguridad
Las lecturas de Canvas están disponibles por defecto tras la configuración local de credenciales.
La escritura está deshabilitada por defecto.
Cada escritura de contenido requiere una política local habilitada, una coincidencia exacta en la lista de permitidos por curso, un texto de confirmación exacto y la aprobación en el cliente MCP.
La subida de imágenes añade una comprobación de carga útil: solo se puede enviar un PNG, JPEG o WebP de propiedad local dentro de una carpeta de confianza configurada, con un tamaño máximo de 10 MiB.
No existe una herramienta genérica de escritura en Canvas.
Las credenciales permanecen en 1Password y, opcionalmente, en el Llavero de macOS. No pertenecen a este repositorio ni a la configuración del cliente.
Cada herramienta de contenido está marcada como mutante y destructiva para que los clientes compatibles puedan exigir aprobación. El servidor local también rechaza una llamada a menos que su confirmación exacta coincida con la acción solicitada, por ejemplo APPROVE CANVAS MODULE WRITE course <course_id>.
La creación de rúbricas acepta una URL de asignación de Canvas del mismo origen, una URL de elemento de módulo de asignación o una URL de curso que contenga un parámetro de consulta assignment_id. Las cadenas de consulta y los fragmentos se ignoran después de resolver el curso y la asignación. La URL nunca elude la política del curso: su ID de curso debe estar explícitamente en la lista de permitidos, y la creación de rúbricas requiere APPROVE CANVAS RUBRIC WRITE course <course_id>. La herramienta se niega a reemplazar una rúbrica de asignación existente, requiere descripciones para cada criterio y calificación, y exige que los puntos de la rúbrica de calificación coincidan con los puntos de la asignación.
Related MCP server: canvas-lms
Qué se incluye
Herramienta | Capacidad | Por defecto |
| Leer el perfil autenticado | Disponible |
| Leer módulos y elementos de un curso | Disponible |
| GET de una ruta normalizada de la API v1 de Canvas | Disponible |
| Inspeccionar el estado de la política local | Disponible |
| Subir una imagen verificada desde la carpeta de confianza configurada | Bloqueado |
| Crear o actualizar una página | Bloqueado |
| Crear un módulo | Bloqueado |
| Colocar un elemento de contenido en un módulo | Bloqueado |
| Crear una asignación | Bloqueado |
| Crear y adjuntar una rúbrica de asignación desde una URL de Canvas | Bloqueado |
| Crear un debate | Bloqueado |
| Crear un Cuestionario Clásico | Bloqueado |
| Añadir una pregunta a un Cuestionario Clásico | Bloqueado |
| Eliminar una página | Bloqueado |
| Eliminar una asignación | Bloqueado |
| Eliminar un debate | Bloqueado |
| Eliminar un Cuestionario Clásico | Bloqueado |
| Eliminar un módulo y sus ubicaciones de elementos | Bloqueado |
Configurar un nuevo Mac
Requisitos previos: Python 3.11 o superior, la CLI de 1Password, una cuenta de servicio de 1Password que pueda leer solo el elemento de credenciales de Canvas previsto, y un token de API de Canvas con los privilegios mínimos prácticos para tu trabajo.
Clona e instala en un entorno aislado:
git clone https://github.com/mrchris-ai/codex_canvas_mcp.git cd codex_canvas_mcp python3 -m venv .venv . .venv/bin/activate python -m pip install --upgrade pip python -m pip install -e .Crea un elemento de 1Password cuyo campo oculto contenga el token de API de Canvas. Da a la cuenta de servicio acceso de lectura solo al contenedor/elemento correspondiente. Anota el nombre del contenedor, el nombre o ID del elemento y la etiqueta del campo oculto; no pongas sus valores en este repositorio.
Elige un método de entrega del token de cuenta de servicio:
Para una sesión de shell de corta duración, proporciona
OP_SERVICE_ACCOUNT_TOKENal proceso del servidor MCP a través de tu lanzador de secretos local.En macOS, guarda ese token en el Llavero y configura etiquetas de búsqueda no secretas. Ejemplo de comando (solicita de forma segura; no pongas el token en la línea de comandos):
security add-generic-password -U -s "your-service-label" -a "your-account-label" -w
Configura el proceso del servidor con estos valores no secretos:
Variable
Propósito
CANVAS_BASE_URLOrigen HTTPS de Canvas, como
https://school.instructure.comCANVAS_OP_VAULTNombre o ID del contenedor de 1Password
CANVAS_OP_ITEMNombre o ID del elemento de credenciales de Canvas
CANVAS_OP_FIELDEtiqueta del campo de token oculto; por defecto
credentialCANVAS_KEYCHAIN_SERVICEEtiqueta de servicio del Llavero de macOS cuando no se usa
OP_SERVICE_ACCOUNT_TOKENCANVAS_KEYCHAIN_ACCOUNTEtiqueta de cuenta del Llavero de macOS cuando no se usa
OP_SERVICE_ACCOUNT_TOKENCANVAS_IMAGE_UPLOAD_ROOTRuta absoluta a la única carpeta local desde la que se permite subir imágenes
Prueba solo el protocolo y las comprobaciones de seguridad, sin contactar con Canvas ni leer credenciales:
python -m unittest discover -s tests -v printf '%s\n' '{"jsonrpc":"2.0","id":1,"method":"tools/list"}' | python -m canvas_mcpAñade el servidor stdio a Codex. La forma a nivel de proyecto es:
[mcp_servers.canvas] command = "/absolute/path/to/codex_canvas_mcp/.venv/bin/python" args = ["-m", "canvas_mcp"] [mcp_servers.canvas.env] CANVAS_BASE_URL = "https://school.instructure.com" CANVAS_OP_VAULT = "your-vault" CANVAS_OP_ITEM = "your-item" CANVAS_OP_FIELD = "credential" CANVAS_KEYCHAIN_SERVICE = "your-service-label" CANVAS_KEYCHAIN_ACCOUNT = "your-account-label" CANVAS_IMAGE_UPLOAD_ROOT = "/absolute/path/to/reviewed/canvas-images"Pon esto en el
.codex/config.tomldel proyecto de confianza o en tu configuración personal de Codex. No añadas valores secretos. Reinicia o abre una nueva tarea después de cambiar la configuración de MCP y verifica las herramientas listadas antes de solicitar datos de Canvas.
Compatibilidad con ChatGPT
Este repositorio implementa un servidor MCP stdio local para Codex y otros clientes que admitan MCP stdio local. Las aplicaciones personalizadas actuales de ChatGPT no se conectan directamente a un servidor stdio local. La guía actual de OpenAI es exponer un MCP local privado a través de Secure MCP Tunnel (o implementar un endpoint MCP remoto revisado), sujeto a la disponibilidad del plan y del administrador del espacio de trabajo. No expongas este proceso directamente a la internet pública.
Consulta Modo desarrollador y aplicaciones MCP en ChatGPT antes de intentar la configuración de ChatGPT; la disponibilidad y el comportamiento de aprobación pueden cambiar.
Habilitar herramientas de creación de contenido
Mantén la escritura desactivada a menos que una tarea específica lo requiera.
Copia
config/write-policy.example.jsona una ubicación fuera del repositorio.Añade solo los IDs de curso de Canvas exactos aprobados para la creación de contenido.
Establece
enabledentruey restringe el archivo:chmod 600 /absolute/private/path/write-policy.jsonAñade
CANVAS_WRITE_POLICY=/absolute/private/path/write-policy.jsonal entorno del servidor MCP.Reinicia el cliente y llama a
canvas_get_write_policypara verificar la política efectiva.Para cada escritura de contenido, revisa el objetivo y la carga útil exactos. Proporciona la frase de confirmación específica de la acción y aprueba la acción mutante en el cliente.
Desactiva la política de nuevo cuando la tarea esté completa.
Si la variable está ausente, el archivo falta, los permisos son más amplios que 0600, la escritura está deshabilitada o el curso no está en la lista de permitidos, el servidor rechaza la escritura.
Habilitar la subida de imágenes
La subida de imágenes usa la misma política de escritura local y la lista de permitidos exacta por curso, además de CANVAS_IMAGE_UPLOAD_ROOT. La herramienta rechaza rutas relativas, enlaces simbólicos, archivos fuera de esa raíz, archivos no propiedad del usuario actual, tipos de imagen no admitidos, archivos cuya firma binaria no coincide con la extensión y archivos de más de 10 MiB. La confirmación exacta es APPROVE CANVAS IMAGE UPLOAD course <course_id>.
Canvas usa un intercambio de subida documentado en tres pasos: inicializar el archivo del curso a través de la API autenticada, enviar la imagen sin el token de acceso de Canvas a la URL de almacenamiento HTTPS devuelta por Canvas, y autenticar la ubicación de finalización de Canvas del mismo origen devuelta. La herramienta luego lee /api/v1/courses/<course_id>/files/<file_id> y comprueba el tipo MIME y el tamaño antes de devolver una ruta de vista previa persistente del curso. Nunca devuelve firmas de almacenamiento ni la URL de verificación de descarga de archivos.
Límite de creación actual
Este proyecto es la fuente de verdad para el MCP de Canvas local compartido utilizado por los chats compatibles en este Mac. Puede crear Páginas, Módulos y elementos de módulo, Asignaciones y Rúbricas de asignación, Debates y Cuestionarios Clásicos con preguntas después de las comprobaciones normales de política y aprobación. También proporciona herramientas de eliminación específicas para Páginas, Asignaciones, Debates, Cuestionarios Clásicos y Módulos; eliminar un Módulo quita sus ubicaciones de elementos pero no el contenido subyacente del curso. Su única capacidad de archivos locales es el subidor de imágenes con comprobación de carga útil descrito anteriormente. La subida de archivos genérica, los Nuevos Cuestionarios y la administración de cuentas/cursos siguen sin ser compatibles.
Consulta docs/2026-08-06-content-authoring-extension.md para el registro de implementación y validación de extremo a extremo.
Consulta docs/2026-08-16-image-upload-extension.md para el modelo de amenazas y el registro de validación de la subida de imágenes.
Desarrollo
python -m pip install -e .
python -m unittest discover -s tests -v
python -m compileall -q src testsLas pruebas simulan los límites de red y credenciales. Consulta AGENTS.md para los invariantes que los contribuyentes deben preservar y ROADMAP.md para las características administrativas diferidas intencionalmente.
Available Tools
11 toolscanvas_create_assignmentADestructive
Create exactly one Canvas assignment in an approved course. Disabled by default and requires explicit confirmation.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| course_id | Yes | ||
| published | No | ||
| description | No | ||
| confirmation | Yes | ||
| points_possible | No | ||
| submission_types | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds meaningful behavioral context beyond annotations: it notes the tool is 'disabled by default' and 'requires explicit confirmation,' which are important operational traits not captured by the readOnly/idempotent/destructive hints. It also clarifies the one-at-a-time creation behavior, providing useful transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with no filler or repetition. Every word earns its place, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the simplicity of the description, the tool has 7 parameters and no output schema, yet the description omits return value behavior and most parameter details. It does not explain what 'approved course' means or how confirmation works, leaving the agent without enough context to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate, but it only references the 'confirmation' parameter. It does not explain the meaning or constraints of course_id, name, published, description, points_possible, or submission_types, leaving significant semantic gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Create exactly one Canvas assignment in an approved course,' specifying the verb (create), resource (Canvas assignment), and scope (exactly one, in an approved course). This distinguishes it from sibling creation tools like canvas_create_module or canvas_create_discussion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when creating a Canvas assignment and mentions preconditions ('approved course', 'requires explicit confirmation'), but it does not explicitly name alternative tools or state when not to use this tool. The guidance is contextually clear but lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
canvas_create_classic_quizADestructive
Create exactly one Canvas Classic Quiz in an approved course. New Quizzes are not supported by this tool. Disabled by default and requires explicit confirmation.
| Name | Required | Description | Default |
|---|---|---|---|
| title | Yes | ||
| course_id | Yes | ||
| published | No | ||
| quiz_type | No | practice_quiz | |
| description | No | ||
| confirmation | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as destructive (destructiveHint=true) and non-read-only. The description adds valuable context beyond this: the restriction to Classic Quizzes, the requirement for an approved course, and the need for explicit confirmation. It does not contradict the annotations and enriches behavioral understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long, front-loaded with the main purpose, and each sentence adds distinct information (what it does, limitation, requirement). No filler or repetition; it is highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool complexity (6 params, no output schema), the description covers the core behavioral aspects: what is created, the Classic vs New distinction, and the confirmation requirement. It omits specifics about return values or quiz_type nuances, but these are secondary to the main purpose and reasonably supplemented by the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate for parameter meanings. It only references the 'confirmation' parameter and indirectly references course_id via 'approved course', but leaves title, published, quiz_type, and description without any added context. This is insufficient for a tool with 6 parameters where the schema alone provides limited guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'Create exactly one Canvas Classic Quiz'. It specifies the resource type (Canvas Classic Quiz) with the verb 'create', and distinguishes from sibling tools by explicitly stating it is for Classic Quizzes, not New Quizzes, and from quiz_question by focusing on the quiz itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: the tool works only in an 'approved course', is for Classic Quizzes (not New Quizzes), and 'requires explicit confirmation'. However, it does not explicitly name alternative tools for other quiz types or when not to use this tool, leaving a small gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
canvas_create_classic_quiz_questionADestructive
Add one question to an existing Canvas Classic Quiz in an approved course. Disabled by default and requires explicit confirmation.
| Name | Required | Description | Default |
|---|---|---|---|
| answers | No | ||
| quiz_id | Yes | ||
| course_id | Yes | ||
| confirmation | Yes | ||
| question_name | Yes | ||
| question_text | Yes | ||
| question_type | Yes | ||
| points_possible | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate destructiveHint: true, but the description adds crucial context by stating 'Disabled by default and requires explicit confirmation', which explains the need for a confirmation parameter. The mention of 'approved course' also signals authorization requirements, going beyond the annotation hints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, dense sentence that conveys the core purpose and key constraints without waste. Every phrase adds value: 'Add one question', 'existing', 'approved course', and 'disabled by default' all contribute essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 8 parameters (6 required) and no output schema, this description is far too brief to provide adequate context. It fails to explain any parameter semantics beyond confirmation, the behavior of question_type enum, or what happens on success/failure, leaving the agent without sufficient guidance for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides almost no parameter details. It only vaguely references 'explicit confirmation' (mapping to the confirmation parameter) and 'existing Canvas Classic Quiz' (implying quiz_id), but the other six required parameters (course_id, question_name, question_text, question_type, etc.) are left entirely to the schema, which lacks descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Add one question to an existing Canvas Classic Quiz in an approved course', specifying the verb (Add), resource (question), and target (existing quiz). This distinguishes it from siblings like canvas_create_classic_quiz, which creates a quiz, and other create_* tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'to an existing Canvas Classic Quiz' provides clear context for when to use this tool (for adding questions to quizzes that already exist). It does not explicitly name alternatives or exclusions, but the 'existing' qualifier implies not for creating quizzes, which is handled by a sibling.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
canvas_create_discussionADestructive
Create exactly one Canvas discussion in an approved course. Disabled by default and requires explicit confirmation.
| Name | Required | Description | Default |
|---|---|---|---|
| title | Yes | ||
| message | Yes | ||
| course_id | Yes | ||
| published | No | ||
| confirmation | Yes | ||
| discussion_type | No | threaded |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool as non-read-only and destructive, but the description adds that it is 'disabled by default' and 'requires explicit confirmation,' which are important behavioral constraints beyond the schema. This helps the agent understand prerequisites and that the tool will not execute without explicit user confirmation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only two sentences, front-loading the primary purpose and immediately adding a critical constraint. Every word earns its place with no unnecessary detail, making it highly efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description does not explain return values or error behavior. It also leaves the 'confirmation' parameter value unspecified and does not clarify what 'approved course' means operationally. However, it does disclose the most critical gating (approval and confirmation), making it minimally adequate for a simple creation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage for all parameters, and the description only adds meaning to the 'confirmation' parameter by indicating it must be explicitly provided. It does not explain expected values for confirmation or clarify the semantics of title, message, course_id, published, or discussion_type, so it fails to compensate for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Create exactly one Canvas discussion in an approved course,' identifying the verb (create), resource (discussion), and scope (approved course). This distinguishes it from sibling tools that create modules, assignments, or quizzes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context by noting the tool requires an 'approved course' and 'explicit confirmation,' setting prerequisites and conditions for use. However, it does not explicitly mention when to use this tool over alternatives or exclude other creation tools, so it lacks explicit usage comparisons.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
canvas_create_moduleADestructive
Create exactly one Canvas module in an approved course. Disabled by default and requires explicit confirmation.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| position | No | ||
| course_id | Yes | ||
| published | No | ||
| confirmation | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=false and destructiveHint=true, so the tool is known to be mutating. The description adds valuable context: it is 'disabled by default' and requires 'explicit confirmation', explaining why it might be unavailable. This goes beyond the annotations without contradicting them.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is direct and free of fluff. It front-loads the verb and resource, and every word adds meaning. No redundancy or unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 5 parameters, 3 required, and no output schema, so the description needs to cover return behavior, parameter details, and error states. It provides only minimal context (approved course, confirmation) and omits crucial information like success/failure behavior, response format, and implications of the position/published flags. This is insufficient for a create operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for documenting parameters. It only mentions 'explicit confirmation' (mapping to the confirmation parameter) and 'approved course' (vaguely relating to course_id), but does not explain name, position, published, or the format of confirmation. The description fails to provide essential parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool creates exactly one Canvas module, using a specific verb ('create') and resource ('module'). This distinguishes it from sibling tools like canvas_create_module_item, which creates items within a module. The phrase 'in an approved course' adds scope, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions prerequisites ('approved course') and a requirement for 'explicit confirmation', which implies the tool is for special cases and not a default action. However, it does not explicitly contrast with alternative tools (e.g., canvas_create_module_item) or state when not to use it. This is clear context but lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
canvas_create_module_itemADestructive
Add one existing Canvas content item or external URL to an existing module in an approved course. Disabled by default and requires explicit confirmation.
| Name | Required | Description | Default |
|---|---|---|---|
| type | Yes | ||
| title | Yes | ||
| new_tab | No | ||
| page_url | No | ||
| position | No | ||
| course_id | Yes | ||
| module_id | Yes | ||
| content_id | No | ||
| confirmation | Yes | ||
| external_url | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate a destructive, non-read-only operation. The description adds valuable context beyond annotations by specifying it is 'Disabled by default' and 'requires explicit confirmation', which are crucial behavioral traits. It also mentions the prerequisite of an approved course. This goes beyond simply restating the safety profile.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loaded with the core purpose and containing no redundant information. It efficiently communicates the key action and the critical confirmation requirement.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 10 parameters and no output schema, the description is too brief to be complete. It omits return value expectations, error conditions, or side effects beyond the destructive hint. It does not explain conditional parameter relationships (e.g., external_url vs content_id) or behavior when adding duplicates.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does 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 hints at the type parameter (content item vs external URL) and emphasizes the confirmation parameter. However, it does not clarify other parameters like position, new_tab, or page_url, leaving many fields semantically unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: adding an existing Canvas content item or external URL to a module. It uses a specific verb ('Add') and resource ('module item'), and distinguishes from siblings like canvas_create_module by emphasizing the item already exists.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (for existing content items) but does not explicitly state when not to use it or name alternatives. It gives context about needing an approved course and explicit confirmation, but lacks explicit guidance on choosing between this and sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
canvas_get_current_userARead-only
Read the authenticated Canvas user's profile. Read-only.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description repeats the readOnlyHint annotation by saying 'Read-only' but adds useful context by specifying 'authenticated user' scope. It does not disclose error handling, rate limits, or response format, which is acceptable given the annotation and simplicity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences with no filler. It states the action and the read-only nature directly and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, read-only tool, the description is sufficient for basic understanding. It doesn't describe the return payload, but the simplicity and annotations compensate. A brief mention of returned fields would make it complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters, so schema coverage is 100% vacuously. Per the guidelines, a zero-parameter tool gets a baseline of 4, and the description adds no unnecessary parameter information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Read the authenticated Canvas user's profile' with a specific verb (read) and resource (authenticated user's profile). It distinguishes from sibling write tools like canvas_create_module or canvas_write_page.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended usage is implied by the name and description – if you need the current user's profile, this is the tool. However, no explicit alternatives or exclusions are given, and it doesn't differentiate from canvas_read_api which could also be used for reading.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
canvas_get_write_policyARead-only
Show write-policy state and approved course IDs. Does not expose credentials.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, and the description adds value by noting 'Does not expose credentials' and specifying the exact data returned. This goes beyond the annotation, providing safety context about what information is included or excluded.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loaded with the core function and a useful safety note. Every word earns its place, and there is no redundant or ambiguous wording.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a no-parameter, read-only getter without an output schema, the description fully covers what the tool does and what it returns. The additional credential-safety note adds helpful context, leaving no meaningful gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema fully covers the input structure. Since no parameters exist, the description need not explain parameter semantics; the baseline of 4 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: showing write-policy state and approved course IDs. It uses a specific verb ('Show') and resource ('write-policy state'), distinguishing it from sibling tools that handle users, modules, or page operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. The description does not mention prerequisites, exclusions, or compare with sibling tools like canvas_read_api or canvas_get_current_user, leaving the agent without explicit usage boundaries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
canvas_list_modulesARead-only
List modules and module items for one Canvas course. Read-only.
| Name | Required | Description | Default |
|---|---|---|---|
| course_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description reiterates 'Read-only,' adding little beyond that. It does add the scoping detail 'for one Canvas course,' which implies course_id targets a single course. However, it does not disclose behaviors like pagination, ordering, or what exactly is returned for modules/items. With annotations covering the safety profile, a score of 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences immediately state the action and scope, and then note read-only behavior. No filler or redundancy. The information is front-loaded and every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, read-only annotation, no output schema), the description covers the essential purpose, scope, and safety. It tells the agent it will get modules and module items for a single course. It lacks return format or pagination details, but for this level of complexity, the description is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one required parameter (course_id) with 0% description coverage. The description adds some meaning by stating 'for one Canvas course,' clarifying that course_id identifies the course and that the tool is scoped to a single course. It also indicates the output will include modules and module items. Yet it does not elaborate on parameter format or constraints beyond what the parameter name and schema already imply.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'List' with a clear resource ('modules and module items') and scope ('one Canvas course'). This clearly distinguishes it from sibling creation tools like canvas_create_module and canvas_create_module_item, as well as from the more general canvas_read_api.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (i.e., when you need to list modules/items for a course), and the 'Read-only' note hints it is safe for inspection. However, it does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or contrast with sibling tools. The guidance is largely implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
canvas_read_apiBRead-only
Read one Canvas REST API v1 path with GET. Cannot make changes.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | ||
| query | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description reinforces this with 'Cannot make changes.' It adds the HTTP method (GET) and scope (one path), but does not disclose other behaviors like error handling, rate limits, or response format. With the annotation covering safety, this is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the core purpose, and every word earns its place. 'Read one Canvas REST API v1 path with GET. Cannot make changes.' is maximally concise and structurally clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is a generic reader with no output schema, so more context would help, such as mention of arbitrary path coverage or usage hints. The description is adequate for a simple read tool, but it leaves open questions about the query parameter and response shape, making it only a baseline complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate, but it only mentions 'path' without explaining its format or the optional 'query' object. The schema provides a pattern for path, but the description adds no semantic meaning for either parameter, especially query.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reads one Canvas REST API v1 path using GET, which is a specific verb and resource. It also explicitly says 'Cannot make changes,' distinguishing it from write tools. This satisfies the purpose clarity requirement.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains what the tool does but gives no guidance on when to use it versus the specific sibling tools like canvas_get_current_user or canvas_list_modules. It does not mention alternatives or exclusions, so the agent receives no usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
canvas_write_pageADestructive
Create or update exactly one Canvas page. Disabled by default. Requires a local per-course allowlist, exact user confirmation, and approval of this write action in the MCP client. This is not generic Canvas write access.
| Name | Required | Description | Default |
|---|---|---|---|
| body | Yes | ||
| title | Yes | ||
| page_url | No | Existing Canvas page URL slug. Omit to create a page. | |
| course_id | Yes | ||
| published | No | ||
| confirmation | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds significant context beyond the annotations: disabled by default, requires a per-course allowlist, exact user confirmation, and MCP client approval. This goes beyond the simple destructiveHint to explain how the destructive operation is gated and controlled.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences front-load the purpose first, then constraints, then a clarifying statement. Each sentence conveys essential information with no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the purpose, scope, and safety prerequisites, which are the most critical aspects for a gated write tool. It does not elaborate on parameter semantics, but the schema provides some names and defaults, and 'exactly one' sets expectation for behavioral scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 17% (only page_url is described). The tool description does not explain the meaning of required parameters like confirmation, body, or course_id, and does not compensate for the low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb and resource: 'Create or update exactly one Canvas page.' It also adds scope ('exactly one') and explicitly distinguishes itself from generic write tools, which helps differentiate it from sibling write tools like canvas_create_module.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly indicates when to use this tool (for Canvas page creation/update) and explicitly excludes other write actions ('not generic Canvas write access'). It does not name specific alternatives, but the purpose and exclusions are unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
11 tool updates
v0.2.0- First observed
canvas_create_assignment - First observed
canvas_create_classic_quiz - First observed
canvas_create_classic_quiz_question - First observed
canvas_create_discussion - First observed
canvas_create_module - First observed
canvas_create_module_item - First observed
canvas_get_current_user - First observed
canvas_get_write_policy - First observed
canvas_list_modules - First observed
canvas_read_api - First observed
canvas_write_page
TDQS
Scored across 11 tools
Each tool targets a distinct Canvas resource and action: user info, module listing, generic API read, write policy, and specific create operations for pages, modules, module items, assignments, discussions, and quizzes. The quiz and quiz-question pair are clearly hierarchical, and the generic read tool is distinct from the specific list tool.
All tools use the 'canvas_' prefix followed by a verb_noun pattern (get_user, list_modules, create_assignment, etc.). Minor deviations include 'read_api' instead of 'get_api' and 'write_page' instead of 'create_page', but the overall pattern is predictable and consistent.
With 11 tools, the set is well-scoped for a Canvas LMS integration focused on reading course structure and creating content items. Each tool has a clear purpose, and the count falls comfortably in the ideal 3-15 range without feeling bloated.
The tool surface covers reading (user, modules, generic API), creation (pages, modules, module items, assignments, discussions, quizzes, quiz questions), and page updates, but lacks explicit update/delete operations for most created entities. The generic canvas_read_api provides a workaround for reads, but delete operations are entirely absent, leaving a noticeable lifecycle gap.
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