eClass MCP Server
Servidor MCP eClass
Características
Autenticación : Inicie sesión en eClass a través del sistema de autenticación CAS SSO de UoA
Gestión de cursos : recuperar listas de cursos inscritos
Gestión de sesiones : mantener sesiones autenticadas entre llamadas de herramientas
Comprobación de estado : verificar el estado de autenticación
Related MCP server: mcpUPB
Estructura del proyecto
Este proyecto sigue una arquitectura modular para una mejor mantenibilidad:
eclass-mcp-server/
├── run_server.py # Entry point script for running the server
├── pyproject.toml # Project configuration and dependencies
├── .env # Environment variables (create from example.env)
├── src/
└── eclass_mcp_server/ # Main package
├── __init__.py # Package initialization
├── server.py # Core server implementation and tool handlers
├── authentication.py # Authentication functionality
├── course_management.py # Course-related functionality
├── html_parsing.py # HTML parsing utilities
└── test/ # Test scripts for functionality verification
├── __init__.py
├── test_login.py
├── test_courses.py
└── run_all_tests.pyInstalación
Instalar el servidor usando UV (recomendado):
# Clone the repository
git clone https://github.com/yourusername/eClass-MCP-server.git
cd eClass-MCP-server
# Install dependencies
uv sync --dev --all-extrasAlternativamente, instale con pip:
pip install -e .Configuración
Cree un archivo .env en el directorio raíz con la siguiente configuración (o copie y cambie el nombre del archivo example.env proporcionado):
ECLASS_URL=https://eclass.uoa.gr
ECLASS_USERNAME=your_username
ECLASS_PASSWORD=your_passwordTodas las credenciales deben proporcionarse en el archivo .env. El servidor no acepta credenciales como parámetros.
Uso
Terminal
Ejecute el servidor utilizando el script de punto de entrada:
python run_server.pyO como módulo:
python -m src.eclass_mcp_server.serverCursor
Vaya a Configuración -> MCP. Haga clic en Add new MCP server .
Seleccione un nombre único pero apropiado para que el Agente sepa para qué sirve el servidor (por ejemplo, "eClass Server")
Seleccione la opción
commanden “Tipo”Agregue esto en la entrada del comando:
python /path/to/eclass-mcp-server/run_server.py
Este comando ejecuta el script run_server.py que conecta el cliente MCP con el punto de entrada del servidor principal en server.py .
Escritorio de Claude
Para utilizar con Claude Desktop:
Abra Claude Desktop
Vaya a Configuración > Servidor
Agregue un nuevo servidor con los siguientes detalles:
Nombre: eClass MCP
Comando: Ruta a su script run_server.py
Haga clic en Agregar servidor
Selecciona el servidor del menú desplegable al chatear con Claude
Herramientas
El servidor proporciona las siguientes herramientas para su uso con clientes MCP:
acceso
Inicie sesión en eClass mediante la autenticación SSO.
{
"random_string": "any_value"
}obtener_cursos
Recuperar una lista de cursos inscritos (requiere iniciar sesión primero).
{
"random_string": "any_value"
}cerrar sesión
Cerrar sesión en eClass.
{
"random_string": "any_value"
}estado de autorización
Verifique el estado de autenticación actual.
{
"random_string": "any_value"
}Pruebas
El proyecto incluye scripts de prueba para verificar la funcionalidad:
# Run all tests
python -m src.eclass_mcp_server.test.run_all_tests
# Run specific tests
python -m src.eclass_mcp_server.test.test_login
python -m src.eclass_mcp_server.test.test_coursesEjemplo de uso del cliente MCP
from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client
import asyncio
async def run_agent():
server_params = StdioServerParameters(
command="python /path/to/eclass-mcp-server/run_server.py",
)
async with stdio_client(server_params) as (read, write):
async with ClientSession(read, write) as session:
# Initialize the session
await session.initialize()
# Login to eClass
login_result = await session.call_tool("login", {
"random_string": "dummy"
})
print(login_result)
# Get courses
courses_result = await session.call_tool("get_courses", {
"random_string": "dummy"
})
print(courses_result)
# Logout
logout_result = await session.call_tool("logout", {
"random_string": "dummy"
})
print(logout_result)
if __name__ == "__main__":
asyncio.run(run_agent())Integración con agentes de IA
Este servidor MCP está diseñado para usarse con agentes de IA compatibles con el Protocolo de Contexto de Modelo. Esto permite que los sistemas de IA interactúen directamente con eClass, lo que permite capacidades como:
Recuperando información del curso
Consulta de anuncios de cursos
Acceso a los materiales del curso
Envío de tareas (función futura)
Consideraciones de seguridad
El servidor maneja credenciales de autenticación confidenciales
Las credenciales solo se utilizan para la autenticación y no se almacenan de forma persistente.
Las cookies de sesión se mantienen en la memoria durante el ciclo de vida del servidor.
El servidor valida el estado de la sesión antes de realizar operaciones
El archivo
.envcon credenciales nunca debe enviarse al control de versiones (está incluido en .gitignore)
Licencia
Licencia MIT
Contribuyendo
¡Agradecemos sus contribuciones! No dude en enviar una solicitud de incorporación de cambios.
Available Tools
4 toolsauthstatusB
Check authentication status with eClass
| Name | Required | Description | Default |
|---|---|---|---|
| random_string | Yes | Dummy parameter for no-parameter tools |
TDQS
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 only states the purpose without disclosing behavioral traits such as whether it requires authentication, what the response format is, or any rate limits. For a tool with zero annotation coverage, this is inadequate.
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, clear sentence with no wasted words. It's appropriately sized and front-loaded, making it easy to understand immediately.
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 lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., success/failure, user details) or any behavioral context, which is necessary for an authentication-related tool with no structured data support.
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 description coverage is 100%, so the schema fully documents the single parameter. The description doesn't add any parameter information, which is acceptable since the schema handles it. With 0 parameters of real semantic weight (the parameter is a dummy), a baseline of 4 is appropriate.
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 purpose as 'Check authentication status with eClass', which is a specific verb ('Check') and resource ('authentication status') combination. It doesn't explicitly distinguish from siblings like 'login' or 'logout', but the purpose is 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?
No guidance is provided on when to use this tool versus alternatives like 'login' or 'logout'. The description states what it does but offers no context about when it should be invoked or what scenarios it addresses.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_coursesB
Get list of enrolled courses from eClass
| Name | Required | Description | Default |
|---|---|---|---|
| random_string | Yes | Dummy parameter for no-parameter tools |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions retrieving a list but doesn't specify whether this requires authentication, what format the list is in, if there are rate limits, or any error conditions. For a read operation with zero annotation coverage, this leaves significant gaps in understanding the tool's behavior.
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, efficient sentence with no wasted words. It's front-loaded with the core purpose ('Get list of enrolled courses from eClass'), making it easy to understand immediately. Every word earns its place without 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?
Given no annotations, no output schema, and a simple read operation, the description is incomplete. It lacks details on authentication requirements, return format, error handling, or any behavioral context. For a tool that likely interacts with an eClass system, this leaves too many unknowns for effective agent use.
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 input schema has one parameter (random_string) with 100% description coverage, indicating it's a dummy parameter for no-parameter tools. The description doesn't add any parameter details beyond the schema, but since this is effectively a zero-parameter tool (with a dummy parameter), the baseline is 4 as it doesn't need to compensate for schema 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 the action ('Get list') and target resource ('enrolled courses from eClass'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools (authstatus, login, logout) which are unrelated authentication tools, so this distinction isn't needed but the purpose remains clear.
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 no guidance on when to use this tool versus alternatives. While the sibling tools are unrelated (authentication vs. data retrieval), there's no explicit mention of prerequisites like needing to be logged in or any context for usage. It simply states what it does without usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
loginB
Log in to eClass using username/password from your .env file through UoA's SSO. Configure ECLASS_USERNAME and ECLASS_PASSWORD in your .env file.
| Name | Required | Description | Default |
|---|---|---|---|
| random_string | Yes | Dummy parameter for no-parameter tools |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions authentication via SSO and .env file usage, but lacks details on what the tool actually does (e.g., establishes a session, returns tokens, handles errors) or behavioral traits like rate limits, side effects, or response format. For a login tool with zero annotation coverage, this is a significant gap.
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 that efficiently convey the core functionality and configuration requirement. It's front-loaded with the main action and wastes no words, making it easy to parse quickly.
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 complexity of a login operation (authentication, session management) with no annotations and no output schema, the description is incomplete. It doesn't explain what happens after login (e.g., session persistence, return values, error handling), leaving gaps in understanding the tool's behavior and outcomes.
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 input schema has 1 parameter with 100% coverage, describing it as a 'Dummy parameter for no-parameter tools.' The description doesn't add any parameter-specific information, which is appropriate since the tool likely doesn't require user-provided inputs. With high schema coverage and no meaningful parameters, a baseline of 4 is justified as the description doesn't need to compensate.
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 purpose: 'Log in to eClass using username/password from your .env file through UoA's SSO.' It specifies the action (log in), target system (eClass), and authentication method (SSO with .env credentials). However, it doesn't explicitly differentiate from sibling tools like 'authstatus' or 'logout' beyond the obvious login/logout distinction.
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 context: it should be used to authenticate with eClass via SSO when credentials are stored in .env. However, it doesn't provide explicit guidance on when to use this vs. alternatives like 'authstatus' (which might check login state) or prerequisites beyond .env configuration. The guidance is somewhat implied but not comprehensive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
logoutB
Log out from eClass
| Name | Required | Description | Default |
|---|---|---|---|
| random_string | Yes | Dummy parameter for no-parameter tools |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'Log out' implies session termination, it doesn't specify what gets invalidated, whether this affects other tools, if re-authentication is required afterward, or what happens on failure. The description lacks important behavioral context for a security-sensitive operation.
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 maximally concise with just three words that directly convey the tool's purpose. There's zero waste or unnecessary elaboration, and it's perfectly front-loaded with the 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?
For a security operation like logout with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after logout, whether the operation can fail, what state changes occur, or how this affects subsequent tool calls. The minimal description leaves critical behavioral questions unanswered.
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 input schema has 100% description coverage, with the single parameter clearly documented as a 'Dummy parameter for no-parameter tools.' The description doesn't need to add parameter semantics since the tool conceptually requires no real parameters, and the schema adequately explains the dummy parameter requirement.
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 ('Log out') and target system ('from eClass'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'login' or 'authstatus' beyond the obvious action difference.
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 no guidance on when to use this tool versus alternatives like 'authstatus' to check login state, or whether logout should follow certain workflows. It simply states what the tool does without context about appropriate usage scenarios.
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.
4 tool updates
- First observed
authstatus - First observed
get_courses - First observed
login - First observed
logout
TDQS
Scored across 4 tools
Each tool has a distinct purpose with no overlap: authstatus checks authentication state, get_courses retrieves course data, login handles authentication, and logout terminates sessions. The descriptions clearly differentiate these functions, making tool selection straightforward for an agent.
Three tools follow a consistent verb_noun pattern (get_courses, login, logout), while authstatus uses a compound noun. This minor deviation slightly reduces consistency, but the naming remains readable and intuitive overall.
Four tools are reasonable for an eClass server focused on authentication and basic course access. It covers core authentication workflows and data retrieval, though it could be slightly expanded for a more comprehensive eClass integration.
The tools cover authentication and course listing well, but there are notable gaps for typical eClass functionality such as accessing course content, assignments, grades, or announcements. This limits the server's ability to support full eClass workflows.
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