Moodle MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes targeting different Moodle resources like assignments, quizzes, students, and submissions, but get_submissions and get_submission_content could be slightly confusing as the latter seems like a more detailed version of the former. The descriptions clarify the difference, but some overlap exists.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using snake_case, starting with 'get_' for retrieval operations and 'provide_' for feedback. This uniformity makes the set predictable and easy to navigate for an agent.
Tool Count4/5
With 7 tools, the count is reasonable for a Moodle server focused on course management tasks. It covers core operations like retrieving assignments, quizzes, students, and submissions, though it might be slightly thin if more advanced features like creating or updating resources are expected.
Completeness3/5
The server provides good read-only coverage for viewing course elements and feedback, but lacks create, update, or delete operations for resources like assignments or quizzes. This creates notable gaps in CRUD functionality, which could limit agent workflows in a full course management context.
Average 3/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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- No high-severity vulnerability alerts
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'obtiene' implies a read-only operation, it doesn't specify authentication requirements, error conditions (e.g., invalid IDs), rate limits, or what happens if no grade exists. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Spanish that directly states the tool's purpose. It's front-loaded with the core action and resource, with no unnecessary words or redundancy. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 insufficiently complete. It doesn't explain what the return value looks like (e.g., numeric grade, letter grade, or structured object), error handling, or any side effects. For a grade retrieval tool, this leaves too much ambiguity for an AI 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 description coverage is 100%, with both parameters clearly documented in the schema. The description doesn't add any parameter-specific details beyond what's in the schema (e.g., format constraints or examples). Baseline 3 is appropriate when the schema fully documents parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('obtiene' - gets/retrieves) and the target resource ('calificación de un estudiante en un quiz específico' - a student's grade on a specific quiz). It distinguishes from siblings like 'get_assignments' or 'get_quizzes' by focusing on grade retrieval rather than lists of resources. However, it doesn't explicitly mention that this is for a single student-quiz pair versus bulk operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention prerequisites (e.g., whether the student must be enrolled or the quiz must be completed), nor does it suggest when to use siblings like 'get_submissions' or 'provide_feedback' instead. Usage is implied by the name but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 of behavioral disclosure. It states the action ('Proporciona feedback') but doesn't clarify if this is a read-only operation, a mutation that updates records, requires specific permissions, has side effects like notifications, or what the response entails. For a tool with four parameters and no annotations, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Spanish that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to understand at a glance, with zero waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a tool with four parameters (including a numeric grade and text feedback), no annotations, and no output schema, the description is incomplete. It doesn't explain the tool's behavior, return values, or how it interacts with siblings, leaving significant gaps for an AI agent to understand its full context and usage.
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 schema already documents all four parameters (studentId, assignmentId, grade, feedback) with descriptions. The tool description doesn't add any additional meaning or context beyond what the schema provides, such as explaining relationships between parameters or usage examples. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Proporciona feedback') and the target resource ('sobre una tarea entregada por un estudiante'), making the purpose understandable. However, it doesn't distinguish this tool from potential siblings like 'get_submissions' or 'get_quiz_grade', which might also involve student work assessment, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With siblings like 'get_submissions' and 'get_quiz_grade' that might retrieve or assess student work, there's no indication of whether this tool is for grading, commenting, or a specific feedback workflow, leaving usage ambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a read operation ('obtiene' = 'gets'), but doesn't describe what 'configured course' means, whether this requires authentication, what format the list returns, or any limitations like pagination or rate limits. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Spanish that directly states the tool's purpose. It's appropriately sized for a simple list-retrieval tool with no parameters. While front-loaded, it could potentially benefit from slightly more structure if behavioral details were needed.
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's simplicity (zero parameters, no output schema, no annotations), the description is minimally adequate but has clear gaps. It explains what the tool does but doesn't provide enough context about the 'configured course' prerequisite, return format, or how this differs from similar sibling tools. For a read-only list tool, it meets basic requirements but lacks completeness.
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 tool has zero parameters with 100% schema description coverage, so the schema already fully documents the parameter situation. The description appropriately doesn't add parameter information beyond what's in the schema, which is correct for a zero-parameter tool. Baseline for zero parameters is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('obtiene la lista de' = 'gets the list of') and resource ('tareas asignadas en el curso configurado' = 'assigned tasks in the configured course'), providing a specific verb+resource combination. It doesn't explicitly differentiate from sibling tools like get_quizzes or get_submissions, but the resource specificity ('assigned tasks') provides some implicit distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 get_quizzes or get_submissions. It mentions 'in the configured course' which implies a prerequisite course configuration, but offers no explicit when/when-not instructions or comparison with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. It states this is a retrieval operation ('obtiene'), implying read-only behavior, but doesn't specify whether it requires authentication, returns paginated results, has rate limits, or what format the list returns. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Spanish that directly states the tool's purpose. It's front-loaded with the core action and resource, with no redundant words or unnecessary elaboration. Every word earns its place in conveying the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema), the description is minimally adequate but incomplete. It doesn't explain what 'curso configurado' means (e.g., is this a pre-configured context or requires prior setup?), what the returned list contains, or any error conditions. For a tool with no annotations or output schema, more contextual detail would be helpful.
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 tool has zero parameters, and schema description coverage is 100% (since there are no parameters to describe). The description correctly indicates no parameters are needed by not mentioning any. With 0 parameters, the baseline is 4, as there's nothing additional to explain beyond what the empty schema already shows.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('obtiene' - gets/retrieves) and the resource ('lista de quizzes en el curso configurado' - list of quizzes in the configured course). It distinguishes from siblings like 'get_assignments' and 'get_quiz_grade' by specifying quizzes rather than assignments or grades. However, it doesn't explicitly differentiate from other list operations beyond the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention prerequisites (like needing a configured course), when not to use it, or how it differs from similar tools like 'get_assignments' or 'get_submissions' beyond the resource type. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 of behavioral disclosure. The description only states what the tool does ('obtiene la lista'), without detailing behavioral traits such as whether it requires authentication, has rate limits, returns paginated results, or handles errors. For a read operation with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence: 'Obtiene la lista de estudiantes inscritos en el curso configurado'. It is front-loaded with the main purpose and has no unnecessary words. However, it could be slightly more concise by omitting 'configurado' if implied, but overall it is efficient and well-structured.
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's simplicity (0 parameters, no output schema, no annotations), the description is minimally complete. It states the basic purpose but lacks details on behavior, usage context, or output format. For a read-only list tool with no structured data support, this is adequate but leaves clear gaps, such as not explaining what the returned list contains or how it's formatted.
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 0 parameters with 100% coverage, meaning no parameters are documented in the schema. The description does not mention any parameters, which is appropriate here. Since there are no parameters, the baseline score is 4, as the description does not need to compensate for missing parameter info.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Obtiene la lista de estudiantes inscritos en el curso configurado' (Gets the list of students enrolled in the configured course). It specifies the verb 'obtiene' (gets) and the resource 'estudiantes inscritos en el curso configurado' (students enrolled in the configured course). However, it does not explicitly differentiate from sibling tools like 'get_assignments' or 'get_submissions', which lowers the score from a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It does not mention any context, prerequisites, or exclusions. For example, it does not clarify if this is for retrieving all students versus filtered subsets, or how it relates to sibling tools like 'get_submissions' that might involve student data. This lack of usage guidance results in a low score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 of behavioral disclosure. It states the tool retrieves detailed content, implying a read-only operation, but doesn't specify whether it requires authentication, has rate limits, returns paginated results, or what happens if the submission doesn't exist. For a tool with no annotation coverage, this lack of behavioral details is a significant gap, though it doesn't contradict any annotations.
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 a single, efficient sentence in Spanish that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and includes key details (text and attachments). Every part of the sentence earns its place by clarifying the scope of retrieval.
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's complexity (a read operation with 2 parameters), no annotations, and no output schema, the description is minimally adequate. It covers the basic purpose and what content is retrieved, but lacks behavioral details (e.g., error handling, return format) and usage guidelines. For a tool with no structured output or annotations, it should do more to be fully complete, but it meets the minimum viable threshold.
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 description coverage is 100%, with both parameters (studentId and assignmentId) clearly documented in the schema. The description doesn't add any parameter-specific information beyond what's in the schema, such as format examples or constraints. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Obtiene el contenido detallado de una entrega específica, incluyendo texto y archivos adjuntos' (Gets the detailed content of a specific submission, including text and attached files). It specifies the verb (obtiene/gets) and resource (contenido detallado de una entrega/detailed content of a submission), and distinguishes itself from siblings like 'get_submissions' (which likely lists submissions) by focusing on detailed content retrieval. However, it doesn't explicitly contrast with other siblings, so it's not a perfect 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention when to choose it over 'get_submissions' (which might list submissions without details) or other sibling tools like 'get_assignments' or 'get_students'. There's no context about prerequisites, such as needing to identify a specific submission first. The usage is implied from the purpose but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'obtiene' implies a read operation, it doesn't specify whether this requires authentication, what permissions are needed, whether results are paginated, what format the returns take, or any rate limits. For a read tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient Spanish sentence that directly states the tool's purpose. There's zero waste - every word contributes to understanding what the tool does. It's appropriately sized for a simple retrieval tool and front-loads the core functionality.
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?
For a simple read operation with 2 optional parameters and 100% schema coverage, the description is minimally adequate. However, with no annotations and no output schema, it should ideally provide more behavioral context about what gets returned (list of submissions? with what fields?) and any authentication requirements. The description covers the basic 'what' but not the 'how' or 'what comes back'.
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 schema already documents both parameters (studentId and assignmentId) with their optional nature and behavior. The description doesn't add any parameter semantics beyond what's in the schema - it doesn't explain parameter interactions, format requirements, or provide examples. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('obtiene' - gets/retrieves) and resource ('entregas de tareas' - task submissions) with scope ('en el curso configurado' - in the configured course). It distinguishes from siblings like get_assignments (which gets assignments rather than submissions) and get_submission_content (which gets content of specific submissions rather than submissions list). However, it doesn't explicitly contrast with all siblings like get_quiz_grade.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention when to use get_submissions versus get_submission_content (for content of specific submissions) or get_quiz_grade (for quiz grades specifically). There's no discussion of prerequisites, timing considerations, or exclusions for this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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