MCP Todoist
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation2/5
There is significant overlap and confusion between 'add-task-to-any-project' and 'add-task-to-project'—they appear to serve nearly identical purposes, with only subtle differences in wording that could easily lead to misselection. The other tools are more distinct but the core task-adding functionality is ambiguous.
Naming Consistency4/5The naming follows a consistent kebab-case pattern (e.g., 'add-task-to-any-project', 'get-projects') throughout all tools, which is predictable and readable. There are no deviations in style, though the specific verb choices could be more standardized.
Tool Count4/5With 5 tools, the count is reasonable for a Todoist integration, covering core operations like adding tasks and retrieving projects/tasks. It's slightly thin but manageable for basic functionality without feeling overloaded.
Completeness2/5The toolset has significant gaps for a Todoist domain: it lacks update or delete operations for tasks or projects, and there is no way to manage task completion or priorities. This incomplete coverage will likely cause agent failures in common workflows.
Average 3/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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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?
With no annotations provided, the description carries full burden of behavioral disclosure. It states this is an 'Add' operation (implying creation/mutation) but doesn't disclose any behavioral traits like authentication requirements, rate limits, error conditions, or what happens when adding tasks to different project types. The description is minimal and lacks operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single sentence with no wasted words. It's front-loaded with the core purpose and uses minimal language to convey the basic function. While perhaps too minimal, it achieves maximum efficiency in word count.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what happens after task creation, what the response looks like, error conditions, or how this differs from the similar sibling tool. The agent lacks necessary context to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both parameters clearly documented in the schema itself. The description doesn't add any meaningful parameter semantics beyond what's already in the schema - it doesn't explain format expectations, constraints, or usage patterns for the parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Add task') and target resource ('to a any Project in Todoist'), providing specific verb+resource combination. However, it doesn't distinguish this tool from its sibling 'add-task-to-project' - the only difference appears to be the word 'any' which doesn't clarify functional distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus the similar 'add-task-to-project' sibling tool. The description doesn't mention prerequisites, alternatives, or specific contexts for usage, leaving the agent to guess about tool selection.
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. While 'Add task' implies a write/mutation operation, the description doesn't disclose important behavioral traits: whether this requires authentication, what happens on success/failure, if there are rate limits, whether the task is immediately visible, or what the return value looks like. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just 7 words, front-loading the essential information ('Add task to a specific Project in Todoist') with zero wasted words. Every element serves a purpose, making it easy to parse quickly while still conveying the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a mutation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what happens after the task is added, what the response looks like, error conditions, or authentication requirements. The presence of sibling tools like 'add-task-to-any-project' creates ambiguity that the description doesn't resolve. For a tool that modifies data, more contextual information is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with both parameters well-documented in the schema itself. The description adds no additional parameter semantics beyond what's already in the schema - it doesn't explain format requirements, constraints, or provide examples. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, though the description contributes no extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Add task') and target resource ('to a specific Project in Todoist'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from the sibling tool 'add-task-to-any-project' - both appear to add tasks, so the distinction between 'specific Project' vs 'any project' isn't clarified in the description itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 explain the relationship with 'add-task-to-any-project' (which appears to be a similar tool), nor does it mention prerequisites like needing a project_id from 'get-project-id' or 'get-projects' first. There's no 'when-not' guidance or context about appropriate use cases.
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 but only states the basic function. It doesn't cover critical aspects like error handling (e.g., if the project doesn't exist), authentication requirements, or rate limits, leaving significant gaps 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and wastes no space, making it highly concise and well-structured for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given 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., a string ID or structured data), error scenarios, or integration with sibling tools, failing to provide enough context for effective use in this environment.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, documenting the 'name' parameter clearly. The description doesn't add extra semantic context beyond what the schema provides, such as format examples or constraints, so it meets the baseline for high schema coverage without enhancing parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('id of the project from Todoist'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'get-projects' which might return project lists rather than IDs, leaving room for ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'get-projects' or 'get-tasks'. The description lacks context about prerequisites, such as whether the project must exist or if authentication is needed, offering minimal usage direction.
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 but only states the basic action without behavioral details. It doesn't disclose whether this is a read-only operation, if it requires authentication, how results are returned (e.g., pagination, format), or any rate limits—critical gaps for a tool that fetches data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose with zero waste. Every word ('Get all the projects from Todoist') directly contributes to understanding the tool's function, making it optimally concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a data-fetching tool. It lacks details on return values (e.g., project fields, format), authentication needs, or error handling, leaving significant gaps despite the simple parameterless design.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't mention parameters, earning a baseline 4 for not adding unnecessary information beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('projects from Todoist'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get-project-id' or 'get-tasks', which would require more specificity about scope or output format to earn 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 Guidelines2/5Does 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-project-id' (for a single project) or 'get-tasks' (for tasks instead of projects). It lacks explicit when/when-not instructions or named alternatives, leaving usage context implied at best.
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 what the tool does but provides no information about permissions required, rate limits, pagination behavior, or what format the returned tasks will have. 'Get all the tasks' implies a read operation but lacks critical behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core purpose without any wasted words. It's appropriately sized for a simple retrieval tool and front-loads the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations, no output schema, and no parameters, the description is insufficiently complete. It doesn't address what 'all the tasks' means in practice (active only? completed? archived?), doesn't mention authentication requirements, and provides no information about the return format or structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does 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 fully documents the parameter situation. The description appropriately doesn't discuss parameters since none exist, earning a baseline score of 4 for not introducing confusion about non-existent parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('all the tasks from Todoist'), making the purpose immediately understandable. It doesn't explicitly distinguish from sibling tools like 'get-projects' or 'get-project-id', but the resource specificity (tasks vs projects) provides implicit differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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-projects' or 'add-task-to-project'. It doesn't mention prerequisites, limitations, or appropriate contexts for retrieving all tasks versus filtered subsets.
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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