MCP Todo
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: add_todo creates items, list_todos retrieves them, remove_todo deletes by ID, and toggle_todo updates completion status. The actions (add, list, remove, toggle) and targets (todos) are unambiguous, making tool selection straightforward for an agent.
Naming Consistency5/5All tools follow a consistent verb_noun pattern with snake_case naming: add_todo, list_todos, remove_todo, toggle_todo. The verbs are descriptive and aligned with CRUD operations, and the noun 'todo' is used consistently across all tools, providing a predictable and readable naming convention.
Tool Count5/5With 4 tools, this server is well-scoped for a todo management domain. Each tool serves a distinct and essential function (create, read, update, delete), and there are no extraneous or missing tools. The count is appropriate for the simple but complete coverage of todo operations.
Completeness5/5The tool set provides complete CRUD/lifecycle coverage for todo management: add_todo for creation, list_todos for retrieval, remove_todo for deletion, and toggle_todo for updating completion status. There are no obvious gaps, and agents can perform all core operations without dead ends.
Average 2.8/5 across 4 of 4 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?
No annotations are provided, so the description carries full burden. 'Add a todo item' implies a write operation, but it doesn't disclose behavioral traits such as permissions needed, whether it's idempotent, error handling, or what happens on success (e.g., returns an ID). For a mutation tool 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence, 'Add a todo item', which is front-loaded and wastes no words. It's appropriately sized for a simple tool, though this brevity contributes to gaps in other dimensions.
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 tool's complexity (a write operation with 1 parameter), lack of annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't cover behavioral aspects, parameter details, or return values, making it inadequate for effective agent use without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter with 0% description coverage, and the description adds no meaning beyond the schema. It doesn't explain what 'title' represents (e.g., the todo's name or content), its format, or constraints. With low schema coverage, the description fails to compensate, leaving the parameter's semantics unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Add a todo item' clearly states the action (add) and resource (todo item), which is adequate. However, it doesn't differentiate from sibling tools like 'list_todos' or 'remove_todo' beyond the basic verb, making it vague in comparison. It's not tautological but lacks specificity about what 'add' entails versus other operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'list_todos' or 'toggle_todo'. It doesn't mention prerequisites, context, or exclusions. While the verb 'add' implies creation, it fails to specify scenarios or constraints, leaving usage unclear relative to siblings.
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 full burden. It mentions 'toggle' but doesn't disclose behavioral traits such as what 'toggle' does (e.g., changes completion status), whether it's idempotent, or any side effects. This leaves critical gaps for a mutation tool.
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 zero waste. It's front-loaded and efficiently states the core action, though this brevity contributes to gaps in other dimensions.
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 tool's complexity (a mutation with no annotations, 0% schema coverage, and no output schema), the description is incomplete. It lacks details on behavior, parameter meaning, and expected outcomes, making it inadequate for reliable agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, with one parameter 'id' undocumented in the schema. The description adds minimal semantics by specifying 'by id', but doesn't explain the parameter's role (e.g., unique identifier) or constraints beyond what's implied, failing to compensate for the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action ('toggle') and target ('todo by id'), which is clear but minimal. It doesn't distinguish from siblings like 'add_todo' or 'remove_todo' beyond the verb, leaving ambiguity about what 'toggle' specifically does (e.g., mark complete/incomplete).
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 on when to use this tool versus alternatives like 'remove_todo' or how it relates to 'list_todos'. It implies usage for toggling a todo's state but lacks context on prerequisites (e.g., existing todo ID) or exclusions.
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 implies a destructive operation ('Remove'), but doesn't specify if deletion is permanent, reversible, requires specific permissions, or has side effects (e.g., affecting related data). For a mutation tool 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence that front-loads the core action. There is zero waste or redundancy, making it efficient for quick understanding, though this brevity contributes to gaps in other dimensions.
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 a destructive tool with no annotations, no output schema, and incomplete parameter documentation, the description is inadequate. It doesn't cover behavioral traits, return values, or error conditions, leaving the agent with insufficient context to use the tool safely and effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, and the description adds no meaning beyond the schema's basic type constraints. It mentions 'id' but doesn't explain what this ID represents (e.g., from 'list_todos'), its format, or valid ranges beyond the schema's 'exclusiveMinimum: 0'. With 1 undocumented parameter, the description fails to compensate for the coverage gap.
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 ('Remove') and resource ('a todo by id'), making the purpose immediately understandable. It distinguishes from siblings like 'add_todo' and 'list_todos' by specifying deletion rather than creation or listing. However, it doesn't explicitly differentiate from 'toggle_todo' which also modifies todos, keeping it from a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'toggle_todo' (which might mark as done instead of deleting) or prerequisites such as needing an existing todo ID. The description only states what it does, not when it's appropriate, leaving the agent to infer usage from context.
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, the description carries full burden but only states the basic action. It does not disclose behavioral traits such as whether it returns all todos at once or paginates, if it requires authentication, rate limits, or error handling. This leaves significant gaps for a tool that likely interacts with 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 with zero waste. It is front-loaded, directly stating the purpose without unnecessary details. Every word earns its place, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, output schema exists), the description is minimally adequate. However, with no annotations and siblings implying data operations, it should ideally mention safety (e.g., read-only) or constraints. The output schema helps, but the description lacks context for usage in a todo management system.
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 adds value by specifying 'all todos' and 'structured format', which clarifies scope and output beyond the schema. Baseline is high due to no parameters, but it compensates with useful context.
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 ('Return') and resource ('all todos'), specifying the output format ('structured format'). It distinguishes from siblings like add_todo or remove_todo by focusing on retrieval rather than modification. However, it lacks explicit sibling differentiation, such as noting this is for unfiltered listing versus other query options.
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. It does not mention prerequisites, context (e.g., after adding todos), or exclusions (e.g., for filtered views). The agent must infer usage from the name and siblings alone, which is insufficient for clear decision-making.
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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