MCPatterns

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes, but 'open_patterns' and 'read_patterns' could cause confusion as both involve accessing patterns, with 'open' being less clear about its specific function compared to 'read' for retrieval. The other tools clearly target different operations like creation, deletion, addition, and search.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using snake_case, such as 'add_code_examples', 'create_patterns', and 'search_patterns'. This uniformity makes the tool set predictable and easy to understand at a glance.
Tool Count5/5
With 7 tools, the count is well-scoped for managing coding patterns, covering core operations like create, read, search, delete, and example management. Each tool appears to serve a necessary function without being excessive or insufficient for the domain.
Completeness4/5
The tool set provides good coverage for CRUD operations on patterns and code examples, including create, read, search, and delete. However, there is a minor gap in update functionality for patterns or examples, which might require workarounds, though the domain is still largely covered.
Average 2.9/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 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 the full burden of behavioral disclosure. While 'Create multiple new' implies a write operation, it doesn't address permissions needed, whether this is idempotent, what happens on partial failures, or how conflicts with existing patterns are handled. The description lacks crucial behavioral context for a database 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core purpose without unnecessary words. It's appropriately front-loaded with the main action and scope, making it easy to parse quickly.
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?
For a database mutation tool with 6 required nested properties, no annotations, no output schema, and 0% schema description coverage, this description is inadequate. It doesn't explain what happens after creation, how to handle errors, or provide any context about the pattern structure beyond what's minimally implied by the tool name.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the 6 nested properties within the 'patterns' array have descriptions in the schema. The description adds no parameter information beyond the name 'patterns' - it doesn't explain what constitutes a valid pattern, required fields, or format expectations. This fails to compensate for the complete lack of schema documentation.
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 ('Create multiple new coding patterns') and resource ('in the database'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'add_code_examples' or 'open_patterns' which might have overlapping functionality.
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 'add_code_examples' or 'read_patterns'. There's no mention of prerequisites, constraints, or appropriate contexts for bulk creation versus individual operations.
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 implies a retrieval or access operation ('open'), but doesn't disclose behavioral traits such as required permissions, whether it's read-only or mutative, error handling, or output format. This leaves critical gaps for safe and effective use.
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 with zero waste. It is appropriately sized and front-loaded, directly stating the tool's action without unnecessary elaboration, making it easy to parse quickly.
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 no annotations and no output schema, the description is incomplete for a tool with one required parameter. It fails to explain what 'open' entails operationally, what is returned, or how it differs from siblings, leaving the agent with insufficient context for reliable invocation.
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%, with the parameter 'names' documented as 'An array of pattern names to retrieve'. The description adds minimal value beyond this, merely restating 'by their names' without clarifying syntax, constraints, or usage examples. Baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Open specific patterns by their names' states a verb ('open') and resource ('patterns'), but is vague about what 'open' means operationally. It doesn't distinguish from siblings like 'read_patterns' or 'search_patterns', leaving ambiguity about whether this retrieves, displays, or activates patterns.
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?
No guidance is provided on when to use this tool versus alternatives. With siblings like 'read_patterns' and 'search_patterns' available, the description lacks explicit context, prerequisites, or exclusions, offering only a basic directive without comparative utility.
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 deletion action without disclosing behavioral traits. It doesn't mention whether deletions are permanent, require specific permissions, have rate limits, or what happens if examples don't exist, leaving significant gaps for a destructive operation.
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 with zero wasted words, making it appropriately sized and front-loaded. Every word contributes directly to stating the tool's purpose.
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?
For a destructive tool with no annotations, 0% schema coverage, and no output schema, the description is incomplete. It lacks details on behavior, parameters, error handling, and output, making it inadequate for safe and effective use by an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 adds no parameter information beyond the tool name. It doesn't explain what 'deletions' array contains, how 'patternName' and 'languages' interact, or provide examples, failing to address the undocumented 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 ('Delete') and target resource ('specific code examples from patterns'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'delete_patterns' which deletes entire patterns rather than just examples, missing full sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'delete_patterns' or 'add_code_examples'. The description lacks context about prerequisites, such as whether patterns must exist first, or exclusions like bulk operations.
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 'Add new code examples' which implies a write/mutation operation, but doesn't cover permissions, side effects, error handling, or response format. For a tool that modifies data without annotation coverage, this leaves significant behavioral gaps unaddressed.
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 with no wasted words. It's front-loaded with the core action and resource, making it immediately understandable. Every word earns its place in conveying the essential purpose.
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 complexity (modifying existing patterns with structured inputs), lack of annotations, no output schema, and 0% schema description coverage, the description is insufficient. It doesn't explain what happens on success/failure, how examples are merged, or provide any context about the system's patterns and examples model.
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 0%, so the description must compensate. It mentions 'code examples' and 'patterns' which aligns with the 'additions' parameter structure, but doesn't explain the semantics of 'patternName' or how 'examples' should be structured (e.g., language-keyed strings). The description adds minimal context beyond the schema's property names.
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 ('Add new code examples') and target resource ('to existing patterns'), which is specific and unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'create_patterns' or 'delete_code_examples', which would require more precise language about scope and relationship to those 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 like 'create_patterns' (for new patterns) or 'delete_code_examples'. It mentions 'existing patterns' which implies a prerequisite but doesn't state it explicitly, and offers no context about appropriate scenarios 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 states the tool deletes patterns, implying a destructive mutation, but doesn't clarify if deletions are permanent, reversible, require specific permissions, or have side effects like cascading deletions. This leaves significant gaps for a destructive operation.
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, direct sentence with zero wasted words. It front-loads the key action ('Delete') and resource ('multiple patterns'), making it efficient and easy to parse, though it could benefit from more detail given the tool's destructive nature.
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?
For a destructive tool with no annotations and no output schema, the description is incomplete. It doesn't address critical aspects like error handling, confirmation prompts, return values, or how deletions interact with sibling tools (e.g., 'read_patterns' post-deletion). More context is needed to safely use this tool.
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%, with the parameter 'patternNames' documented as 'An array of pattern names to delete'. The description adds no additional meaning beyond this, such as format constraints or examples. Since the schema already covers the parameter adequately, the baseline score of 3 is appropriate.
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 ('Delete') and target resource ('multiple patterns from the database'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'delete_code_examples' or 'open_patterns', but the verb+resource combination is specific enough to infer the 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?
No guidance is provided on when to use this tool versus alternatives like 'delete_code_examples' or other deletion-related operations. The description lacks context about prerequisites, such as whether patterns must exist or be in a specific state before deletion, or what happens to associated data.
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 searches 'across all fields', which adds some context beyond the input schema, but fails to describe critical behaviors like whether results are paginated, sorted, or limited; what the return format looks like; or any performance considerations. For a search tool with zero annotation coverage, this leaves significant 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 that directly states the tool's function without any redundant or vague language. It is appropriately sized and front-loaded, with every word contributing to understanding the tool's purpose.
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 incomplete for a search tool. It doesn't explain what the search returns (e.g., list of patterns, metadata, relevance scores), how results are structured, or any behavioral traits like error handling. The agent is left with significant unknowns about the tool's operation and output.
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 input schema has 100% description coverage, with the 'query' parameter fully documented in the schema itself. The description adds marginal value by implying the query searches 'across all fields', but doesn't provide additional syntax, format details, or examples beyond what the schema already states. This meets the baseline for high schema coverage.
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 'search' and the resource 'patterns', specifying it searches 'based on a query across all fields'. This distinguishes it from siblings like 'read_patterns' (likely a simple retrieval) and 'create_patterns' (creation). However, it doesn't explicitly contrast with 'open_patterns' or other search-like siblings, 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 Guidelines2/5
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 'search_patterns' over 'read_patterns' or 'open_patterns', nor does it specify any prerequisites, exclusions, or optimal contexts for usage. 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states a read operation but doesn't clarify aspects like whether it returns all patterns at once, uses pagination, requires specific permissions, or has rate limits. This leaves significant gaps in understanding how the tool behaves beyond its basic function.
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, clear sentence with no wasted words, making it highly efficient and easy to parse. It front-loads the essential information without unnecessary elaboration, which is ideal for a simple tool.
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 incomplete for a read operation. It doesn't specify what 'all patterns' entails (e.g., format, scope, or limitations), leaving the agent uncertain about the tool's full context and behavior. This is inadequate for a tool that might return complex data.
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, so no parameter documentation is needed. The description doesn't add parameter details, which is acceptable in this case, as there are no parameters to explain. This meets the baseline for tools with no 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 ('Read') and resource ('patterns from the database'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'search_patterns' or 'open_patterns', which might offer similar functionality with different scopes or methods.
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?
No guidance is provided on when to use this tool versus alternatives such as 'search_patterns' or 'open_patterns'. The description lacks context about prerequisites, ideal scenarios, or exclusions, leaving the agent to infer usage based on 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.

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