autocad-mcp

Server Quality Checklist

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Latest release: v3.0.0
Disambiguation4/5
Tools are mostly distinct, with annotation covering text/leaders/dimensions and specialized tools for audit, auto, batch, plan, and repair. Some overlap exists between individual dimension creation in annotation and the batch/auto tools, but performance rules help disambiguate.
Naming Consistency4/5
All tools use snake_case, and annotation-related tools share an 'annotation_' prefix. However, patterns vary (e.g., detect_parts vs. auto_dimension), though still readable.
Tool Count5/5
9 tools is well-scoped for a CAD server covering drawing management, annotation, and P&ID. Each tool has clear purpose without redundancy.
Completeness2/5
Significant gaps: no tools for basic geometry creation (lines, circles), general editing, or layer management. The server is heavily biased toward dimensions and P&ID, missing fundamental CAD operations.
Average 3.3/5 across 9 of 9 tools scored. Lowest: 1.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 29 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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{
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  "maintainers": [
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  ]
}
```
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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

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description claims 'Create or revise' which implies mutation, but annotations declare readOnlyHint=true, a direct contradiction. This undermines transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence but too vague to be effective. It fails to convey essential information concisely.
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?
With 0% schema coverage, no parameter explanations, and a contradictory description, the tool definition is incomplete for an agent to use correctly.
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 coverage is 0%. The description does not explain the 'data' or 'include_preview' parameters, leaving the agent without meaningful guidance.
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 states it creates or revises a plan and explicitly says no AutoCAD entity is created, but 'D1/D2... plan' is vague. It somewhat distinguishes from siblings that deal with dimensions.
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 on when to use this tool versus alternatives like annotation_auto_dimension or annotation_batch_create_dimensions.
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?
The description aligns with the destructiveHint annotation by mentioning removal and fixing. However, it adds no additional behavioral details such as what exactly gets destroyed, required permissions, or rate limits. The title provides some context but is not part of the description.
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 concise sentence with no unnecessary words or repetition. It is appropriately front-loaded.
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 that the tool has an output schema, no required parameters, and a destructive hint, the description is too sparse. It does not explain what kind of data is expected, how the screenshot parameter affects behavior, or what the output looks like. The title and annotations provide some context, but the description itself is incomplete.
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?
The description provides no information about the parameters (data, include_screenshot). With 0% schema description coverage, the description fails to add any meaning beyond the bare schema structure.
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: removing duplicates and fixing issues related to safe layer/style/lane from a fresh audit. However, it does not differentiate itself from sibling tools like annotation_audit_dimensions or annotation_plan_dimensions, which might also deal with layout issues.
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. The phrase 'from a fresh audit' implies it is used after an audit, but this is not explicit, and there is no mention of when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description lists sub-operations, which gives some behavioral insight beyond the minimal annotations. However, it does not disclose side effects, permissions, or detailed behavior of each operation.
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 front-loaded with the main purpose and then lists operations in a structured way. It is reasonably concise for the number of operations, but could be slightly more compact.
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 (multiple operations, 3 parameters, output schema present), the description is incomplete. It does not explain return values, how to structure the data parameter for each operation fully, or usage with screenshots.
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 description adds meaning by listing valid operation values and hinting at data structures for many operations. However, it does not fully define the data parameter schema, and the include_screenshot parameter is not mentioned. Schema coverage is 0%.
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 is for P&ID drawing with a CTO symbol library and lists specific operations. However, it does not distinguish this tool from sibling tools like 'drawing' or other annotation tools.
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 lists operations but does not explain the context or prerequisites for using the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description identifies read-only sub-operations (detect_parts, audit_dimensions) and mentions behavior like undo groups and regen for batch operations. Beyond the annotations (readOnlyHint=false), it adds context but does not fully disclose error states, permission requirements, or the full scope of effects, especially for commit operations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is structured as a bullet list of operations, which aids scanning. However, it is quite long and includes repetitive performance rules at the end. Some information could be condensed without loss of clarity.
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 complexity of the tool (many operations) and minimal schema, the description covers the main operations and provides performance rules. However, it omits how output schema looks, error handling, and the relationship to sibling tools. It is adequate but not fully comprehensive.
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?
With the input schema having 0% parameter description coverage, the description compensates by listing expected data keys for each operation (e.g., create_text expects x, y, text, etc.). This adds significant meaning beyond the generic schema. Some operations are vaguely defined (e.g., dimension_profiles has 'action' but no details), so it's not perfect.
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 domain—text, dimensions, leaders, and automatic dimension workflows. It lists multiple specific operations, making the purpose evident. However, it does not differentiate this parent tool from sibling tools that seem to provide the same sub-operations directly, which could cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes explicit performance rules (e.g., use batch or auto_dimension for multiple dimensions, pass region when possible) and notes mutual exclusivity of selection parameters. These provide actionable guidance for efficient tool use. However, it lacks guidance on when to use this parent tool versus the sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety and idempotency. The description adds that the tool finds specific quality issues, which is consistent and provides useful output context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single 14-word sentence that efficiently lists all audit categories without extraneous text. It is front-loaded and concise.
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 (auditing with multiple issue types) and the presence of an output schema, the description adequately conveys the purpose but lacks context about the input 'data' parameter and how to interpret results.
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 no parameter descriptions exist. The tool description does not mention or explain the 'data' or 'include_preview' parameters, leaving the agent with no semantic guidance beyond parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly lists six distinct types of issues (duplicates, overlap, crossings, missing intent, detached refs, style errors), clearly stating what the tool does. It distinguishes itself from sibling tools that create, plan, or repair dimensions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no explicit guidance on when to use this tool versus alternatives like annotation_auto_dimension or annotation_repair_dimension_layout. The usage context is implied but not 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?
Annotations indicate readOnlyHint=false, but the description does not disclose potential side effects, required permissions, or failure modes for operations like 'save', 'purge', or 'undo'. Behavioral traits beyond the annotation are minimal.
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 front-loaded with 'Drawing file management' and uses a clear bullet list of operations. It is concise with no unnecessary words, but the structure could be improved by grouping operations or using consistent formatting.
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 multiple operations and presence of an output schema, the description adequately lists operations and their data inputs. However, it lacks details on return values for each operation and does not explain how to handle common scenarios like opening a non-existent file. It is functional but not exhaustive.
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 0% description coverage, so the description partially compensates by showing expected data fields per operation (e.g., 'data: {name?}' for create). However, the 'data' parameter is loosely defined as any object, and the description does not fully cover all operations or parameter constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Drawing file management' and lists specific operations (create, open, info, etc.), making it distinct from sibling tools which focus on annotations and PID. The verb+resource pattern is explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lists all operations with brief explanations, providing clear context for when to use each sub-operation. However, it does not explicitly contrast with sibling tools or state when not to use this tool. The distinction is implied by the operations offered.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations include destructiveHint=true, but the description does not elaborate on destructive behavior. It adds some context (performance rules) but does not explain side effects or state changes beyond annotations. No contradiction.
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?
Extremely concise: two sentences for core purpose and two performance rules. No redundancy, every sentence adds value.
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?
Despite having output schema and annotations, the description fails to explain the input parameters ('data', 'include_screenshot') or how to construct them. The catch-all 'data' parameter is left ambiguous, making the tool less usable.
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% for the two parameters ('data', 'include_screenshot'). The description references parameters like 'region', 'entity_ids', 'selection' that are not in the schema, and does not explain the actual parameters, leaving the agent uninformed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool's action ('plan and immediately commit dimensions') and resource ('one selected part/region/entity set'). It also distinguishes from sibling tools like annotation_batch_create_dimensions and annotation_plan_dimensions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear performance rules: when to use batch vs single, and how to optimize by passing region/entity_ids/selection and reusing geometry_cache_token after detect_parts. Explicitly states to avoid calling create_dimension_* repeatedly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description adds value by explaining clustering, return format (part_1, part_2...), and cache reuse behavior. No contradictions.
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?
Two sentences with zero fluff: first sentence defines purpose, second provides critical performance guidance. Every word earns its place.
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?
The description covers core functionality and performance rules, but omits parameter semantics and lacks detail on what the indexed preview includes. Output schema exists, so return values are documented elsewhere, but parameter info is missing.
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%, and the description does not mention any parameter (data, include_preview). It fails to add meaning beyond the schema, leaving users to infer purpose and constraints of the two parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'Cluster Model Space geometry and return part_1, part_2... with an indexed preview', specifying the verb (cluster and return) and resource (independent drawing parts). This distinguishes it from sibling tools like annotation_audit_dimensions or drawing, which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit performance rules: 'pass region, entity_ids, or selection='current' whenever possible' and 'reuse geometry_cache_token together with target_part_id...'. While no explicit when-not-to-use or alternatives, the guidance on efficient use is clear and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark it as destructive (destructiveHint: true) and non-readonly. The description adds context: batch creation in one Undo group and accepted dimension types/forms. No contradictions, but it doesn't cover failure modes or authorization needs, so a 3 is appropriate.
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?
Two succinct sentences: first states the core function, second provides usage guidance and parameter hints. No redundant words; every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool complexity (nested objects, output schema exists), the description covers creation purpose, batch nature, and dimension types. It lacks details on output or structure, but output schema likely fills gaps. Sibling context is minimal but sufficient.
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 coverage is 0%, so description must compensate. It explains that data.dimensions accepts specific types (linear, diameter, etc.) in two forms, which adds value. However, it does not detail the object structure or include_screenshot semantics, so it is only partially helpful.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Create two or more dimensions in one request and one Undo group.' It specifies the verb (create), resource (dimensions), and distinguishes from siblings by emphasizing batch creation and Undo group atomicity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly advises: 'Use this instead of repeatedly calling annotation.create_dimension_*.' This provides clear when-to-use guidance. It implies not to use for single dimensions but does not list all alternatives; a bit more explicit exclusion would earn a 5.
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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