Markdown3D MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose: transformation (normal and chunked), validation, assembly, cache management, status checking, and performance stats. The only potential overlap is between the two transform tools, but the chunked variant's purpose is explicitly differentiated.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (e.g., assemble_chunks, clear_cache, get_performance_stats, transform_to_nm3). The naming is predictable and uniform.
Tool Count5/5
With 7 tools, the set is well-scoped for a server focused on transforming markdown to NM3. Each tool serves a specific function in the workflow, and there are no extraneous or missing tools relative to the domain.
Completeness4/5
The tool set covers the core transformation lifecycle (normal and chunked), validation, and assembly, plus utility functions (cache, status, performance). A minor gap is the lack of a reverse conversion (NM3 to markdown), but this is not part of the stated purpose.
Average 2.9/5 across 7 of 7 tools scored. Lowest: 2.1/5.
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, the description fails to disclose any behavioral traits, such as whether the operation is read-only, has side effects, or requires specific permissions. The single sentence provides no insight into tool behavior beyond the implied status check.
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 extremely concise (one sentence), which is efficient but insufficient for a tool with no annotations or output schema. It sacrifices necessary detail for brevity.
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 single parameter and lack of output schema, the description should explain what status information is returned, possible values, or how to interpret results. It provides none of this, leaving the agent underinformed.
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 has 100% coverage for the single parameter 'manifestPath', so the baseline is 3. The description adds no extra meaning beyond the schema's own description, but does not detract either.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Check status of chunked output' merely rephrases the tool name without providing additional context or distinguishing it from siblings like 'assemble_chunks'. It lacks specificity about what 'status' entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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. There is no mention of prerequisites, context, or exclusions, making it impossible for an agent to determine appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full responsibility for behavioral disclosure. It merely states the action without any details on side effects, destructiveness, idempotency, required permissions, or state changes. This is insufficient for an agent to gauge safety.
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 sentence that is front-loaded and contains zero wasted words. It is appropriately sized for a tool with no parameters.
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, output schema, and usage guidance, the description is too brief to fully inform an agent. It lacks crucial behavioral and contextual details, such as when this action is safe or what the consequences are.
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?
There are no parameters, and schema coverage is trivially 100%. The description adds no parameter information because none is needed. Baseline for zero parameters is 4, which is appropriate here.
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 'Clear all caches' clearly states the verb (clear) and resource (all caches). It is specific enough for an agent to understand the action, though 'all caches' could be ambiguous in scope. Distinguishes from sibling tools which focus on chunk operations and transformations.
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 vs alternatives. The description does not mention prerequisites, contexts, or situations where clearing caches is appropriate. 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, the description carries the full burden. It does not disclose any behavioral traits such as whether the operation is read-only, requires authentication, or has side effects.
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 a single sentence, but it is very brief and lacks detail. It is functional but could be improved with more context.
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 output schema and no annotations, the description is minimal. It does not explain what kind of statistics are returned, how to interpret them, or how this tool relates to other cache/tools.
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 0 parameters, and the schema coverage is 100%. Per guidelines, a baseline of 4 is appropriate since the description does not need to add parameter details.
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 'Get performance and cache statistics' clearly states the verb (Get) and resource (performance and cache statistics), distinguishing it from sibling tools like clear_cache or get_chunk_status.
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. There is no mention of context, prerequisites, 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?
No annotations provided, so description must cover behavioral traits. It indicates 'Validate' (read-only), but does not disclose what happens on failure (e.g., error thrown, return false) or side effects. Lacks depth.
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?
Single sentence with no wasted words. Could benefit from slight expansion, but not overly verbose.
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?
Simple tool with one parameter and no output schema. Description is minimally complete but lacks details on return value (boolean, errors) and the specific spec. Acceptable for a straightforward validation 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 coverage is 100% with description 'NM3 XML to validate'. Description adds no further meaning beyond schema, so baseline 3 is appropriate. No format, encoding, or size constraints mentioned.
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 'Validate' and the resource 'NM3 XML', and mentions compliance with a spec. It distinguishes from sibling tools like transform_to_nm3. However, 'spec' is vague without specifying which standard.
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 (e.g., after transformation, before further processing). No exclusions or prerequisites mentioned.
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 discloses the truncation behavior for large documents (>300 nodes) and states the output format (full XML). However, without annotations, it does not cover other behavioral aspects like idempotency, authorization needs, or side effects.
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 sentence that quickly conveys the action and a key limitation. It is efficient and front-loaded, though slightly ambiguous due to the contradiction between 'full XML' and 'may truncate'.
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 no output schema and 5 parameters, the description is insufficient. It contradicts itself (returns full XML but may truncate), lacks information about error conditions, streaming behavior, or the XML structure. For a moderately complex tool, this is incomplete.
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 100% with all parameters described. The tool description adds no extra meaning beyond the schema; the truncation note is not parameter-specific. Baseline score 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 verb 'Transform' and the resource 'markdown to NM3', and adds a note about returning XML with a truncation warning. However, it does not explicitly differentiate from the sibling tool 'transform_to_nm3_chunked'.
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 explicit when-to-use or when-not-to-use guidance is provided. The truncation warning hints at a limitation but does not suggest alternatives or contextual usage rules.
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 must convey behavioral traits. It only states the purpose without mentioning any side effects, required permissions, error conditions (e.g., missing manifest), or whether the operation is destructive. This is insufficient for an AI agent to understand the tool's behavior.
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 sentence that is concise and front-loaded. Every word is necessary; no wasted text.
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 only 2 parameters and no output schema, the description lacks important context: it does not explain what an NM3 file is, what the manifest path should point to, or what the output directory defaults to. Given the sibling tools, more details would help an agent decide when to invoke 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% (both parameters have descriptions). The tool description adds no additional meaning beyond what the schema already provides. Based on the rubric, baseline is 3 when schema coverage is high, so no deduction.
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 'Assemble chunked output into final NM3 file' clearly states the verb (assemble) and resource (chunked output to NM3 file). It distinguishes well from siblings like transform_to_nm3_chunked, which creates the chunks, and get_chunk_status, which checks progress.
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 explicit guidance on when to use this tool versus alternatives. While it is implied that this should be used after transform_to_nm3_chunked, the description does not state prerequisites, exclusions, or mention alternative workflows like using transform_to_nm3 for non-chunked inputs.
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 present, so the description carries the full burden. It mentions chunked output but does not disclose behavioral traits like whether the tool is destructive, the need to later assemble chunks (given sibling assemble_chunks), or any side effects of caching/streaming parameters.
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?
Description is a single, front-loaded sentence that conveys purpose and benefit efficiently. It is concise without unnecessary words, though could be slightly expanded for clarity.
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 the tool having 7 parameters and no output schema, the description is minimal. It does not explain the chunking mechanism, how results are returned, or the relationship with sibling tool assemble_chunks. This leaves the agent with insufficient context to use the tool effectively.
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 parameters. The description adds no extra meaning beyond the schema; for example, it does not clarify how 'chunked output' relates to the parameters or the output process.
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?
Description clearly states the action (transform), input (markdown), output format (NM3 with chunked output), and the problem it solves (prevents truncation for large docs). It distinguishes from sibling transform_to_nm3 by mentioning chunked output.
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?
Implies usage for large documents to prevent truncation, but does not explicitly state when to use this tool vs alternatives like transform_to_nm3, nor when not to use it. No exclusions or alternative tool names are provided.
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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