mfds-mcp

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct operation: extracting sections, retrieving documents, finding latest versions, listing recent updates, refreshing data, searching guidelines, searching law notices, checking status, and viewing version history. There is minimal overlap.
Naming Consistency3/5
All tools share the 'mfds_' prefix, but the naming pattern is inconsistent: some use verb_noun (extract_section, get_document, search_guidelines), while others use noun phrases (latest_version, status, version_history) or verb_adj (list_recent). This could confuse an agent expecting a uniform pattern.
Tool Count5/5
With 9 tools, the server is well-scoped for the domain of MFDS document and law notice access. The count feels appropriate without being overwhelming or too sparse.
Completeness3/5
The server covers key reading and searching operations, but has notable gaps: there is no tool to retrieve actual current law text (only amendment notices with 'unknown' currency) and no browsing or listing of all documents beyond recent ones. Core workflows are supported but incomplete.
Average 3.7/5 across 9 of 9 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 9 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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint=true. The description adds value by listing the specific types of diagnostic data returned (e.g., attachment parsing failures, structure warnings). However, it does not disclose any potential side effects, rate limits, or other behavioral traits beyond what annotations provide.
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, compact sentence that lists the output categories. It is front-loaded with '진단:' to indicate purpose. While efficient, the list format could be more structured (e.g., bullet points) for easier parsing.
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 is marginally adequate given the presence of an output schema and no parameters. However, it is very terse and does not explain the context (e.g., what 'board' refers to) or the structure of the output. An agent might need more context to fully understand the returned 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?
There are zero parameters, and the schema coverage is 100%. The description does not need to add parameter semantics. The baseline for 0 params is 4, and the description does not detract.
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 provides diagnostic information: document counts, status distribution, attachment parsing failures, last crawl time, and structure warnings. It specifies the resource (system status) and the action (diagnosis). However, it does not explicitly differentiate from sibling tools, and the purpose could be more action-oriented.
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 lacks any guidance on when to use this tool versus alternatives. It does not mention prerequisites, exclusions, or typical scenarios. The agent is left to infer usage from the context alone.
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 declare readOnlyHint=true, so the description adds context like including source attachment name. However, it does not disclose details about behavior like truncation or error handling.
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 key information (action, resource, source inclusion) is efficient and front-loaded, though extra parameter hints could help.
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?
Lacks explanation for required parameters board and seq, which are essential for identifying the document. With output schema present, the description should clarify these identifiers.
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 50% (keyword and window have descriptions), but the description does not add meaning for the undocumented required parameters board and seq. It only implies keyword usage.
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 specific verb 'extract' and resource 'sections around keywords from long guideline text', and distinguishes from siblings like mfds_get_document (full document) and mfds_search_guidelines (search).
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 implies usage for extracting keyword-related sections, but does not explicitly state when to use this tool versus alternatives or provide any exclusions.
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 adds context beyond the readOnlyHint annotation by specifying that the tool returns '판본·상태·판정근거' (version, status, judgment basis), indicating an audit-focused read operation. However, no additional behavioral traits (e.g., rate limits, data freshness) are disclosed.
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 directly conveys the tool's purpose without wasted words. It is appropriately sized and front-loaded.
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 that an output schema exists, the description need not detail return values, but it still specifies the key outputs (version, status, judgment basis). This provides sufficient context for a read-only audit tool, though it could mention any limitations or prerequisites.
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 both parameters (board and seq) adequately. The description does not add further parameter semantics, meeting the baseline expectation.
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 identifies the tool's output (full version, status, judgment basis) and distinguishes it from sibling tools like mfds_latest_version by specifying an 'audit view' of a version group. However, it lacks an explicit action verb (e.g., 'Retrieve'), though the purpose is still clear.
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 siblings. The description does not mention alternatives, prerequisites, or exclusions, leaving the agent to infer usage from the tool's name and output description.
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 declare readOnlyHint=true, and the description does not contradict it. It states the tool performs a search, which is read-only. No additional behavioral details (e.g., rate limits) are needed for a simple search tool.
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 two short sentences, front-loads the main purpose, and contains no fluff. Could be slightly more structured, but efficient.
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's complexity (5 parameters, output schema, readOnlyHint), the description is adequate. It specifies the document type and prioritization, which complements the schema. No major gaps.
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%, so baseline 3. The description adds no significant meaning beyond what each parameter's description already provides in the schema.
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?
Description clearly states it is a full-text search for MFDS guidelines, specifying document type (m_1059) and prioritization of current versions. However, it does not explicitly differentiate from sibling search tool mfds_search_law_notices.
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?
Description implies use for searching guidelines but provides no guidance on when to use alternatives or exclusions. No mention of when not to use this tool.
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 declare readOnlyHint=true, so the description does not contradict. The description adds valuable context: the tool auto-estimates the current version, confidence levels, and warns about low confidence or unknown status requiring manual verification.
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?
Description is very concise: action stated first, return fields listed, then a warning. No wasted words. Well-structured for easy scanning.
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?
Output schema exists, so return values are documented. The description covers primary behavior, confidence estimation, version history, and verification warning. It lacks mention of domain parameter handling and error conditions, but overall adequately complete.
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 coverage is 0%, so description must compensate. It provides context for 'title_or_topic' (주제/제목) but does not explain the optional 'domain' parameter. Missing parameter semantics reduce clarity for the agent.
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 returns the current guideline candidate with evidence and confidence, plus version history, based on a subject/title. It distinguishes this from siblings like mfds_version_history (which returns full history) and mfds_search_guidelines.
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 implies usage when needing the latest version with confidence assessment, but does not explicitly state when to avoid this tool or mention alternatives like mfds_get_document or mfds_search_guidelines.
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?
The annotation indicates readOnlyHint=true, and the description adds behavioral context by specifying the ordering (descending by publication date). This goes beyond the annotation, providing useful execution behavior without 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?
The description is extremely concise: two sentences that front-load the purpose and ordering. Every sentence adds value without redundancy.
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's simplicity and the presence of an output schema, the description is sufficiently complete. It covers purpose, ordering, and board grouping. Missing details like pagination are not critical for a list tool with a limit parameter.
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?
The schema already covers 75% of parameters with descriptions. The tool description does not add additional meaning beyond implying board grouping and date ordering. It fails to clarify the 'limit' parameter or provide extra context for usage.
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 lists recent documents by board in descending order of publication date, specifying the resource and action. It distinguishes from siblings like search tools by focusing on monitoring recent items.
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 implies use for monitoring recent documents but does not explicitly state when to use this tool versus alternatives like search or extract tools. No exclusions or alternative recommendations are provided.
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?
The description discloses behavioral traits beyond the annotations: it reveals the multi-step pipeline (crawl, parse, load, reassess) and warns about potential slowness. Annotations already indicate readOnlyHint=false, destructiveHint=false, idempotentHint=true, and the description aligns without contradiction. The additional pipeline context helps the agent understand the cost and side effects of invoking this tool.
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 very concise: a single sentence in Korean that front-loads the operation type and pipeline steps. Every word serves a purpose, and the warning about slowness is useful. It sacrifices some structural clarity (e.g., no bullet points or emphasis) but is efficient for the information conveyed.
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's complexity (multi-step refresh, multiple parameters, and output schema), the description together with annotations and schema provides sufficient context. The pipeline steps, write nature, and speed warning cover most operational aspects. However, it does not explain the purpose of the refresh (e.g., updating cached data) or when the output schema might be relevant, but the output schema itself handles return value details.
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 already has full coverage (100%) with descriptions for all three parameters ('board', 'max_pages', 'full'). The description text adds no additional meaning or context about these parameters beyond what the schema provides. According to the guidelines, when schema coverage is high, the baseline is 3, and the description does not exceed this baseline.
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 defines the tool as a refresh pipeline: '게시판 크롤 → 첨부 파싱 → 적재 → 상태 재판정' (crawl bulletin board, parse attachments, load, reassess status). The verb is implied by the name 'refresh' and the pipeline. It clearly distinguishes from sibling tools like 'mfds_get_document' (single retrieval) or 'mfds_search_guidelines' (search), as it is a batch update operation.
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 provides some usage context by labeling it as '운영/쓰기' (write operation) and warning it may be slow ('느릴 수 있음'). This implies it should be used for bulk updates rather than quick queries. However, it does not explicitly state when to use this tool versus specific alternatives, nor does it mention when not to use it. The guidelines are therefore implicit rather than explicit.
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 declare readOnlyHint=true, so the description does not need to reiterate. The description adds context about the part parameter's role in saving context, but beyond that, no behavioral details (e.g., pagination, error handling) are provided.
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, well-structured sentence that immediately states the main purpose and follows with a key usage tip. Every word serves a purpose, and there is no redundancy.
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 presence of a full output schema (not shown) and complete parameter descriptions, the description is sufficient for a straightforward tool. It clearly communicates the core action and a critical parameter nuance. It could be slightly improved by clarifying what 'meta' includes, but it is not necessary.
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 covers all 4 parameters with descriptions. The description adds semantic value by explaining the rationale behind the part parameter default ('컨텍스트 절약을 위해'), which helps an agent understand when to use 'meta' vs 'full'.
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 action (단일 문서 조회, i.e., view a single document) and the resource (문서). It is distinct from sibling tools like mfds_list_recent or mfds_extract_section, which serve 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving a single document and suggests using part='meta' to save context, but it does not explicitly state when to choose this tool over siblings or provide exclusion criteria.
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. The description adds valuable behavioral context: the tool returns amendment notices (not current law), the law_currency field is always 'unknown', and the results link to law.go.kr. This goes beyond the annotation by disclosing limitations and required user verification.
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 extremely concise: two short Korean sentences plus a warning. It front-loads the purpose and key limitation, with no unnecessary words or repetition. Every sentence adds value.
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 presence of an output schema and 100% schema coverage for parameters, the description adequately covers the tool's purpose, warning, and key return fields. It mentions the critical always-unknown field. It is slightly lacking in terms of pagination details, but for a search tool this is 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 description coverage is 100%, so the schema already documents all parameters (query, law_name, since_date, limit). The description does not add additional parameter-level meaning beyond what the schema provides. Baseline 3 is appropriate.
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 searches for MFDS law amendment promulgation notices, explicitly distinguishing it from current law text. It specifies what each result item provides (announcement number, dates, URL). This differentiates it from siblings like mfds_latest_version and mfds_status.
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 warns that this is not current law and that the law_currency field is always 'unknown', urging users to check the original URL. While it does not explicitly list alternatives or when-not-to-use, the warning implicitly guides the agent away from using this for current law queries.
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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