depreciation-mcp
depreciation-mcp
법인세법 기준 고정자산 내용연수·감가상각·세무조정 참고값을 Model Context Protocol(MCP)로 제공하는 서버입니다.
계산 결과는 참고용입니다. 신고·회계처리는 적용 법령·사실관계·전문가 검토가 필요합니다.
PRD 배경 (MCP-DEP-001-v1)
아래 프로젝트 개요, 문제 정의, 목표 사용자, 핵심 사용자 시나리오는 PRD 시설 감가상각 계산 MCP v1.0(수정판) 의 1·2·3·6장을 README용으로 옮긴 것입니다.
1. 프로젝트 개요
고정자산 감가상각은 결산 및 법인세 신고에서 반복적으로 수행되는 핵심 실무다.
하지만 실제 현장에서는 다음 문제가 반복된다.
자산 유형별 내용연수 확인을 위해 시행규칙 [별표 5·6]를 직접 찾아야 한다.
회계팀 또는 총무팀이 스프레드시트 수식에 의존하여 계산한다.
정액법/정률법 선택, 내용연수 범위 검토, 세무조정 계산이 분리되어 있어 작업이 번거롭다.
담당자 변경 시 판단 기준이 남지 않아 일관성이 떨어진다.
본 MCP는 이 과정을 표준화하여, 사용자가 자산 정보를 입력하면
법인세법 기준의 내용연수 조회 → 감가상각 계산 → 세무조정 참고값 → 일괄 처리 및 비교 분석까지 일관되게 제공하는 것을 목표로 한다.
2. 문제 정의
2.1 현재 실무의 불편
법령 조회의 반복성
자산 분류와 업종별 기준연수를 매번 수동 확인해야 한다.계산의 비일관성
같은 자산도 담당자에 따라 다른 내용연수 또는 다른 계산식이 적용될 수 있다.세무조정의 분리 관리
회계상 감가상각비와 세무상 상각범위액 비교를 별도로 계산해야 한다.다수 자산 처리의 비효율
결산 시즌에는 수십 건 자산을 반복 계산해야 한다.업종별 비교 검토의 어려움
동일 자산을 서로 다른 업종 기준으로 검토하려면 수작업이 많다.
3. 목표 사용자
사용자 그룹 | 주요 자산 | 주요 니즈 |
병원·의료기관 총무팀 | 의료장비, 건물부속설비, 차량 | 고가 자산 내용연수 및 상각방법 검토 |
제조업 회계팀 | 기계장치, 공장설비, 차량 | 정률법 기준 계산과 세무조정 |
IT·서비스 기업 총무팀 | 서버, 네트워크 장비, 소프트웨어, 가구 | 자산 분류 및 내용연수 표준화 |
중소기업 대표/경리 | 차량, 비품, 사무설비 | 빠르고 실수 없는 기준 계산 |
결산 담당자 | 다수 자산 포트폴리오 | 일괄 계산 및 요약표 확인 |
4. 핵심 사용자 시나리오 (PRD 6장)
시나리오 A — 병원 장비 내용연수 조회
사용자:
“MRI 장비를 의료업 기준으로 보면 내용연수가 몇 년인지 알려줘.”
처리 흐름
get_useful_life호출Q86 + 의료기기 기준 조회
기준내용연수, 허용 범위, 상각방법, 법적 근거 반환
시나리오 B — 단일 자산 감가상각 계산
사용자:
“취득가액 15억, 취득일 2026-03-01, 내용연수 5년으로 감가상각 스케줄 계산해줘.”
처리 흐름
calc_depreciation_schedule호출정액법/정률법/생산량비례법 중 해당 방식 계산
연도별 감가상각비, 장부가액, 누계액 반환
시나리오 C — 세무조정 계산
사용자:
“회계상 감가상각비와 세무상 상각범위액 차이 알려줘.”
처리 흐름
calc_tax_adjustment호출손금부인액, 시인부족액, 추인 가능 금액 계산
설명 메모와 함께 반환
시나리오 D — 결산 시즌 다수 자산 일괄 처리
사용자:
“자산 50건을 한 번에 계산해서 연간 감가상각비와 손금부인액 요약해줘.”
처리 흐름
calc_bulk_depreciation호출자산별 계산 수행
총 감가상각비, 총 세무 한도, 총 손금부인액 요약 반환
시나리오 E — 업종 간 비교
사용자:
“같은 서버 장비를 의료업과 소프트웨어업 기준으로 비교해줘.”
처리 흐름
compare_industry_life호출업종별 내용연수 및 연도별 감가상각 차이 비교
비교표 반환
Related MCP server: ko-stock-mcp
요구 사항
Node.js 20 이상
pnpm 9 이상 (또는
npm/corepack으로pnpm활성화)
설치 (공통)
저장소를 클론한 뒤 의존성 설치와 빌드까지 진행합니다.
git clone https://github.com/boam79/depreciation-mcp.git
cd depreciation-mcp
pnpm install
pnpm run build빌드가 끝나면 실행 파일은 dist/index.js 입니다. (dist/는 저장소에 포함되지 않으므로 반드시 로컬에서 pnpm run build 필요)
개발 모드 (빌드 없이 실행)
pnpm exec tsx src/index.tsCursor AI에 연결하는 방법
1) 전역 MCP 설정 파일
Cursor에서 Settings → MCP 로 이동하거나, 설정 JSON을 직접 엽니다.
macOS에서 사용자 MCP 설정은 보통 다음 경로입니다.
~/.cursor/mcp.jsonmcpServers안에 아래 블록을 추가합니다.args의 경로는 본인 PC에서 클론·빌드한 폴더의 절대 경로로 바꿉니다.
{
"mcpServers": {
"depreciation-mcp": {
"command": "node",
"args": ["/절대경로/depreciation-mcp/dist/index.js"]
}
}
}예 (다운로드 폴더에 둔 경우):
"depreciation-mcp": {
"command": "node",
"args": ["/Users/본인계정/Downloads/depreciation-mcp/dist/index.js"]
}Cursor를 완전히 종료 후 다시 실행합니다.
채팅에서 MCP 도구 목록에
get_useful_life,calc_depreciation_schedule등이 보이면 연결된 것입니다.
2) 프로젝트 전용 (선택)
프로젝트 루트의 .cursor/mcp.json을 쓰는 워크스페이스라면, 동일한 JSON을 그 파일에 넣을 수 있습니다. (Cursor 버전에 따라 UI 경로가 다를 수 있습니다.)
3) 빌드 없이 tsx로 연결 (선택)
"depreciation-mcp": {
"command": "pnpm",
"args": ["exec", "tsx", "/절대경로/depreciation-mcp/src/index.ts"],
"cwd": "/절대경로/depreciation-mcp"
}Claude Desktop에 연결하는 방법 (macOS)
Claude Desktop을 종료합니다.
설정 파일을 엽니다.
~/Library/Application Support/Claude/claude_desktop_config.json최상위에
mcpServers가 없으면 만들고, 다음을 추가합니다.
{
"mcpServers": {
"depreciation-mcp": {
"command": "node",
"args": ["/절대경로/depreciation-mcp/dist/index.js"]
}
}
}파일을 저장하고 Claude Desktop을 다시 실행합니다.
새 대화에서 MCP 도구가 노출되는지 확인합니다.
Windows 사용자는 Claude 공식 문서의 설정 파일 경로를 확인한 뒤, 동일하게 command / args만 맞추면 됩니다.
제공 도구 (6개)
도구 | 설명 |
| 자산 유형·업종·건물구조 기준 내용연수·허용 범위·기본 상각방식 |
| 정액·정률·생산량비례 스케줄 |
| 회계 vs 세무 한도 차이(손금부인·시인부족·추인 단순모형) |
| 자산 분류 목록 |
| 최대 100건 일괄·요약 |
| 업종별 내용연수·상각 비교 |
스크립트
명령 | 설명 |
| TypeScript → |
|
|
|
|
| Vitest |
| stdio 연결·도구 6개· |
연결 테스트 (로컬)
빌드 후 프로젝트 루트에서:
pnpm smokeOK: listTools 및 OK: get_useful_life가 나오면 MCP 서버 프로세스와 프로토콜이 정상입니다.
데이터에 관해
src/data/annex5.ts, annex6.ts 등은 실무 보조용 요약 데이터입니다. 법령 개정 시 내용을 갱신하고 pnpm test로 검증하세요.
저장소
Available Tools
6 toolscalc_bulk_depreciation일괄 감가상각C
최대 100건, 회계 스케줄 vs 세무 기본 스케줄로 당기 손금부인 등 요약
| Name | Required | Description | Default |
|---|---|---|---|
| assets | Yes | 자산 목록 | |
| fiscal_year | Yes | ||
| output_format | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description provides minimal behavioral context: limit of 100 assets, comparison of accounting vs tax schedules, and a summary output. No disclosure of whether the tool mutates data, requires authentication, or any side effects. Since no annotations exist, the description should carry the full burden but fails to cover key traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is a single sentence, very concise, but it omits structure like a separate purpose statement or parameter details. It is not excessively long, but the brevity sacrifices completeness. A more structured format would improve usefulness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters, nested objects, and no output schema, the description lacks crucial details: what the summary contains, how to interpret the output, and any prerequisites. The tool is moderately complex but the description does not adequately inform an agent how to use it or what to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 3 parameters with only 33% description coverage (only 'assets' has label '자산 목록'). The tool description adds no parameter-level context; it does not explain fiscal_year or output_format beyond the enum values. Despite low coverage, the description does not compensate, leaving parameter semantics unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description indicates bulk depreciation calculation for up to 100 assets, comparing accounting and tax schedules, producing a summary including tax deduction denial. This differentiates from sibling tools like calc_depreciation_schedule (likely single asset) and calc_tax_adjustment (likely more detailed adjustment). However, the phrasing '등 요약' is vague, slightly reducing clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. No mention of alternatives or prerequisites. The description implies bulk usage via '최대 100건' but does not clarify when to choose this tool over calc_depreciation_schedule or calc_tax_adjustment.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calc_depreciation_schedule감가상각 스케줄B
단일 자산의 정액법·정률법·생산량비례법 스케줄(연도별)
| Name | Required | Description | Default |
|---|---|---|---|
| asset_name | Yes | 자산명 | |
| asset_type | Yes | 자산 유형(내용연수 자동참조 시 사용) | |
| industry_code | No | ||
| cost | Yes | 취득가액 | |
| acquired_date | Yes | 취득일 YYYY-MM-DD | |
| method | No | 미입력 시 내용연수 조회 결과의 기본 상각방식 | |
| useful_life_years | No | 미입력 시 업종·자산 기준 표준 내용연수 | |
| total_units | No | ||
| current_units | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so description carries full burden. It only states the calculation without disclosing side effects, permissions, output format, or behavior on invalid inputs. Minimal transparency for a tool with 9 parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with key info (single asset, methods, yearly). Every word is functional, but could be slightly expanded for clarity without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 9 parameters and no output schema, the description fails to explain the schedule's structure (e.g., yearly breakdown columns, totals) or return format. Lacks completeness for a tool of this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 67% (6 of 9 parameters have descriptions). The description does not add meaning beyond schema; it merely lists methods. No explanation of parameter interplay or defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description explicitly states single asset and three depreciation methods (정액법·정률법·생산량비례법) and yearly schedule. The name and description contrast with sibling `calc_bulk_depreciation`, clearly differentiating scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies single-asset usage but does not explicitly state when to choose this over siblings like `calc_bulk_depreciation` or `compare_industry_life`. No when-not or alternative guidance provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calc_tax_adjustment세무조정 참고B
회계 감가상각비 vs 세무 상각범위액 → 손금부인·시인부족·추인(단순모형)
| Name | Required | Description | Default |
|---|---|---|---|
| book_depreciation | Yes | ||
| tax_limit | Yes | ||
| carried_over_denial | No | 전기 이월 손금부인액 |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions the tool computes specific adjustments but does not disclose side effects, return format, error handling, or assumptions. The description is minimal and lacks behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, capturing the core purpose in a single line. However, it is not structured to highlight parameter usage or provide additional context. It is front-loaded but benefits could be improved with parameter mapping.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has three parameters, no output schema, and no annotations, the description is insufficient. It does not explain return values, how to use the carried_over_denial parameter, or any assumptions of the simple model. Context is lacking for an agent to correctly invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only one of three parameters has a description in the schema, and the description does not explain any parameters. The Korean text hints at book depreciation and tax limit but does not map explicitly to the schema parameters. With low schema coverage (33%), the description fails to compensate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool compares accounting depreciation vs tax depreciation limit and computes adjustments like denial, shortfall, and carryforward. It distinguishes from sibling tools like calc_bulk_depreciation and calc_depreciation_schedule which focus on different aspects of depreciation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for tax adjustment calculations but does not explicitly state when to use this tool versus alternatives like calc_bulk_depreciation or get_useful_life. No guidance on prerequisites or exclusions is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
compare_industry_life업종 간 내용연수·상각 비교B
동일 자산·취득가에 대해 업종별 표준 내용연수 및 1년차·5년 누적 상각(비교용)
| Name | Required | Description | Default |
|---|---|---|---|
| asset_type | Yes | ||
| cost | Yes | ||
| industry_codes | Yes | ||
| method | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only states what the tool does without disclosing behavioral traits such as output format, precision, or any side effects. The description does not compensate for the missing annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the purpose. However, it could be slightly more structured by including parameter information without being overly verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 lacks completeness. It does not explain the output format, how results are presented for multiple industries, or additional context needed for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, and the description only vaguely mentions 'asset and acquisition cost' and 'by industry', failing to provide meaningful details about the four parameters, their enumerations, or how to use them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The title and description explicitly state the tool compares standard useful life and depreciation across industries for a given asset and cost. It clearly differentiates from siblings like calc_depreciation_schedule (full schedule) and get_useful_life (single value).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the use case of cross-industry comparison but provides no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_useful_life내용연수 조회B
자산 유형·업종·건물구조 기준 기준내용연수·허용범위·기본 상각방식·법적근거
| Name | Required | Description | Default |
|---|---|---|---|
| asset_type | Yes | 자산 유형 | |
| industry_code | No | KSIC 스타일 코드 (예: Q86, J62). 미입력 시 별표5 공통 | |
| structure | No | 건물(asset_type=building)일 때 구조 |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It does not explicitly state that the tool is read-only, nor does it disclose behavior for missing inputs or errors. The description only lists outputs without behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the key criteria and outputs. No unnecessary words; every element earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a retrieval tool with no output schema, the description lists the four output fields (standard useful life, allowable range, default depreciation method, legal basis), which is fairly complete. Missing details on output format or typical use cases, but overall adequate for simple lookup.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% description coverage, so baseline is 3. The description adds little beyond the schema; it repeats the criteria but does not explain output format or parameter interactions beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the criteria (asset type, industry, building structure) and outputs (standard useful life, allowable range, default depreciation method, legal basis). It distinguishes from sibling calculation tools by being a retrieval tool, but could explicitly state 'lookup' or 'retrieve' for clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. The sibling tools are all calculation-oriented (calc_bulk_depreciation, etc.), but the description does not explicitly direct the agent to use get_useful_life for retrieval and the others for computations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_asset_categories자산 분류 목록B
업종별(또는 공통) 자산 분류·내용연수·상각률 요약
| Name | Required | Description | Default |
|---|---|---|---|
| industry_code | No | ||
| asset_filter | No | ||
| show_rates | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral details such as read-only nature, default behavior with empty parameters, or the scope of data returned. This is a significant gap for a list tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the key purpose. However, it could be more structured with details, but overall it is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of schema descriptions, annotations, and output schema, the description is far from complete. It does not explain parameter usage, output format, or provide enough context for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 0% coverage with no descriptions, and the tool description does not explain any parameter semantics (e.g., industry_code format, asset_filter enum meaning, show_rates effect). The description adds no value beyond parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it provides a summary of asset classifications, useful lives, and depreciation rates by industry (or common), which distinguishes it from sibling calculation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 like calc_depreciation_schedule. Usage is implied as a lookup tool, but no when-not or alternative recommendations are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
6 tool updates
v1.0.0- First observed
calc_bulk_depreciation - First observed
calc_depreciation_schedule - First observed
calc_tax_adjustment - First observed
compare_industry_life - First observed
get_useful_life - First observed
list_asset_categories
TDQS
Scored across 6 tools
Each tool targets a distinct function: bulk calculation, single schedule, tax adjustment, industry comparison, useful life lookup, and category listing. No overlap in purpose.
All tools use snake_case with a consistent verb_noun pattern (calc_, compare_, get_, list_). No mixing of conventions.
6 tools is well-scoped for a depreciation-focused server, covering core calculations, lookups, and comparisons without being excessive.
Covers key operations: schedule calculation, bulk processing, tax adjustment, useful life retrieval, and category listing. Minor gap: no explicit method for depreciation method enumeration, but still highly functional for its purpose.
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