mcp-egrul
mcp-egrul
MCP 서버(Model Context Protocol — AI 어시스턴트를 외부 도구에 연결하기 위한 오픈 프로토콜)로, EGRUL(러시아 연방 법인 통합 국가 등록부) 및 EGRIP(러시아 연방 개인 사업자 통합 국가 등록부) 작업을 수행합니다. 데이터 소스는 FTS(연방 세무청)의 공식 오픈 데이터 덤프입니다.
상태: v0.1.2 — 오픈 버전(SQLite를 통한 self-host)이 완전히 준비되었으며, hosted Pro 클라이언트 부분( api.atomno.ru용 HTTP 클라이언트 HostedClient)도 포함되어 있습니다. PyPI에 게시되었으며 Glama 및 Smithery에 인덱싱되어 있습니다. hosted Pro 인프라 자체는 활발히 개발 중입니다. 커버리지 100.00% (345개 테스트, ruff clean, fastmcp 3.2.4, --cov-fail-under=100으로 강제).
연동 프로젝트: mcp-fns-check (EGRUL 기반의 리스크 체크 레이어).
기능
AI 어시스턴트(Cursor, Claude Desktop, Cline, 모든 MCP 클라이언트)에서 볼 수 있는 7가지 MCP 도구:
도구 | 설명 | 인수 |
| INN으로 검색 (10자리 - 법인, 12자리 - 개인 사업자) |
|
| OGRN(13) 또는 OGRNIP(15)으로 검색 |
|
| 이름으로 퍼지 검색 (FTS5) |
|
| 모든 섹션이 포함된 전체 카드 |
|
| 지분을 포함한 설립자 정보만 |
|
| 현재 대표자 정보만 |
|
| 대량 확인 (최대 100개 INN) |
|
서버 상태 확인을 위한 ping 도구가 포함되어 있습니다.
페이로드 전체 사양은 src/mcp_egrul/schemas.py (Pydantic 모델 CompanyCard, IECard, SearchResult, BulkResult)를 참조하세요.
Related MCP server: onec-meta-mcp
설치
옵션 1 — PyPI를 통한 설치 (사용자 권장)
# Без локального clone — работает «из коробки»
uvx atomno-mcp-egrul
# Или установка глобально
pipx install atomno-mcp-egrul
atomno-mcp-egrul
# Или классический pip в venv
pip install atomno-mcp-egrul
atomno-mcp-egrul옵션 2 — 개발 모드 (개발자용)
Python 3.11+ 및 uv(pip의 빠른 대체제, 선택 사항)가 필요합니다.
git clone https://github.com/atomno-labs/mcp-egrul
cd mcp-egrul
uv venv
uv pip install -e ".[dev]"pip를 통한 대안:
python -m venv .venv
.venv/Scripts/activate # Windows
# source .venv/bin/activate # Linux/macOS
pip install -e ".[dev]"실행
atomno-mcp-egrul기본 전송 방식은 stdio(표준 JSON-RPC 입출력)입니다. Cursor / Claude Desktop / Claude Code 연결에 적합합니다.
Claude Desktop (claude_desktop_config.json)
{
"mcpServers": {
"egrul": {
"command": "uvx",
"args": ["atomno-mcp-egrul"]
}
}
}Cursor (프로젝트 내 .cursor/mcp.json 또는 전역 ~/.cursor/mcp.json)
{
"mcpServers": {
"egrul": {
"command": "uvx",
"args": ["atomno-mcp-egrul"]
}
}
}
uv를 사용하지 않는 경우,"command": "uvx", "args": ["atomno-mcp-egrul"]을"command": "atomno-mcp-egrul"로 교체하세요 (pip install atomno-mcp-egrul또는pipx install atomno-mcp-egrul필요).
Docker (self-host) — 빠른 시작
# 1. Скачайте дампы ФНС (acceptance на сайте ФНС — раз в жизни).
# Источники:
# ЕГРЮЛ — https://www.nalog.gov.ru/opendata/7707329152-egrul/
# ЕГРИП — https://www.nalog.gov.ru/opendata/7707329152-egrip/
# Положите их в структуру:
mkdir -p dumps/egrul/2026-04-24 dumps/egrip/2026-04-24
cp ~/Downloads/EGRUL_*.zip dumps/egrul/2026-04-24/
cp ~/Downloads/EGRIP_*.zip dumps/egrip/2026-04-24/
# 2. Первоначальный полный импорт (однократно, ~30-60 минут):
docker compose --profile import run --rm \
mcp-egrul-import atomno-mcp-egrul-import --registry egrul --full
docker compose --profile import run --rm \
mcp-egrul-import atomno-mcp-egrul-import --registry egrip --full
# 3. Запустите сервер + фоновый cron-демон:
docker compose up -d
docker compose logs -f mcp-egrul-scheduler가져오기 후 약 10분 뒤 모든 도구(search_by_inn, search_by_name 등)가 로컬 FTS 데이터로 응답합니다.
컨테이너 내부 /data 볼륨 구조:
/data/
├── mcp_egrul_data.sqlite # SQLite + FTS5
└── dumps/ # read-only монтируется из ./dumps
├── egrul/
│ └── YYYY-MM-DD/*.zip
└── egrip/
└── YYYY-MM-DD/*.zipCron 데몬(atomno-mcp-egrul-scheduler)은 dumps/<registry>/<YYYY-MM-DD>/에 파일을 넣으면 매일 03:00(Europe/Moscow 기준)에 최신 덤프를 자동으로 가져옵니다. 새로운 데이터가 없으면 작업은 nothing_to_import로 종료되며 import_log에 불필요한 기록을 남기지 않습니다.
FTS 덤프 가져오기 (수동 모드)
소스:
EGRUL open-data:
https://www.nalog.gov.ru/opendata/7707329152-egrul/EGRIP open-data:
https://www.nalog.gov.ru/opendata/7707329152-egrip/
형식: ZIP 내 일일 XML 아카이브, 전체 덤프 약 15GB. 법적으로 FTS 웹사이트에서 라이선스 동의 후 다운로드해야 합니다. 서버는 아카이브를 직접 다운로드하지 않습니다.
CLI:
# Полный первоначальный импорт (однократно):
atomno-mcp-egrul-import --registry egrul --full
atomno-mcp-egrul-import --registry egrip --full
# Инкремент (cron / ручной): загружается только если появилась более
# свежая YYYY-MM-DD-папка, чем последний успешный `import_log.source_dump_date`.
# Если новее нет — exit-code 5 и сообщение `nothing_to_import`.
atomno-mcp-egrul-import --registry egrul --incremental
# Фоновой cron-демон с ежедневным 03:00 MSK (вызывать вручную редко;
# обычно запускается сервисом mcp-egrul-scheduler в docker-compose).
atomno-mcp-egrul-scheduler --run-nowatomno-mcp-egrul-import 종료 코드:
코드 | 의미 |
0 | 가져오기 성공 |
2 | 잘못된 설정 / CLI 인수 |
4 | 수집 오류 (손상된 XML, 덤프 디렉토리 없음, DB 오류) |
5 |
|
Pro / hosted 모드 (api.atomno.ru 프록시)
ATOMNO_API_KEY가 설정되면 7가지 도구 모두가 자동으로 hosted Pro API로 프록시됩니다(SPEC §5.4, §5.4.1). 이 모드에서는 로컬 SQLite가 사용되지 않으며, hosted Pro는 다음을 제공합니다:
오늘 기준 최신 데이터 (오픈 데이터 덤프의 일일 지연 없음):
egrul.nalog.ru직접 스크래핑 + 서버 측 Dadata 폴백.Rate-limit 없는 Bulk 엔드포인트 (
POST /companies/bulk) — N개의 로컬 gather 대신 단일 요청.AI 카드 요약, 변경 이력, 대표자 이름 검색 (Pro 전용 도구 — Phase 2에서 hosted 서버와 함께 제공, §5.4.1 참조).
가격: Pro — 월 $10 또는 mcp-fns-check와 번들 시 월 $15. Free tier: 등록 없이 IP당 일일 30회 요청(SPEC §1).
Cursor 설정 (.cursor/mcp.json):
{
"mcpServers": {
"egrul": {
"command": "uvx",
"args": ["atomno-mcp-egrul"],
"env": {
"ATOMNO_API_KEY": "your-pro-key-here"
}
}
}
}동작 및 오류 — silent fallback은 없습니다. hosted API를 사용할 수 없는 경우 클라이언트는 오래된 로컬 덤프에서 데이터를 가져오는 대신 타입이 지정된 예외를 발생시킵니다. HTTP ↔ MCP 오류 코드 매핑은 SPEC §5.4.1을 참조하세요:
hosted API HTTP 응답 | 클라이언트 예외 |
|
200 | — | — |
400 |
|
|
401 |
|
|
403 |
|
|
404 (code=not_found) |
|
|
404 (wrong route) |
|
|
413 |
|
|
429 |
|
|
5xx |
|
|
timeout / DNS fail |
|
|
INN/OGRN 검증은 클라이언트 측에서 수행됩니다 (잘못된 식별자로 인한 불필요한 HTTP 요청 방지).
설정 (환경 변수)
변수 | 설명 | 기본값 |
| EGRUL/EGRIP 덤프가 포함된 SQLite 파일 경로 |
|
| HTTP 클라이언트 User-Agent |
|
| HTTP 타임아웃 (초) |
|
| FTS 덤프 디렉토리, 구조 |
|
| 로그 레벨 |
|
| 스케줄러용 시간대 (cron 03:00) |
|
| (Pro) hosted 구독 키 — | 설정 안 됨 |
| (Pro) hosted API 기본 URL |
|
예시는 .env.example을 참조하세요.
구조
apps/mcp-egrul/
├── pyproject.toml
├── LICENSE # MIT
├── README.md # ЭТОТ ФАЙЛ
├── Dockerfile
├── docker-compose.yml
├── .env.example
├── .gitignore
├── src/mcp_egrul/
│ ├── __init__.py
│ ├── server.py # FastMCP entrypoint, регистрация 7 тулзов + ping
│ ├── context.py # ServiceContext (DI: SQLiteStore + HTTP-клиент)
│ ├── config.py # Чтение env-vars в типизированные поля
│ ├── constants.py # Все магические числа и enum'ы
│ ├── validators.py # Контрольные цифры ИНН (10/12) и ОГРН (13/15)
│ ├── schemas.py # Pydantic-модели CompanyCard/IECard/SearchResult/...
│ ├── errors.py # McpEgrulError и подклассы
│ ├── db/
│ │ ├── __init__.py
│ │ └── sqlite.py # Async-клиент (aiosqlite), init/query/upsert/search + import_log
│ ├── sources/
│ │ ├── __init__.py
│ │ ├── base.py # Абстрактный интерфейс Source
│ │ ├── opendata.py # ФНС open-data адаптер (read-local → SQLite upsert)
│ │ ├── opendata_parser.py # Потоковый lxml.iterparse парсер ЕГРЮЛ/ЕГРИП XML
│ │ └── hosted_adapter.py # HTTP-клиент hosted Pro API (SPEC §5.4.1)
│ ├── tools/
│ │ ├── __init__.py
│ │ ├── search_by_inn.py
│ │ ├── search_by_ogrn.py
│ │ ├── search_by_name.py
│ │ ├── get_full_card.py
│ │ ├── get_founders.py
│ │ ├── get_director.py
│ │ └── bulk_cards.py
│ └── scripts/
│ ├── __init__.py
│ ├── import_opendata.py # CLI `atomno-mcp-egrul-import` (ручной / одноразовый)
│ └── scheduler.py # CLI `atomno-mcp-egrul-scheduler` (apscheduler cron 03:00 MSK)
└── tests/
├── __init__.py
├── conftest.py
├── fixtures/
│ ├── egrul_sample.xml # Мини-ЕГРЮЛ (2 валидных + 1 skip на неизвестный статус)
│ └── egrip_sample.xml # Мини-ЕГРИП (active + closed)
├── test_validators.py
├── test_schemas.py
├── test_config.py # Config.from_env + _parse_float_env (валидация env)
├── test_sqlite_store.py
├── test_cards.py # _cards.py: parse_iso_date/datetime + build_*card
├── test_server_ping.py # FastMCP tool-layer + server.main()
├── test_tools.py # 7 тулзов: happy-path + validation + not_found
├── test_opendata_parser.py # XML-парсер (zip, xml, skip-на-неизвестный-статус)
├── test_opendata_source.py # OpenDataSource.run_ingest (full/incremental)
├── test_integration_import.py # Полный цикл import → search → get_card
├── test_import_cli.py # CLI `atomno-mcp-egrul-import`
├── test_scheduler_cli.py # CLI `atomno-mcp-egrul-scheduler` + _run_scheduler
└── test_hosted_adapter.py # HostedClient + маршрутизация тулзов (respx-моки)테스트
pytest -v --cov=src/mcp_egrul현재 커버리지: 100.00% (345 tests passed, ruff clean, 1529 statements + 382 branches, 0 misses). --cov-fail-under=100 정책으로 강제되어 회귀 발생 시 CI가 실패합니다. 테스트 범위:
INN/OGRN/OGRNIP 검증기 (체크섬);
Config.from_env+ float-env 변수 파서;7가지 MCP 도구 전체 (happy-path + validation + not_found + bulk partial);
SQLite store + FTS5 +
import_log;EGRUL/EGRIP XML 파서 (zip, xml, 알 수 없는 상태의 레코드 건너뛰기);
OpenDataSource.run_ingest(full/incremental/nothing_to_import);전체 통합 주기
import fixture → search → get_card → bulk;CLI 2종 (
atomno-mcp-egrul-import,atomno-mcp-egrul-scheduler) — cron-job 등록, 인수 파싱,_run_daily_ingest전체 주기,_run_scheduler(mock-edasyncio.Event포함);FastMCP 도구 레이어 — 오류 직렬화,
server.main()환경 변수 검증;HostedClient(hosted Pro API proxy) — 7개 메서드 전체, SPEC §5.4.1의 모든 HTTP 오류, 타임아웃/ConnectError, 잘못된 JSON/페이로드, 클라이언트 측 bulk 검증,async with컨텍스트; hosted 모드에서의 도구 라우팅;XML 파서 엣지 케이스 (75개의 개별 단위 테스트);
SQLite 스토어 프라이빗 헬퍼;
ServiceContext재진입성,atexit정리,Config.from_envValidationError → CLI 종료 코드 2.
외부 API는 테스트에서 직접 호출되지 않으며, respx(HTTP 모킹)와 로컬 XML 픽스처(tests/fixtures/)를 통해서만 수행됩니다.
보안 및 법적 상태
모든 소스는 FTS의 공개 데이터(EGRUL / EGRIP open-datasets)이며, 러시아 연방 법률에 따라 배포가 허용됩니다(SPEC §8 참조).
법인은 152-FZ(개인정보 보호법)의 적용을 받지 않습니다.
대표자 및 설립자의 성명은 FTS가 직접 공개하는 정보이므로 전송이 합법적입니다.
외부 API에 대한 쓰기 작업은 없습니다.
보안 정보는 환경 변수를 통해서만 관리하며, 리포지토리에는 값이 없는
.env.example만 포함됩니다.
면책 조항
본 서비스는 FTS 공개 데이터에 대한 집계 및 편리한 인터페이스입니다. FTS와 제휴되어 있지 않습니다. 사용자의 책임하에 사용하십시오. 서비스 응답 정보는 전문적인 법률 또는 재무 평가를 대체하지 않습니다.
라이선스
MIT. 루트 폴더의 LICENSE 파일을 참조하세요.
Available Tools
8 toolsbulk_cardsA
Массовая выгрузка до 100 карточек за один вызов.
Вернёт объект с полями cards (успешные) и errors (точечные ошибки
по отдельным ИНН) — один плохой ИНН не ломает весь bulk.
| Name | Required | Description | Default |
|---|---|---|---|
| inns | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses important behavioral aspects like returning both successful cards and per-TIN errors, and that one bad TIN doesn't break the whole call. However, it omits whether the operation is read-only or has side effects, and no mention of authorization or rate limits.
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 two short sentences with no fluff. The first sentence front-loads the core purpose and capacity, and the second explains the return structure and error handling. Every word contributes value.
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 simple input schema (one parameter) and the existence of an output schema (not provided but implied), the description sufficiently covers maximum batch size, return format (cards/errors), and partial failure behavior. It is complete for its 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?
Although the schema has no description for the 'inns' parameter, the description mentions 'отдельным ИНН' (individual TINs), clarifying that the array contains Russian tax identifiers. With 0% schema coverage, the description adds meaning beyond the raw schema.
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 performs a massive upload of up to 100 cards per call, specifying the action (выгрузка) and resource (карточек). It distinguishes itself from siblings like search_by_inn by handling multiple INNs and returning partial errors.
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 indicates usage for batch card retrieval with a capacity limit of 100, but does not explicitly state when not to use it or list alternatives. However, the context of sibling tools and the capacity hint provide implicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_directorB
Текущий руководитель юр.лица по ИНН (только 10-значный ИНН).
| Name | Required | Description | Default |
|---|---|---|---|
| inn | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states it returns the current director, but fails to mention aspects like error handling, data freshness, auth requirements, or side effects. This is insufficient.
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 sentence, very concise and front-loaded with the key action and constraint. Every word earns its place, though it could be slightly expanded for additional clarity without losing brevity.
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 simple single-parameter tool and the existence of an output schema, the description is minimally adequate but lacks details on edge cases or error responses. It covers the basic purpose but not the full context of 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. The tool description adds value by specifying that the INN must be exactly 10 digits. However, it doesn't fully compensate for missing schema descriptions, e.g., no mention of format beyond digit count.
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 retrieves the current director of a legal entity by INN. It specifies the exact resource (director), action (get), and constraint (10-digit INN for legal entities). This distinguishes it from siblings like get_founders or search_by_inn.
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 does not provide any guidance on when to use this tool versus alternatives such as get_founders or search_by_inn. It only describes what it does without contextual or comparative usage advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_foundersB
Учредители юр.лица по ИНН (только 10-значный ИНН).
| Name | Required | Description | Default |
|---|---|---|---|
| inn | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It only mentions the TIN length constraint but does not disclose whether this is a read-only operation, error handling, or any 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that conveys the core purpose and a key constraint without any unnecessary words. It is efficiently structured and front-loaded.
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 presence of an output schema (not shown), the description does not need to detail return values. However, it lacks information on error handling, input validation details, or the structure of the founders data, which could be incomplete for an agent.
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 input schema has 0% description coverage, leaving the 'inn' property undocumented. The description adds the crucial constraint that only a 10-digit TIN is accepted, which is valuable beyond the schema definition.
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 retrieves founders of a legal entity by TIN and specifies the requirement of a 10-digit TIN. This distinguishes it from siblings like get_director which targets a different role.
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 over alternatives like search_by_inn or get_director. It does not state prerequisites or exclusions, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_full_cardA
Полная карточка (все секции: реквизиты, ОКВЭД, учредители, директор).
Хотя бы один из inn / ogrn обязателен. Если переданы оба — используется inn.
| Name | Required | Description | Default |
|---|---|---|---|
| inn | No | ||
| ogrn | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
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 discloses that at least one of inn/ogrn is required and inn takes precedence, but does not mention read-only nature, authentication needs, or error handling for missing 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?
The description is two sentences and front-loads the purpose. It is concise with no unnecessary words, though structure could be improved with bullet points for clarity.
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 presence of an output schema and only two parameters, the description covers the primary requirements: purpose and parameter constraints. It lacks mention of error cases or usage limitations, but is largely complete for a simple 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?
The input schema has 0% description coverage, but the description adds meaning by clarifying that inn and ogrn are alternative identifiers, at least one is mandatory, and inn is used if both are provided. This significantly compensates for the schema's lack of parameter descriptions.
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 explicitly states 'Full card (all sections: details, OKVED, founders, director)', clearly indicating it retrieves a complete company card. This distinguishes it from sibling tools like get_director and get_founders, which target specific sections.
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 retrieving full card data, but does not explicitly contrast with siblings or state when to use this tool over alternatives like search_by_inn or get_director. No exclusion criteria or context is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pingA
Диагностика: сервер жив, сообщает версию и размер локального слепка.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description takes full burden. It discloses that the tool reports version and snapshot size, which is useful. However, it does not mention read-only nature, safety, or potential side effects, though for a ping tool these 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that front-loads the main purpose ('Диагностика') and immediately specifies what the tool reports. No wasted words.
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 zero parameters, an output schema exists (not shown but referenced), and a set of sibling tools, the description is complete for this simple tool: it tells the agent exactly what the tool returns and its role as a health check.
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?
There are zero parameters, so the description need not add parameter info. Baseline for zero parameters is 4, and the description appropriately focuses on the tool's output rather than parameters.
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 is for diagnostics: checking server liveness, version, and snapshot size. It uses a specific verb ('диагностика') and resource ('сервер'), and is distinct from sibling tools that handle cards, directors, or searches.
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 health checks but does not explicitly state when to use this tool vs alternatives, nor does it mention exclusions or prerequisites. Given the clear purpose, usage is implied but not guided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_by_innA
Карточка юр.лица или ИП по ИНН (10 цифр — ООО/АО, 12 — ИП/физлицо).
| Name | Required | Description | Default |
|---|---|---|---|
| inn | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must cover behavioral traits. It only states the searchby TIN and format, omitting any details on error handling, rate limits, or return behavior.
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 extremely concise (one short phrase) and front-loaded with the core purpose, containing no wasted words.
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 simple lookup tool with an output schema, the description is minimally complete but lacks details on error cases and what the card contains, leaving some gaps.
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 input schema has no parameter descriptions (0% coverage), but the description adds critical semantic meaning by explaining the TIN length and entity mapping, significantly aiding correct usage.
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 returns a card of a legal entity or individual entrepreneur by TIN, and distinguishes it from siblings by specifying TIN format (10/12 digits) and entity types.
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 this tool is for TIN-based lookup, distinct from siblings like search_by_name or search_by_ogrn, but provides no explicit when-to-use or when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_by_nameB
Fuzzy-поиск юр.лиц по названию через FTS5.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | максимум результатов (1..50). | |
| query | Yes | строка запроса (минимум 2 символа). | |
| only_active | No | фильтровать только записи со статусом 'active'. |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions fuzzy search via FTS5 but omits details like matching behavior, result ordering, or handling of misspellings.
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, concise but lacking structure. It could benefit from additional context without being lengthy.
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 annotations and only input schema provided, the description omits important behavioral traits and result format expectations. Even with an output schema, more context would be helpful.
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 coverage is 100% with descriptions for all parameters. The description adds no new meaning beyond 'fuzzy', so baseline 3 applies.
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 clearly states it is a fuzzy search of legal entities by name using FTS5, which is specific and distinguishes from siblings like search_by_inn and search_by_ogrn.
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. It implicitly targets name-based searches, but without stating exclusions or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_by_ogrnB
Карточка по ОГРН (13 цифр) или ОГРНИП (15 цифр).
| Name | Required | Description | Default |
|---|---|---|---|
| ogrn | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavior. It only states what the tool does (retrieve a card) but omits details about error handling, side effects, or what happens for invalid inputs. This is insufficient for an agent to fully anticipate behavior.
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 sentence, which is highly concise and front-loaded. However, it could be structured with separate sentences for clarity, but for a simple tool it is appropriately sized.
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 existence of an output schema (not shown), the description may not need to detail return values. It provides the parameter format but lacks any mention of error handling or usage context. For a simple lookup tool, it is minimally adequate.
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, so the description must compensate. It adds meaningful format constraints: 13 digits for OGRN and 15 digits for OGRNIP, which is valuable beyond the plain string type in the schema.
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 that the tool retrieves a card by OGRN (13 digits) or OGRNIP (15 digits), making the purpose and resource specific. It distinguishes itself from sibling tools like search_by_inn and search_by_name by indicating the identifier type.
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 offers no explicit guidance on when to use this tool versus alternatives or when not to use it. The context is only implied by the tool name and description, with no mention of prerequisites or exclusions.
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.
8 tool updates
v0.1.2- First observed
bulk_cards - First observed
get_director - First observed
get_founders - First observed
get_full_card - First observed
ping - First observed
search_by_inn - First observed
search_by_name - First observed
search_by_ogrn
TDQS
Scored across 8 tools
Each tool targets a distinct query type: bulk export, specific fields (director, founders), full card, health check, and three search methods (INN, name, OGRN). No overlapping purposes.
Most tools use a verb_noun pattern (get_director, get_founders, search_by_inn, etc.). Ping and bulk_cards are minor deviations but still clear.
Eight tools cover a complete set of operations for a business registry: multiple search methods, specific field lookups, bulk export, and health check. No extraneous tools.
Covers essential read operations for a registry: search by various identifiers, retrieval of full cards and specific fields, bulk export. Missing filtering or advanced search (e.g., by region) but acceptable for a focused server.
Maintenance
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