MCP-сервер для REST API XMPie uStore BackOffice по адресу
https://produproduce.mysite.com/ustorebackofficerestapi.
Статус: рабочий, проверен от начала до конца на живом API. Спецификация загружается (52 пути / 63 операции в 15 группах тегов), вход выполняется успешно, и ustore_call_endpoint GET /v1/admin/stores возвращает HTTP 200. Защита от записи корректно отклоняет DELETE.
Сервер не зашивает эндпоинты в код. При первом использовании он загружает собственный документ OpenAPI 3.0 API и предоставляет на его основе пять инструментов:
Инструмент | Назначение |
| Группы контроллеров + количество операций — ознакомительный вызов |
| Поиск/фильтрация операций по тегу, методу или тексту |
| Полный контракт: параметры, тело запроса, форма ответа |
| Выполнение запроса; аутентификация на стороне сервера |
| Диагностика: базовый URL, источник спецификации, режим аутентификации, политика записи |
Это та же схема, что и у MCP-серверов MSSQL (list_databases → list_tables → describe_table → query), и она сохраняет количество инструментов небольшим независимо от того, сколько эндпоинтов предоставляет API. Она также переживает обновления uStore — новые эндпоинты появляются автоматически при следующем обновлении спецификации.
Запись отключена по умолчанию. Методы, отличные от GET, отклоняются, пока на серверном процессе не установлено USTORE_ALLOW_WRITES=true.
Related MCP server: mcp-db-server
Должен работать на хосте с доступом к внутренней сети produproduce.
cd /opt/mcp/ustore-backoffice-mcp
npm install
cp .env.example .env
$EDITOR .env # credentials — the base URL and spec URL are preset
npm run probe # optional: re-confirm the spec URL and auth handshakeРукопожатие аутентификации подтверждено на живом API и уже используется по умолчанию:
POST {base}/v1/admin/auth/login {"email": "...", "password": "..."}
-> 200 {"Token": "..."}
Authorization: uStoreBackoffice <token> # on every subsequent requestОбратите внимание: в теле входа используется email, а не username, а поле токена — с заглавной Token. Схема буквально uStoreBackoffice — API отклоняет любой другой префикс с {"Errors":[{"Message":"Invalid security token."}]}.
URL спецификации также подтверждён и задан заранее:
USTORE_SPEC_URL=https://produproduce.mysite.com/ustorebackofficerestapi/ustore-oas3Его необходимо задать явно — этот деплоймент отдаёт OAS3 по адресу /ustore-oas3, а пути, которые loadSpec() в противном случае опрашивала бы, все возвращают 404.
Затем:
npm run http # or: npm run stdioПроверка:
$ curl -s localhost:8931/healthz
{"ok":true,"target":"https://produproduce.mysite.com/ustorebackofficerestapi"}/healthz доказывает только то, что процесс запущен. Чтобы подтвердить, что часть API работает, вызовите ustore_server_info из клиента — он сообщает выбранную схему аутентификации и количество операций и громко падает, если вход не работает.
pm2 start index.js --name ustore-mcp --node-args="--enable-source-maps"
pm2 save[Unit]
Description=uStore BackOffice MCP server
After=network-online.target
[Service]
Type=simple
User=tc
WorkingDirectory=/opt/mcp/ustore-backoffice-mcp
EnvironmentFile=/opt/mcp/ustore-backoffice-mcp/.env
ExecStart=/usr/bin/node index.js
Restart=on-failure
RestartSec=5
[Install]
WantedBy=multi-user.targetДержите .env с правами chmod 600 — в нём хранятся учётные данные uStore BackOffice, которые являются административными.
Для SSE требуется отключить буферизацию и установить длинный тайм-аут сервера, иначе сеансы обрываются:
backend be_mcp_ustore
mode http
option http-server-close
timeout server 3600s
timeout tunnel 3600s
http-request set-header X-Accel-Buffering no
server ustore1 127.0.0.1:8931 checkОбслуживаются оба транспорта: POST /mcp (Streamable HTTP, текущая спецификация) и GET /sse + POST /messages (унаследованный SSE, совместимый с существующим стеком). Установите MCP_BEARER_TOKEN, если хотите, чтобы сам сервер проверял общий секрет, а не полагался только на ACL HAProxy.
Локальный stdio (Claude Desktop на той же машине):
{
"mcpServers": {
"ustore-backoffice": {
"command": "node",
"args": ["/opt/mcp/ustore-backoffice-mcp/index.js"],
"env": { "MCP_TRANSPORT": "stdio" }
}
}
}Записывайте файл конфигурации в UTF-8 без BOM.
В этом блоке env учётные данные не нужны: сервер читает .env, который находится рядом с index.js. Claude Desktop запускает MCP-серверы с cwd=/ и почти пустым окружением, поэтому config.js ищет .env относительно собственного расположения файла, а не рабочего каталога. Всё, что вы действительно поместите в env, по-прежнему имеет приоритет — реальные переменные окружения имеют приоритет над файлом.
После редактирования конфигурации полностью завершите Claude Desktop (Cmd-Q на macOS, а не просто закройте окно), чтобы процесс сервера был перезапущен.
Область действия учётных данных. Учётные записи BackOffice API обычно имеют полные права администратора. Если uStore поддерживает ограниченную роль оператора, используйте её — защита от записи в этом сервере защищает от случайностей, а не от скомпрометированного токена.
USTORE_ALLOW_PATHS — это список разрешений через регулярное выражение. Его установка сужает сервер до контроллеров, которые вам действительно нужны, что является более сильным контролем, чем один только флаг записи.
Усечение ответа по умолчанию составляет 60 тысяч символов. Если конечная точка списка переполняется, используйте её параметры постраничной навигации, а не увеличивайте лимит — в этом API они называются pageNumber (с 1) и pageSize (по умолчанию 50).
Кэширование спецификации обновляется каждые 15 минут. После обновления uStore вызовите ustore_server_info с refreshSpec: true, чтобы сразу получить изменения.
Сбои аутентификации, которые выглядят как сбои соединения. Сервер запускается и перечисляет свои инструменты, даже если учётные данные отсутствуют — вход происходит только при первом вызове API. Если инструменты появляются, но каждый вызов завершается ошибкой, запустите ustore_server_info и проверьте hasToken.
Это дополняет, а не заменяет SQL MCP-сервер. REST API обеспечивает соблюдение бизнес-логики uStore, поэтому это правильный путь для всего, что изменяет состояние. Прямые запросы [PRODUPRODUCE].ustore остаются лучшими для отчётных объединений и археологии схемы.
Execute a request against the uStore BackOffice REST API. Path placeholders such as {orderId} are filled from pathParams. Authentication is handled by the server. Non-GET methods are refused unless writes are explicitly enabled.
| Name | Required | Description | Default |
|---|---|---|---|
| body | No | JSON request body for POST/PUT/PATCH | |
| path | Yes | Spec path, e.g. /api/Orders/{orderId} | |
| query | No | Query string parameters | |
| method | Yes | GET, POST, PUT, DELETE, PATCH | |
| headers | No | Extra request headers | |
| pathParams | No | Values substituted into {placeholders} |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the burden, and it does add useful behavioral context: authentication is server-side, and non-GET methods are refused unless writes are explicitly enabled. However, it does not clarify what 'explicitly enabled' means, nor does it describe errors, response behavior, 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
Four short sentences deliver the essential facts without filler. The most critical constraints and behaviors are placed up front, and every sentence 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?
The description is adequate for a generic endpoint caller, covering auth, path substitution, and write protection. However, the ambiguous 'writes explicitly enabled' condition and the lack of any guidance about the response format or failure modes leave meaningful gaps for an agent choosing to invoke likely mutating endpoints.
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 complete, but the description adds meaningful context beyond the schema by explaining how pathParams fill placeholders and by adding an operational constraint on the method parameter. This behavior cannot be inferred from the input schema alone.
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 uses a specific action ('Execute a request against the uStore BackOffice REST API') and clearly identifies the target resource and mechanism. It distinguishes the tool from siblings like list_endpoints or describe_endpoint by being the actual invocation tool.
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 intended use—executing a request—is implied by the name and description, but there is no explicit guidance about when to choose this against discovering or describing endpoints. The write-refusal note is a restriction, not a usage guideline with alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Show the full contract for one operation: path/query/header parameters, request body shape, and response shape. Call this before ustore_call_endpoint.
| Name | Required | Description | Default |
|---|---|---|---|
| path | No | e.g. /api/Orders/{orderId} | |
| method | No | Required when path is ambiguous | |
| operationId | No | Alternative to path+method |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description implies a read-only operation (showing the contract) but does not explicitly state that it has no side effects or require permissions. It does add useful behavioral context by explaining what the tool returns and the required sequence, but lacks mention of error behavior or edge cases.
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?
Two concise sentences that front-load the core purpose and then give actionable guidance. No filler or redundancy.
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?
The description covers what the tool returns and its recommended usage sequence. Missing mention of error behaviors or parameter ambiguity resolution, but given its simple role and lack of output schema, it is sufficiently complete for an agent to invoke it 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?
The input schema already provides descriptions for all three parameters with 100% coverageging. The description mentions the contract contents but doesn't add further semantic meaning to the parameters themselves, so baseline 3 is appropriate.
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 'Show the full contract for one operation' and enumerates the contract's contents (path/query/header parameters, request body, response shape). It distinguishes this from sibling tools by tying it to ustore_call_endpoint, making its purpose unambiguous and specific.
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?
It explicitly directs the agent to 'Call this before ustore_call_endpoint', providing a clear temporal use case. It doesn't discuss when not to use it or contrast with list_endpoints, but the core guidance is strong and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List operations in the uStore BackOffice REST API. Filter by tag, HTTP method, or a free-text search across path, operationId and summary.
| Name | Required | Description | Default |
|---|---|---|---|
| tag | No | Restrict to one tag group | |
| limit | No | Default 100 | |
| method | No | GET, POST, PUT, DELETE, PATCH | |
| search | No | Substring match on path/operationId/summary |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of indicating safety and behavior. 'List operations' conveys a read-only action and the filterable fields are stated, but it does not describe pagination behavior, output shape, or authentication expectations. This is acceptable for a simple list tool but not highly transparent.
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 the key action first and filtering capabilities in the second. Every word earns its place; there is no repetition or filler.
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 discovery tool with four fully documented optional parameters and no output schema, the description is largely complete: it states the resource, the filtering dimensions, and implies the fields available in results. It does not add alternative-tool guidance, but given the low complexity, this is a minor gap.
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 100%, so the baseline is 3. The description rephrases tag, method, and search filtering but adds little beyond the schema's parameter descriptions; the search field details are already present in the schema. The limit parameter is left entirely to 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 the tool lists operations in the uStore BackOffice REST API, with a specific verb and resource. It distinguishes itself from siblings like ustore_describe_endpoint, ustore_call_endpoint, and ustore_list_tags by focusing on discovering operations rather than describing, calling, or listing tags.
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 intended use is implied by the purpose — discover API operations and optionally filter them — but the description does not explicitly state when to prefer this tool over alternatives, nor does it mention excluded cases or prerequisites. There is no when/when-not guidance, only the clear listing behavior.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List the tag groups (controllers) exposed by the uStore BackOffice REST API, with the number of operations in each. Start here to orient yourself.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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 clearly identifies the operation as a read-only listing ('List') and specifies what is returned (tag groups with operation counts). It does not mention auth or rate limits, but for a simple zero-parameter list this is not a significant gap.
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, front-loaded with the action and resource, and every sentence earns its place. 'Start here to orient yourself' adds practical guidance without unnecessary verbosity.
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 zero-parameter orientation tool with no output schema, the description is sufficiently complete: it states what is listed, what counts are included, and how to use it as a starting point. It could mention relationship to sibling tools, but this is not essential for the tool's simple purpose.
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 tool has zero parameters and schema description coverage is 100%, so the baseline is 4. The description does not need to add parameter details, and it appropriately focuses on the output and purpose.
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 uses a specific verb ('List') with a clear resource ('tag groups (controllers) exposed by the uStore BackOffice REST API') and adds useful detail ('with the number of operations in each'). It distinguishes itself from sibling tools like list_endpoints and describe_endpoint by focusing specifically on tag groups/controllers.
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?
'Start here to orient yourself' provides clear context for when to use this tool, positioning it as the initial discovery step. However, it does not explicitly name alternatives or state when not to use it, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Report the configured base URL, spec source, auth mode, and write policy. Use this when calls are failing to confirm how the server is wired up.
| Name | Required | Description | Default |
|---|---|---|---|
| refreshSpec | No | Re-fetch the OpenAPI document |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, but description implies a read-only reporting operation. The parameter description covers refreshSpec's side effect (re-fetching OpenAPI), providing adequate transparency.
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?
Two concise sentences: first states purpose, second gives usage context. No redundancy.
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 info tool with one optional parameter and no output schema, the description covers what it does and when to use it, making it complete enough.
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?
Parameter refreshSpec is fully described in the schema (coverage 100%). The main description adds no extra meaning beyond the schema, so baseline 3 is appropriate.
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?
Clearly states it reports the configured base URL, spec source, auth mode, and write policy, distinguishing from sibling tools like list/describe/call endpoints.
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?
Explicitly suggests using when calls are failing to confirm server wiring, but does not mention when not to use or alternatives (though siblings are evident).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.1ustore_call_endpointustore_describe_endpointustore_list_endpointsustore_list_tagsustore_server_infoScored across 5 tools
Each tool has a distinct role: listing tags, listing endpoints, describing a single endpoint, calling an endpoint, and reporting server info. No overlap or ambiguity between them.
Most tools follow a ustore_verb_noun pattern (list_tags, list_endpoints, describe_endpoint, call_endpoint), but server_info deviates by using noun_noun without a verb. This is a minor inconsistency in an otherwise predictable scheme.
Five tools is an ideal count for a focused API client server. Each tool serves a necessary and distinct function, with no bloat or obvious missing piece.
The tool set covers the full workflow: orient (list tags), discover (list endpoints), understand (describe endpoint), and act (call endpoint), plus diagnostics (server info). No critical gaps for interacting with the underlying API.
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