Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@ustore-backoffice-mcp List all pending orders in uStore"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
An MCP server for the XMPie uStore BackOffice REST API at
https://produproduce.mysite.com/ustorebackofficerestapi.
Status: working, verified end to end against the live API. The spec loads
(52 paths / 63 operations across 15 tag groups), login succeeds, and
ustore_call_endpoint GET /v1/admin/stores returns HTTP 200. The read-only
guard correctly refuses DELETE.
The server does not hardcode endpoints. On first use it fetches the API's own OpenAPI 3.0 document and exposes five tools over it:
Tool | Purpose |
| Controller groups + operation counts — the orientation call |
| Search/filter operations by tag, method, or text |
| Full contract: params, request body, response shape |
| Execute a request; auth handled server-side |
| Diagnostics: base URL, spec source, auth mode, write policy |
This is the same shape as the MSSQL MCP servers (list_databases →
list_tables → describe_table → query), and it keeps the tool count low
regardless of how many endpoints the API exposes. It also survives uStore
upgrades — new endpoints appear automatically on the next spec refresh.
Writes are disabled by default. Non-GET methods are refused until
USTORE_ALLOW_WRITES=true is set on the server process.
Related MCP server: mcp-db-server
Must run on a host with internal network access to 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 handshakeThe auth handshake is confirmed against the live API and is already the default:
POST {base}/v1/admin/auth/login {"email": "...", "password": "..."}
-> 200 {"Token": "..."}
Authorization: uStoreBackoffice <token> # on every subsequent requestNote the login body uses email, not username, and the token field is
capital-Token. The scheme is literally uStoreBackoffice — the API rejects any
other prefix with {"Errors":[{"Message":"Invalid security token."}]}.
The spec URL is likewise confirmed and preset:
USTORE_SPEC_URL=https://produproduce.mysite.com/ustorebackofficerestapi/ustore-oas3It must be set explicitly — this deployment serves OAS3 at /ustore-oas3, and
the paths loadSpec() would otherwise probe all return 404.
Then:
npm run http # or: npm run stdioVerify:
$ curl -s localhost:8931/healthz
{"ok":true,"target":"https://produproduce.mysite.com/ustorebackofficerestapi"}/healthz only proves the process is up. To confirm the API leg works, call
ustore_server_info from a client — it reports the resolved auth scheme and the
operation count, and it fails loudly if login is broken.
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.targetKeep .env at chmod 600 — it holds a uStore BackOffice credential, which is
an administrative one.
SSE needs buffering off and a long server timeout, or sessions get cut:
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 checkBoth transports are served: POST /mcp (Streamable HTTP, current spec) and
GET /sse + POST /messages (legacy SSE, matching the existing stack). Set
MCP_BEARER_TOKEN if you want the server itself to check a shared secret rather
than relying on HAProxy ACLs alone.
Local stdio (Claude Desktop on the same box):
{
"mcpServers": {
"ustore-backoffice": {
"command": "node",
"args": ["/opt/mcp/ustore-backoffice-mcp/index.js"],
"env": { "MCP_TRANSPORT": "stdio" }
}
}
}Write the config file as UTF-8 without a BOM.
No credentials are needed in that env block: the server reads the .env that
sits next to index.js. Claude Desktop launches MCP servers with cwd=/ and a
near-empty environment, so config.js resolves .env against its own file
location rather than the working directory. Anything you do put in env
still wins — real environment variables take precedence over the file.
After editing the config, fully quit Claude Desktop (Cmd-Q on macOS, not just closing the window) so the server process is relaunched.
Credential scope. BackOffice API accounts are typically full admin. If uStore supports a limited operator role, use one — the read-only guard in this server protects against accidents, not against a compromised token.
USTORE_ALLOW_PATHS is a regex allowlist. Setting it narrows the server to
the controllers you actually need, which is a stronger control than the write
flag alone.
Response truncation defaults to 60k characters. If a listing endpoint
overflows, use its paging parameters rather than raising the cap — this API
spells them pageNumber (1-based) and pageSize (default 50).
Spec caching refreshes every 15 minutes. After a uStore upgrade, call
ustore_server_info with refreshSpec: true to pick up changes immediately.
Auth failures that look like connection failures. The server starts and
lists its tools even when credentials are missing — the login only happens on
the first API call. If tools appear but every call errors, run
ustore_server_info and check hasToken.
This complements, not replaces, the SQL MCP server. The REST API enforces
uStore's business logic, so it is the right path for anything that mutates
state. Direct [PRODUPRODUCE].ustore queries remain better for reporting joins
and schema archaeology.
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. Dates show when Glama detected each change.
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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