Click on "Deploy 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., "@horoshop-mcp-server list orders from today"
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 unofficial MCP server for stores built on Horoshop.
This project connects AI agents, internal assistants, and MCP-compatible clients to the Horoshop API through a practical Model Context Protocol server. It is designed for teams that run e-commerce operations on Horoshop and want language models to interact with store data in a controlled, tool-based way.
This project is not affiliated with, endorsed by, or maintained by Horoshop. It is a community-built integration for the Horoshop ecosystem.
Horoshop gives merchants a hosted e-commerce platform at horoshop.ua, but AI tools still need a reliable way to access store operations such as orders, catalog data, and order status updates. MCP is a good fit for that layer because it lets LLMs call clearly defined tools instead of improvising against raw APIs.
This server turns the Horoshop API into MCP tools that can be used from clients like Claude Desktop, Cursor, and other agent frameworks that support MCP over stdio.
Related MCP server: SellerChamp MCP Server
This server is useful when you want AI to do real operational work around a Horoshop store, for example:
customer support assistants that look up an order, confirm its current status, and hand back structured answers to an operator
back-office agents that review new orders and move them into the next processing state
catalog helpers that inspect product data before content updates or merchandising tasks
internal dashboards where AI can answer questions like "show me the latest orders from today" or "find the product by ID and summarize its current state"
automation flows that need a safe bridge between natural-language prompts and Horoshop API methods
store operations copilots that combine Horoshop data with CRM, ERP, shipping, or analytics tooling
The current implementation provides a compact but useful starting point:
authenticates against the Horoshop API using either a token or login/password credentials
exposes MCP tools for listing and fetching orders
exposes MCP tools for listing and fetching products
supports updating order status from an MCP client
includes a generic passthrough tool for calling arbitrary Horoshop API functions
This gives you enough to start with real workflows while keeping the codebase small enough to extend quickly.
With this MCP server, an agent can support workflows such as:
"Find order 12345 and tell me whether it has already moved to the shipped status."
"List the newest orders and summarize which ones need manual attention."
"Fetch product 9876 and prepare a short product brief for a support manager."
"Update order 12345 to status 7 after warehouse confirmation."
"Call a custom Horoshop API function that is not wrapped yet, then return the raw payload for inspection."
Copy .env.example to .env and configure:
HOROSHOP_BASE_URL: your Horoshop store domain, for example https://your-store.example.com
HOROSHOP_LOGIN: API login created in the Horoshop admin panel
HOROSHOP_PASSWORD: API password created in the Horoshop admin panel
HOROSHOP_TOKEN: optional token if you already use token-based access
You need either:
HOROSHOP_TOKEN
or:
HOROSHOP_LOGIN
HOROSHOP_PASSWORD
npm installnpm run build
npm startFor development:
npm run dev{
"mcpServers": {
"horoshop": {
"command": "node",
"args": [
"D:/usr/www/mcp-dev/horoshop/dist/index.js"
],
"env": {
"HOROSHOP_BASE_URL": "https://your-store.example.com",
"HOROSHOP_LOGIN": "api-login",
"HOROSHOP_PASSWORD": "api-password"
}
}
}
}horoshop_auth: verify authentication and confirm token access
horoshop_list_orders: list orders using Horoshop order export functions
horoshop_get_order: fetch one order by ID
horoshop_list_products: list products using Horoshop catalog export functions
horoshop_get_product: fetch one product by ID
horoshop_update_order_status: change the status of an order
horoshop_call_api: call any Horoshop API function with arbitrary JSON parameters
This project is a strong fit for:
Horoshop merchants who want AI assistants to work with store operations
agencies building AI-enabled tooling for Horoshop clients
developers integrating Horoshop into MCP-based automation stacks
teams that want a base server they can customize for their own business rules
This repository focuses on the operational core first: authentication, orders, products, status updates, and a raw API escape hatch.
That means it is intentionally useful on day one, but not yet a complete wrapper for the full Horoshop API surface. The generic horoshop_call_api tool is included specifically so you can validate store-specific behavior and extend the server safely as new requirements appear.
The server assumes the Horoshop API endpoint pattern:
https://<domain>/api/<function>/
If your store exposes different function names or request shapes than the defaults currently wrapped in this repository, use horoshop_call_api first and then extend src/index.ts.
Horoshop website: https://horoshop.ua/
Authenticates with Horoshop and returns token metadata.
| Name | Required | Description | Default |
|---|---|---|---|
| force_refresh | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It says 'Authenticates' and 'returns token metadata' but does not disclose side effects (e.g., session creation, token storage), whether it is idempotent, or any rate limits or permissions needed. This is insufficient for an auth operation.
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 immediately states the core action and outcome. 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 the tool is simple (one optional parameter, no output schema), the description should still explain what authentication entails, what token metadata is returned, and the role of force_refresh. It does none of these, leaving the agent with significant 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 schema has one boolean parameter 'force_refresh' with no description, and schema description coverage is 0%. The description does not mention this parameter at all, so the agent receives no guidance on its meaning or when to set it. The description fails to compensate for the lack of schema documentation.
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 authenticates with Horoshop and returns token metadata, using a specific verb ('Authenticates') and resource ('Horoshop'). This clearly distinguishes it from sibling tools that list/get/update orders and products.
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 is provided on when to use this tool versus alternatives like 'horoshop_call_api', which could also be used for auth endpoints. The description implies it is for authentication but does not state prerequisites, sequencing, or when force_refresh should be used.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Calls any Horoshop API function with arbitrary JSON parameters.
| Name | Required | Description | Default |
|---|---|---|---|
| params | No | ||
| function_name | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for disclosing behavior. It fails to mention authentication needs, potential mutation effects, rate limits, error handling, or response format. A generic 'calls any function' gives no indication of safety, side effects, or required prerequisites, making it opaque for an agent.
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 is direct and free of unnecessary words. It conveys the essential purpose without padding, achieving high 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?
For a generic API caller with no annotations and no output schema, the description is severely incomplete. It lacks information about the set of available functions, authentication requirements, return values, error behavior, and relationship to sibling tools. The complexity of a dynamic API caller demands far more context than this one-liner provides.
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 two parameters (function_name and params) with no descriptions (0% coverage). The description adds minimal value beyond labeling parameters as 'arbitrary JSON parameters.' It does not explicitly explain that function_name is the API method name or that params are the arguments, leaving interpretation to inference. The description fails to compensate for the schema's lack of detail.
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 states the tool's function clearly: 'Calls any Horoshop API function with arbitrary JSON parameters.' It identifies the verb (calls), resource (Horoshop API functions), and scope (any, arbitrary). This distinguishes it from sibling tools that target specific endpoints, though it could better emphasize its role as a generic/low-level fallback.
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 is provided on when to use this tool versus the specific sibling tools (e.g., horoshop_get_order, horoshop_update_order_status). The description does not mention that this is a general-purpose tool for functions not covered by dedicated wrappers, nor does it give any context for when it should be preferred or avoided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns a single order by id using the Horoshop API.
| Name | Required | Description | Default |
|---|---|---|---|
| order_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so description must carry full behavioral burden. It states 'returns' but does not confirm read-only nature, authentication requirements, error handling, or response format beyond the basic operation.
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, direct sentence with no wasted words. Front-loaded with action and resource.
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 one-parameter get operation, the description is minimally sufficient. However, without output schema or annotations, it leaves ambiguity about the exact shape of the returned order and error conditions.
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 0% description coverage for order_id. Description only says 'by id', not adding details on format, type variations, or how to obtain the id. Fails to compensate for lack of schema documentation.
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 uses specific verb 'returns' and resource 'single order by id', clearly distinguishing from sibling tools like horoshop_list_orders (multiple orders) and horoshop_get_product.
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?
Implied usage: use when you need a specific order by its id. Does not explicitly mention alternatives or exclusions compared to horoshop_list_orders or other siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns a product by id using the Horoshop API.
| Name | Required | Description | Default |
|---|---|---|---|
| product_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the core operation and does not mention error behavior (e.g., not found), authentication requirements, response format, or any side effects. This is insufficient for a tool with zero annotation coverage.
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 and is efficient. However, the phrase 'using the Horoshop API' is redundant given the tool name and adds no value, preventing a perfect score.
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 get-by-id tool, the description provides the essential purpose, but with no output schema, no annotations, and no usage guidance, it leaves gaps around return shape, error cases, and prerequisites. It is minimally viable for a low-complexity tool but not fully complete.
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 shows a single parameter, product_id, with 0% description coverage. The description's phrase 'by id' adds a minimal level of meaning by confirming that product_id is the identifier, but it does not explain accepted formats, constraints, or how to handle the number/string union. It partially compensates for the schema gap.
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 action ('Returns'), the resource ('a product'), and the key qualifier ('by id'). This distinguishes it from sibling tools like horoshop_list_products (which lists products) and horoshop_get_order (which fetches an order).
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 tool should be used when a specific product_id is known, but it does not explicitly state when to use it over alternatives or mention any exclusions. No guidance on prerequisites like authentication is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns orders using the Horoshop orders/export endpoint.
| Name | Required | Description | Default |
|---|---|---|---|
| filters | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description must disclose behavioral traits. It only says 'returns orders' and provides no information about filtering, pagination, response format, or side effects. This is insufficient transparency for a data-fetching 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, efficient sentence with no wasted words. It is front-loaded with the main action. However, its brevity contributes to missing critical details, so it earns a 4 rather than a 5.
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 tool has no annotations, no output schema, and a single undocumented parameter. The description does not compensate for these gaps, lacking essential context such as how filters work, what the response looks like, or any prerequisites. Incomplete for effective agent use.
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 sole parameter 'filters' is an open object with no description in the schema (0% coverage). The description does not mention filters or explain how to use them, leaving the agent completely in the dark about acceptable filter structure.
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 'Returns orders' and names the exact endpoint (orders/export), making it clear this lists orders. It distinguishes from sibling horoshop_get_order, which implies fetching a single order, and horoshop_list_products.
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. It doesn't mention criteria like listing all orders versus a single order, or when to use list_products instead. Only a bare statement of functionality.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns products using the Horoshop catalog/export endpoint.
| Name | Required | Description | Default |
|---|---|---|---|
| filters | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosure. It only says 'Returns products using the Horoshop catalog/export endpoint,' but does not mention pagination, filter behavior, authentication requirements, or the shape of the response. The endpoint name provides mild context but not sufficient behavioral 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?
The description is a single concise sentence with no filler. It front-loads the primary action (returns products) and the data source. Every word contributes to the meaning, making it highly concise and well-structured.
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 tool has a complex 'filters' object parameter and no output schema, but the description provides no information about filter options, response format, pagination, or limits. This is insufficient for an agent to correctly invoke the tool with meaningful filters or interpret results.
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 one optional 'filters' object with no description, and the description does not mention filtering at all. With 0% schema coverage, the agent receives no semantic information about the sole parameter, making it unusable.
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 states 'Returns products' with a specific endpoint, clearly identifying the tool's function as listing products. The plural 'products' and endpoint name distinguish it from sibling tools like horoshop_get_product (single product) and horoshop_list_orders (orders).
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 is provided on when to use this tool versus alternatives. It does not mention that this is for bulk listing or that horoshop_get_product is for individual products, nor does it specify any prerequisites or use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Updates an order status using the Horoshop API.
| Name | Required | Description | Default |
|---|---|---|---|
| order_id | Yes | ||
| status_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description adds no behavioral context beyond restating the action. It does not mention authentication requirements, side effects, whether the operation is idempotent, or what is returned upon success or failure.
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, but it is under-specified. The phrase 'using the Horoshop API' is filler that adds no value, and the description lacks the detail needed to be useful despite its 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?
As a mutation tool with no output schema and no annotations, the description must convey return values, errors, and prerequisites. It covers none of these, making it severely inadequate for an agent to invoke 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?
Schema description coverage is 0%, and the description does not explain the meaning of order_id or status_id. The agent receives no additional context about what status_id represents or what valid values exist, leaving the parameters effectively undocumented.
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's action: 'Updates an order status' with a specific verb and resource. It distinguishes from sibling tools like horoshop_list_orders and horoshop_get_order through the explicit update verb, though it does not name alternatives.
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 is provided on when to use this tool versus horoshop_call_api or other order-related siblings. There is no mention of prerequisites, sequencing, or scenarios that would favor this tool over alternatives.
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.
v0.1.0horoshop_authhoroshop_call_apihoroshop_get_orderhoroshop_get_producthoroshop_list_ordershoroshop_list_productshoroshop_update_order_statusScored across 7 tools
Most tools are clearly distinct (list vs get, orders vs products), and auth is separate. However, horoshop_call_api is a catch-all that could overlap with any tool, introducing some ambiguity about when to use it versus the specific tools.
All tools follow the consistent pattern horoshop_ + verb + noun (e.g., list_orders, get_order, update_order_status). The only minor deviation is horoshop_auth, but it is still a recognizable action and fits the style.
With 7 tools, the count is well-scoped for a typical e-commerce API integration. Each tool covers a distinct core operation without unnecessary bloat or sparseness.
The core workflows for orders (list, get, update status) and products (list, get) are covered. Missing product creation/update and order creation are notable, but the horoshop_call_api fallback fills these gaps, making the surface reasonably complete.
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