Which integrations are available for this server?

Provides tools to discover DTC brands and search products on Shopify. Provides tools to discover DTC brands and search products on WooCommerce. Provides tools to discover DTC brands and search products on WordPress (WooCommerce).

How do I use dentro MCP?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@dentro MCP Find me a sustainable tote bag under $30" 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.

dentro MCP

Official

by dentro-fyi

Overview Schema Related Servers Score Discussions

JavaScript

Remote

dentro MCP

Structured commerce data for AI agents. One MCP server, 22,000+ DTC brands, real-time product data, no scraping, no hallucination.

npm version MCP License: MIT

What it does

Lets any MCP-compatible agent (Claude Desktop, Cursor, custom agents) query a curated registry of 22,000+ DTC e-commerce brands across 16 countries. Five tools, all returning clean JSON:

discover_companies — find brands by natural-language query
search_products — search products within a brand, real prices and stock
get_product — full product detail with variants, images, descriptions
list_categories — browse a brand's category tree
get_site_info — brand metadata and agent instructions

Related MCP server: Commerce MCP Server

Why use it

Without dentro	With dentro
Agent web-searches Google, scrapes 10 storefronts, hallucinates prices	One tool call, structured JSON, real data
30+ second latency, 50K+ tokens	Sub-second, ~2K tokens
Generic results dominated by Amazon	Curated DTC brands, agent-optimized

Install

npm install -g @dentro-fyi/mcp

Get an API key at dentro.fyi (free tier available).

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "dentro": {
      "command": "npx",
      "args": ["-y", "@dentro-fyi/mcp"],
      "env": {
        "DENTRO_API_KEY": "your-key-here"
      }
    }
  }
}

Restart Claude Desktop. Try: "Find me a sustainable tote bag under $30."

Cursor / other MCP clients

Same config shape. Any MCP-compatible client can use it.

Example

You: I need merino wool socks for hiking, ideally American-made.
Claude: [calls discover_companies({query: "merino wool hiking socks American-made"})]
        [finds: Darn Tough, Smartwool, Farm to Feet]
        [calls search_products({company_id: "darn-tough", query: "merino hiking"})]
        Here are 3 options from Darn Tough, all in stock, made in Vermont...

Coverage

22,173 brands across 16 countries
4 verified platforms (Shopify, WooCommerce, WordPress, Magento) plus custom connectors
Tier 1 (verified): full product API
Tier 2 (listed): structured data only
Tier 3 (directory): brand info only

Pricing

Free tier: 100 requests/day, all tools
Paid tiers: higher limits, priority discovery, attribution analytics
See dentro.fyi/pricing

Resources

Docs: dentro.fyi/docs
API reference: dentro.fyi/api
Issues: github.com/dentro-fyi/dentro-mcp/issues
Contact: hello@dentro.fyi

License

MIT.

Available Tools

5 tools

discover_companiesA

Find e-commerce companies in the Dentro network that match a natural language query. Returns ranked matches with company IDs to use in subsequent product searches. Use this first when the user asks about a product type or brand.

ParametersJSON Schema

Name	Required	Description
`limit`	No	Max results (1-50). Default 10.
`query`	Yes	Natural-language description of what you are looking for (e.g. "sustainable tote bags", "merino wool socks for men")
`category`	No	Optional category filter (e.g. "apparel", "footwear")

TDQS

A4/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses the core behavior (search companies, return ranked IDs) and the network scope. However, it does not mention rate limits, authentication needs, or other side effects. The description is adequate but not rich in behavioral detail.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two sentences with no wasted words. The first sentence covers purpose and output, the second gives usage guidance. It is well-structured and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and no annotations, the description adequately explains the tool's function, input, and output (company IDs). It also relates to sibling tools via the usage hint. Minor absence: not detailing the format of the ranked matches beyond IDs, but still sufficient for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

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 adds context for the query parameter ('natural-language query') and the overall goal, but it does not provide additional meaning beyond the schema's existing descriptions for limit and category.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool finds e-commerce companies matching a natural language query and returns ranked matches with company IDs. It distinguishes from siblings by explicitly advising use when the user asks about a product type or brand, setting it apart from product search tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit when-to-use guidance ('Use this first when the user asks about a product type or brand') and explains the output's role in subsequent product searches. However, it lacks explicit statements about when not to use it or direct alternatives beyond the implied sequence.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_productA

Get full details for a specific product — all variants, images, descriptions, stock, pricing.

ParametersJSON Schema

Name	Required	Description	Default
`company_id`	Yes
`product_id`	Yes	Product ID or slug from search results

TDQS

A4.2/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, description carries full burden. It discloses it returns variants, images, descriptions, stock, pricing. This is transparent for a read operation, though no mention of side effects (likely none). Could be clearer about read-only nature, but still strong.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single, front-loaded sentence with no filler. Every word adds meaning (Get, full details, specific product, enumerated fields). Ideal conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has 2 simple required params, no output schema, no nested objects. Description covers main return fields. For a straightforward retrieval operation, it is complete enough. Could mention if product_id supports other formats, but not a major gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 50% (company_id no description, product_id described). Description doesn't elaborate on company_id or how to obtain it. Product_id description matches schema ('ID or slug from search results'). Baseline is 3 given moderate coverage; description adds minimal extra value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states 'Get full details for a specific product' with specific verb (get) and resource (product), and enumerates attributes (variants, images, descriptions, stock, pricing). This distinguishes it from sibling tools like search_products (searching) and list_categories (categories).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when needing full product details, and sibling tool names provide context for alternatives. No explicit when-not-to-use guidance, but for a simple retrieval tool, context is sufficient.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_site_infoB

Get metadata about a company — platform, agent instructions (cookie banners, country selectors, etc.), available tools.

ParametersJSON Schema

Name	Required	Description	Default
`company_id`	Yes

TDQS

B3.1/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, and the description only states 'Get metadata' without disclosing behavioral traits such as read-only nature, destructive potential, authentication requirements, 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that efficiently conveys the tool's purpose. However, it could be slightly expanded to include the company_id parameter explanation without losing conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one parameter, no output schema, no annotations), the description provides a reasonable overview. However, it lacks details about the company_id parameter and potential return structure, making it only minimally adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema describes 'company_id' as a required string with no description (0% coverage). The tool description does not explain what the company_id represents or how to obtain it, leaving the parameter's semantics unclear.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get metadata about a company' and lists specific metadata types (platform, agent instructions, available tools), distinguishing it from siblings like discover_companies or search_products.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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 like discover_companies, or when not to use it. The description does not mention preconditions or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_categoriesA

List all product categories / collections for a specific company. Useful for browsing.

ParametersJSON Schema

Name	Required	Description	Default
`company_id`	Yes

TDQS

A3.9/5.0

Behavior3/5

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 listing all categories but doesn't address pagination, result format, or potential side effects. 'List' implies read-only, but more detail on limits or ordering would improve transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences efficiently state purpose and usage context. Every word serves a purpose with no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple list tool with one parameter and no output schema, the description covers the essential: what it returns, the required parameter, and a use case. Minor omissions like whether results are ordered or limited do not significantly hinder completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It only says 'for a specific company' about company_id, adding minimal meaning beyond the schema's type 'string' and requirement. No format, validation, or example is provided.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'List' and the resource 'product categories / collections' with scope 'for a specific company'. It effectively distinguishes from sibling tools like search_products and get_product which focus on individual items or different operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes 'Useful for browsing' which implies suitable for exploratory contexts. However, it lacks explicit when-not-to-use guidance or alternatives, though the sibling tools provide natural differentiators.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search_productsA

Search for products within a specific company. Returns real-time data: name, price, stock status, variants, direct product URL. Call after discover_companies to find specific products at the matched brand.

ParametersJSON Schema

Name	Required	Description
`limit`	No	Max results (1-50). Default 10.
`query`	Yes	What to search for (e.g. "polarized sunglasses", "black dress")
`company_id`	Yes	Company ID from discover_companies (e.g. "knockaround", "allbirds")

TDQS

A4.2/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Despite no annotations, the description discloses key behavioral traits: returns real-time data and lists fields (name, price, stock status, variants, URL). Could mention more (e.g., rate limits, pagination), but current coverage is solid.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the core purpose. Every word earns its place; no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Adequately describes returns and provides usage context. With no output schema, missing details on pagination/sorting. Sibling context is leveraged. Overall near-complete for a search tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and parameter descriptions are already clear in the schema. The tool description adds no additional semantic detail beyond the schema, so baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's action ('Search for products'), resource ('within a specific company'), and provides differentiation from siblings by mentioning real-time data and specifying it is for finding specific products at the matched brand.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly advises to call after discover_companies, providing clear sequence context. However, it does not explicitly state when not to use or mention alternatives like list_categories for browsing.

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. Dates show when Glama detected each change.

5 tool updatesv0.1.1Jul 28, 2026
- First observeddiscover_companies
- First observedget_product
- First observedget_site_info
- First observedlist_categories
- First observedsearch_products

Install Server

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

A4/5.0

Disambiguation5/5

Each tool has a clearly distinct function: discovering companies, searching products within a company, getting product details, listing categories, and retrieving site metadata. No overlap.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with underscores, using descriptive verbs like discover, search, get, list.

Tool Count5/5

With 5 tools, the server is well-scoped for its purpose of exploring e-commerce companies and their products. Each tool is necessary and the count fits within the ideal 3-15 range.

Completeness4/5

The tool surface covers the core workflow: discover companies, browse categories, search products, and get details. Missing direct listing of all companies, but the natural language query mechanism serves that purpose well.

Maintenance

ActivityInactive

ResponsivenessSyncing

Resources

Need Help?

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dentro MCP

What it does

Why use it

Install

Claude Desktop

Cursor / other MCP clients

Example

Coverage

Pricing

Resources

License

Available Tools

Tool Schema Changelog

Maintenance

Resources

Looking for Admin?

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