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@striderlabs/mcp-yelp

@striderlabs/mcp-yelp

MCP server connector for Yelp - the leading platform for local business discovery. Enables AI agents to search restaurants, read reviews, view photos, check hours, find deals, and discover trending spots.

Installation

npm install @striderlabs/mcp-yelp

Related MCP server: Yelp Fusion AI MCP Server

Configuration

Add to your MCP client configuration:

{
  "mcpServers": {
    "yelp": {
      "command": "npx",
      "args": ["@striderlabs/mcp-yelp"]
    }
  }
}

Available Tools

Tool

Description

yelp_search_restaurants

Search restaurants by location, cuisine, price

yelp_search_businesses

Search any type of business

yelp_get_business_details

Get detailed business information

yelp_get_reviews

Get reviews with ratings and text

yelp_get_photos

Get business photos by category

yelp_get_menu

Get restaurant menu items and prices

yelp_get_hours

Get business hours

yelp_find_similar

Find similar businesses

yelp_get_trending

Get trending/new spots in a location

yelp_get_collections

Get curated Yelp collections

yelp_check_wait_time

Check estimated wait time

yelp_get_deals

Get current deals and offers

Example Usage

// Search for sushi restaurants
const results = await client.call("yelp_search_restaurants", {
  query: "sushi",
  location: "San Francisco, CA",
  priceRange: "$$",
  sortBy: "rating"
});

// Get business details
const details = await client.call("yelp_get_business_details", {
  businessId: "nobu-san-francisco"
});

// Read reviews
const reviews = await client.call("yelp_get_reviews", {
  businessId: "nobu-san-francisco",
  sortBy: "newest",
  limit: 20
});

// Get restaurant photos
const photos = await client.call("yelp_get_photos", {
  businessId: "nobu-san-francisco",
  category: "food"
});

// Find trending restaurants
const trending = await client.call("yelp_get_trending", {
  location: "San Francisco, CA",
  category: "restaurants"
});

Features

  • Restaurant Search: Filter by cuisine, price, distance, ratings

  • Business Discovery: Search for any type of local business

  • Reviews: Access user reviews with ratings and photos

  • Photos: Browse food, interior, and exterior photos

  • Menus: View menu items with prices

  • Hours: Get operating hours including special hours

  • Trending: Discover hot new spots

  • Collections: Access curated "best of" lists

  • Deals: Find current promotions and offers

Requirements

  • Node.js 18+

License

MIT

Available Tools

6 tools
yelp_get_dealsB

Get current deals and offers for businesses in a location.

ParametersJSON Schema
NameRequiredDescriptionDefault
categoryNoBusiness category
locationYesLocation to search

TDQS

B3.1/5.0
Behavior2/5

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

No annotations provided, and the description does not disclose any behavioral traits (e.g., rate limits, authorization, 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.

Conciseness4/5

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

Single sentence, no wasted words, but could benefit from slightly more structure or detail.

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

Completeness2/5

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

No output schema and no description of return format or pagination; incomplete for a search-like tool with multiple siblings.

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?

Both parameters ('location' and 'category') are described in the schema (100% coverage), so the description adds no additional meaning beyond schema.

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 retrieves 'current deals and offers for businesses in a location,' distinguishing it from siblings like yelp_get_hours or yelp_get_menu.

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; lacks context or exclusions.

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

yelp_get_hoursA

Get business hours including special hours and holidays.

ParametersJSON Schema
NameRequiredDescriptionDefault
businessIdYesYelp business ID

TDQS

A3.5/5.0
Behavior3/5

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

Without annotations, the description carries full burden. It states it returns business hours including special/holiday hours, but does not disclose error handling, rate limits, data freshness, or response structure. This is adequate but not rich.

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 a single sentence that is clear and concise, with no unnecessary words. Every word earns its place.

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?

The tool is simple with one required parameter and no output schema. However, the description lacks details on return format, error scenarios, or data structure (e.g., days of week). Given no annotations, it is moderately complete but could be more informative.

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 the parameter 'businessId' already has a description in the schema ('Yelp business ID'). The tool description adds no further meaning beyond what the schema provides, so baseline 3 applies.

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 'Get' and the resource 'business hours', and specifies inclusion of special hours and holidays. It is distinct from sibling tools (deals, menu, reviews, etc.) which cover other aspects.

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 is provided on when to use this tool versus alternatives, prerequisites, or context such as needing a valid business ID. The description is purely functional.

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

yelp_get_menuB

Get menu items and prices for a restaurant.

ParametersJSON Schema
NameRequiredDescriptionDefault
businessIdYesYelp business ID

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states 'Get menu items and prices', implying a read operation, but does not explicitly confirm no side effects, permissions needed, or rate limits. An agent might need to assume it's safe, but the description lacks explicit 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?

The description is a single, concise sentence that directly states the tool's purpose with no unnecessary words. It is front-loaded and efficient.

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?

For a simple read tool with one parameter and no output schema, the description is functional but minimal. It does not describe the structure of the returned data (e.g., list of items with names and prices), which would improve completeness. Given the low complexity, a score of 3 is adequate but not exceptional.

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?

The input schema has 100% coverage with a description for the only parameter (businessId: 'Yelp business ID'). The tool description adds no additional meaning beyond the schema, so a 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 function: retrieving menu items and prices for a restaurant. The verb 'Get' and resource 'menu items and prices' are specific, and the tool is easily distinguished from siblings (e.g., yelp_get_reviews, yelp_get_hours) by its focus on menu data.

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 is provided on when to use this tool versus alternatives. The description does not mention prerequisites, when-not-to-use, or mention sibling tools. The agent must infer usage solely from the tool name and description.

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

yelp_get_reviewsB

Get reviews for a specific business with ratings and text.

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of reviews to retrieve
sortByNoSort reviews by
businessIdYesYelp business ID

TDQS

B3.4/5.0
Behavior3/5

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

No annotations provided, so description carries burden. It discloses returning reviews with ratings and text, but omits pagination behavior (limit parameter) and does not mention that results are a list. Minimal but not misleading.

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?

Single sentence with no fluff, efficiently conveying the core purpose. Could include more detail without sacrificing conciseness, but currently it is appropriately sized.

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 has 3 parameters, no output schema, and is a read operation, the description is adequate but lacks explicit mention of pagination, sorting, and the fact it returns a list. Gaps remain.

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%, so parameters are already described. The description adds no extra meaning beyond what is in the schema, meeting baseline.

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 'Get', resource 'reviews', and what is returned ('ratings and text'), distinguishing it from sibling tools like yelp_get_deals or yelp_get_hours.

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. The description does not mention scenarios or prerequisites, leaving the agent to infer usage from context.

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

yelp_search_businessesC

Search for any type of business on Yelp (not just restaurants).

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query (e.g., 'plumber', 'hair salon')
categoryNoBusiness category
locationYesLocation (city, neighborhood, or address)

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description must bear the full burden of disclosing behavioral traits. It only states the action (search) without describing what the tool returns, whether it has side effects, or any constraints (e.g., rate limits, pagination). For a search tool, the lack of output format details is 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.

Conciseness4/5

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

The description is extremely concise at one sentence with no wasted words. While it could benefit from additional context, it does not contain any filler or redundancy, earning a high score for efficiency.

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

Completeness2/5

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

Given the absence of an output schema and annotations, the description is insufficiently complete. It does not explain the result format, any default behavior (e.g., ordering, limits), or how it complements sibling tools like yelp_get_reviews. An agent would have to infer many details from the tool name alone.

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?

The input schema already has 100% parameter description coverage, providing clear meaning for all three parameters (query, category, location). The description adds no extra information about the parameters, so it meets the baseline expectation without exceeding it.

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

Purpose4/5

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

The description states the tool searches for any type of business on Yelp and explicitly clarifies it is not limited to restaurants, which distinguishes it from a common assumption. However, it does not specify that the search uses query and location parameters, leaving some ambiguity about how the search is performed.

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 is provided on when to use this tool versus its siblings (yelp_get_deals, yelp_get_hours, etc.). The description does not mention prerequisites, limitations, or alternative tools, leaving the agent to infer the appropriate context from the tool name and siblings alone.

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.

  1. 6 tool updatesv0.1.0
    • First observedyelp_get_deals
    • First observedyelp_get_hours
    • First observedyelp_get_menu
    • First observedyelp_get_reviews
    • First observedyelp_get_trending
    • First observedyelp_search_businesses

TDQS

A3.5/5.0
Disambiguation5/5

Each tool targets a distinct aspect of Yelp data: deals, hours, menu, reviews, trending, and general search. There is no overlap in purpose, so an agent can clearly distinguish them.

Naming Consistency4/5

All tools start with 'yelp_' and use a verb_noun pattern, but 'search_businesses' uses 'search' instead of 'get', which is a minor deviation. Overall, the naming is predictable and readable.

Tool Count5/5

With 6 tools, the set is well-scoped for a Yelp MCP server. It covers core read operations without unnecessary bloat, fitting the typical use cases for a Yelp integration.

Completeness4/5

The tools cover search, reviews, hours, menu, deals, and trending, which are key read operations. A minor gap is the lack of a dedicated business detail tool, but search likely covers basic info. Write operations are not expected.

Maintenance

ActivityInactive
ResponsivenessSyncing

Resources

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