MercadoLibre MCP Server
MercadoLibre MCP 서버
MercadoLibre API에 대한 액세스를 제공하는 MCP 서버입니다.
특징
도구
search_products- MercadoLibre에서 제품을 검색하고 제품 목록을 반환합니다.query- 검색 쿼리category- 검색할 카테고리filters- 적용할 필터
product_reviews- 제품 리뷰 받기product_description- 제품 설명 가져오기seller_reputation- 판매자 평판 가져오기
Related MCP server: Mercado Livre MCP Server
설정
필수 조건
이 서버를 사용하려면 MercadoLibre 클라이언트 ID와 클라이언트 비밀번호가 필요합니다. https://developers.mercadolibre.com/ 에서 무료로 받으실 수 있습니다. 애플리케이션을 생성하고 자격 증명을 받으세요.
자격 증명을 받으면 CLIENT_ID 및 CLIENT_SECRET 환경 변수를 설정할 수 있습니다. 또한 SITE_ID 환경 변수를 사용할 사이트로 설정해야 합니다.
Mercado Libre 사이트 ID
MLA: 아르헨티나(기본)
MLB: 브라질
MCO: 콜롬비아
MEX: 멕시코
MLU: 우루과이
MLC: 칠레
설치
이 서버를 사용하는 방법은 두 가지가 있습니다.
Smithery를 통해 설치
Smithery를 통해 Claude Desktop용 MercadoLibre MCP 서버를 자동으로 설치하려면:
지엑스피1
옵션 1: NPX(권장)
Claude Desktop 구성 파일에 다음 구성을 추가하세요.
{
"mcpServers": {
"mercadolibre-mcp": {
"command": "npx",
"args": [
"-y",
"mercadolibre-mcp"
],
"env": {
"CLIENT_ID": "<YOUR_CLIENT_ID>",
"CLIENT_SECRET": "<YOUR_CLIENT_SECRET>",
"SITE_ID": "<YOUR_SITE_ID>"
}
}
}
}옵션 2: 로컬 설치
저장소를 복제합니다
종속성 설치:
npm install서버를 빌드하세요:
npm run buildClaude Desktop 구성에 다음 구성을 추가하세요.
{
"mcpServers": {
"mercadolibre-mcp": {
"command": "node",
"args": [
"/path/to/mercadolibre-mcp/dist/index.js"
],
"env": {
"CLIENT_ID": "<YOUR_CLIENT_ID>",
"CLIENT_SECRET": "<YOUR_CLIENT_SECRET>",
"SITE_ID": "<YOUR_SITE_ID>"
}
}
}
}디버깅
MCP 서버는 stdio를 통해 통신하므로 디버깅이 어려울 수 있습니다. 패키지 스크립트로 제공되는 MCP Inspector를 사용하는 것이 좋습니다.
npm run inspector검사기는 브라우저에서 디버깅 도구에 액세스할 수 있는 URL을 제공합니다.
기여하다
여러분의 참여를 진심으로 환영합니다! 새로운 MCP 서버나 코드베이스 개선 사항에 대한 PR을 열어주세요.
부인 성명
이 프로젝트는 MercadoLibre와 제휴 관계가 없습니다. 모든 로고는 해당 소유자의 상표입니다.
특허
이 프로젝트는 MIT 라이선스에 따라 라이선스가 부여되었습니다. 자세한 내용은 LICENSE.md 파일을 참조하세요.
Available Tools
3 toolsproduct_descriptionB
Obtiene la descripción de un producto
| Name | Required | Description | Default |
|---|---|---|---|
| productId | No | ID del producto |
TDQS
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 states the action ('obtiene') but doesn't describe whether this is a read-only operation, requires authentication, has rate limits, or what the return format looks like. For a tool with zero annotation coverage, this is a significant gap in 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, efficient sentence in Spanish that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, with zero wasted text, 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?
Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is minimally adequate but has clear gaps. It states what the tool does but lacks behavioral details, usage context, and output information. Without annotations or output schema, the description should provide more complete guidance for effective 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 schema description coverage is 100%, with the single parameter 'productId' documented in the schema as 'ID del producto'. The description doesn't add any additional meaning about parameters beyond what the schema provides, such as format examples or constraints. With high schema coverage, the baseline score of 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 'Obtiene la descripción de un producto' clearly states the verb ('obtiene' - gets) and resource ('descripción de un producto' - product description), making the purpose specific and understandable. However, it doesn't differentiate from sibling tools like 'product_reviews' or 'seller_reputation', which would require mentioning it's specifically for retrieving descriptive information rather than reviews or seller data.
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 provides no guidance on when to use this tool versus alternatives like 'product_reviews' or 'seller_reputation'. It doesn't specify use cases, prerequisites, or exclusions, leaving the agent to infer usage based on tool names alone without explicit direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
product_reviewsC
Obtiene las reseñas de un producto
| Name | Required | Description | Default |
|---|---|---|---|
| productId | No | ID del producto |
TDQS
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 states the tool obtains reviews but doesn't mention whether this is a read-only operation, if it requires authentication, rate limits, error handling, or what the return format looks like (e.g., list, summary, ratings). This leaves significant gaps in understanding how the tool behaves beyond its basic purpose.
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, clear sentence in Spanish ('Obtiene las reseñas de un producto') that directly states the tool's purpose without unnecessary words. It's front-loaded and efficient, making it easy to parse quickly, which is ideal for conciseness in tool descriptions.
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's complexity (simple read operation with one parameter) but lack of annotations and output schema, the description is incomplete. It doesn't explain what the reviews include (e.g., text, ratings, dates), how they're returned, or any behavioral aspects like pagination or errors. For a tool that likely returns data, more context is needed to use it effectively.
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 has 100% description coverage, with 'productId' documented as 'ID del producto'. The description doesn't add any parameter semantics beyond this, such as format examples or constraints. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
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 'Obtiene las reseñas de un producto' clearly states the action (obtains) and resource (product reviews), providing a basic understanding of the tool's function. However, it doesn't differentiate from sibling tools like 'product_description' or 'seller_reputation' beyond the obvious resource difference, lacking specificity about scope or format of the reviews obtained.
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 offers no guidance on when to use this tool versus alternatives like 'product_description' or 'seller_reputation'. It doesn't specify prerequisites, context for usage, or exclusions, leaving the agent to infer usage based solely on the tool name and description without explicit direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
seller_reputationC
Obtiene la reputación de un vendedor
| Name | Required | Description | Default |
|---|---|---|---|
| sellerId | No | ID del vendedor |
TDQS
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 states the tool 'obtains' reputation, implying a read operation, but doesn't disclose behavioral traits like whether it requires authentication, rate limits, error handling, or what the output format might be. For a tool with no annotations, this is a significant gap in 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, efficient sentence in Spanish that directly states the tool's purpose. It's front-loaded with no wasted words, making it highly concise and well-structured for quick understanding.
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 no annotations and no output schema, the description is incomplete. It doesn't explain what 'reputación' entails (e.g., numerical score, textual feedback), how results are returned, or any dependencies. For a tool with minimal structured data, the description should provide more context to be fully helpful.
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 has 100% description coverage, with the parameter 'sellerId' documented as 'ID del vendedor'. The description doesn't add any meaning beyond this, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate as the schema does the heavy lifting.
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 'Obtiene la reputación de un vendedor' clearly states the action (obtains) and resource (seller reputation) in Spanish. It's specific about what the tool does, though it doesn't differentiate from sibling tools like product_description or product_reviews, which focus on different resources. No tautology with the name 'seller_reputation'.
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 provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools or any context for usage, such as prerequisites or scenarios where this tool is appropriate. This leaves the agent with minimal direction.
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.
3 tool updates
- First observed
product_description - First observed
product_reviews - First observed
seller_reputation
TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose targeting different aspects of products and sellers: product_description retrieves product details, product_reviews gets customer feedback, and seller_reputation assesses seller credibility. There is no overlap or ambiguity between these functions.
All tool names follow a consistent snake_case pattern with a clear 'noun_noun' structure (product_description, product_reviews, seller_reputation). This predictable naming makes it easy for agents to understand and select the appropriate tool.
With only 3 tools, the server feels under-scoped for a marketplace domain like MercadoLibre. While the tools cover basic product and seller information, there are likely many other operations (e.g., search, purchase, listing management) that are missing, making the set feel incomplete for comprehensive marketplace interactions.
The tool surface is severely incomplete for a marketplace server. It only provides read-only access to product descriptions, reviews, and seller reputation, with no ability to search for products, create listings, manage orders, or perform other essential marketplace operations. This creates significant gaps that will limit agent functionality.
Maintenance
Related MCP Connectors
Mercado Livre (Latin America's largest marketplace) via the official API, seller profile and reputat
Mercado Libre keyword & competitor intelligence for AI agents across all 18 ML markets.
The Mercado Pago MCP Server implements the Model Context Protocol to provide AI agents and LLMs with access to Mercado Pago's APIs and tools within compatible development environments. It acts as an intermediary that translates Mercado Pago resources into executable functions (tools) that AI applications can invoke to perform actions and automate flows. The server simplifies integration, enables using documentation to implement or improve code, and optimizes operations through natural language interactions without manual implementations.
Amazon search and product extraction: titles, prices, ASINs, and listings as clean JSON.
Related MCP Servers
- AlicenseAqualityCmaintenanceConnects AI agents to MercadoLibre, the largest e-commerce marketplace in Latin America. Search products, get item details, browse categories, track trends, and convert currencies.871 npm4MIT
- AlicenseBqualityDmaintenanceIntegrates with the Mercado Livre API to enable management of sales, shipments, and shipping labels directly through Claude.71MIT
- FlicenseNot gradedqualityCmaintenanceConnects Claude to your MercadoLibre seller account, enabling natural language management of listings, orders, and shipments.-
- AlicenseNot gradedqualityAmaintenanceEnables read-only access to your Mercado Livre buyer account, letting you query purchase history, products, payments, installments, sellers, and download NF-e invoices through natural language.8 npmMIT