mcp-meupc is a Brazilian PC building and price comparison MCP server that lets AI assistants interact with meupc.net — no API keys required. It supports Brazilian Portuguese queries and is optimized for the Brazilian PC building market.
Search PC components by text query (e.g., "rtx 4070", "ryzen 7") with configurable result limits
List components by category with pagination and sorting (by lowest/highest price) across 10 categories: processadores, placas-video, placas-mae, memorias, armazenamentos, gabinetes, fontes, monitores, coolers-processador, and water-coolers
Get full component details including technical specifications, prices per store (PIX and regular pricing), and lowest available price
Browse current deals with discount information and 90-day price history, filterable by category
Explore community PC builds sortable by best-recent, best, or newest, with title, price, and component info
Get detailed build information including the full component list, prices, compatibility checks, and estimated power consumption
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., "@mcp-meupc Encontre o menor preço para um processador Ryzen 7 5700X"
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.
A Model Context Protocol (MCP) server that lets AI assistants search PC components, compare prices across stores, find deals, and explore community builds on meupc.net. No API keys required.
Add the following config to your MCP client:
{
"mcpServers": {
"meupc": {
"command": "npx",
"args": ["-y", "mcp-meupc"]
}
}
}claude mcp add meupc -- npx -y mcp-meupcOr go to Cursor Settings → MCP → New MCP Server and use the config above.
Install via the VS Code CLI:
code --add-mcp '{"name":"meupc","command":"npx","args":["-y","mcp-meupc"]}'Or follow the MCP install guide with the config above.
Add the config above to your claude_desktop_config.json:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
Linux: ~/.config/Claude/claude_desktop_config.json
codex mcp add meupc -- npx -y mcp-meupcFollow the configure MCP guide using the config above.
Follow the Cline MCP configuration guide and use the config above.
Go to Settings | AI | Manage MCP Servers → + Add to add an MCP Server. Use the config above.
Go to Settings | Tools | AI Assistant | Model Context Protocol (MCP) → Add. Use the config above.
Related MCP server: mcp-brazil-marketplaces
Ask your AI assistant to:
"Qual a placa de video mais barata?" — Search components and compare prices
"Quero montar um PC gamer por R$5000" — Explore community builds by budget
"Mostra as ofertas de SSD" — Find current deals with discount history
"Detalha esse Ryzen 7 5800X3D" — Get full specs and prices across stores
Tool | Description |
| Search components by text (e.g. "rtx 4070", "ryzen 7") |
| List components by category with pagination and sorting |
| Full specs and prices per store (PIX and regular) |
| Current deals with discount and 90-day price history |
| Community-shared PC builds |
| Build details: components, prices, compatibility, power consumption |
Supported categories: processadores, placas-video, placas-mae, memorias, armazenamentos, gabinetes, fontes, monitores, coolers-processador, water-coolers
git clone https://github.com/leosebben/mcp-meupc.git
cd mcp-meupc
npm install
npm run build
claude mcp add meupc -- node /path/to/mcp-meupc/build/index.jsnpm run dev # Run with tsx (hot reload)
npm run build # Compile TypeScript
npm start # Run compiled version@modelcontextprotocol/sdk — Official MCP SDK
node-html-parser — HTML parsing
Zod — Schema validation
Detalhes de uma build específica: lista completa de componentes, preços, compatibilidade e consumo estimado
| Name | Required | Description | Default |
|---|---|---|---|
| build_id | Yes | ID da build (ex: 'oI7mI7', extraído da URL /build/{id}) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden of behavioral disclosure. It describes what the tool returns but does not state that the operation is read-only, nor mention authentication or rate limits. The description lacks essential safety cues.
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, well-structured sentence that front-loads the tool's purpose and lists key information included in the output. 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?
Considering no output schema, the description adequately explains the return content (components, prices, compatibility, consumption). It misses some details like format or optional filtering, but for a simple retrieval tool it is reasonably 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?
Schema coverage is 100%, and the schema already describes the parameter effectively. The tool description does not add information about the parameter beyond what is in the schema, so a baseline 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 clearly states it provides details of a specific build, listing components, prices, compatibility, and estimated consumption. This is distinct from sibling tools like list_community_builds (multiple builds) and get_component_details (single component).
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 explicit guidance on when to use this tool versus alternatives. The description does not indicate that this is for a single build or exclude cases where other tools are more appropriate (e.g., searching builds vs. retrieving one).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Detalhes completos de um componente: especificações técnicas, preços por loja (PIX e normal), menor preço
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL do componente (ex: '/peca/W6UIQZ/processador-amd-ryzen-7-5800x3d' ou URL completa) |
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 describes the output content but does not disclose any behavioral traits such as side effects, required authentication, 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the purpose without any 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?
For a simple tool with one parameter and no output schema, the description adequately covers the core functionality. Minor missing details like error handling or pagination are not critical here.
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 100% and the description does not add additional meaning beyond the existing parameter description for 'url'. 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 clearly states it provides complete details of a component including technical specifications and prices. It distinguishes from sibling tools like list_components (which lists multiple) and search_components (which searches).
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 usage for getting details on a single component, but does not explicitly state when to use this versus alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Ofertas atuais com desconto no meupc.net, com preço atual e menor preço em 90 dias
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Número da página | |
| category | No | Filtrar por categoria (ex: 'processadores', 'placas-video', 'memorias') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full burden. It mentions the data returned but lacks details on pagination behavior, whether category filtering is supported (only hinted by schema), or any 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?
A single, well-structured sentence that immediately conveys the tool's purpose and key data points, with no superfluous information.
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 simple nature of a list tool with no output schema, the description covers the essential purpose and data fields. However, it could mention that results are paginated and that the category filter is optional for full completeness.
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 100% with descriptions for both parameters. The description adds context about the tool's output but does not elaborate on parameter usage beyond what the schema already provides.
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 'Ofertas atuais com desconto' (current deals with discount) and specifies the included data (current price, lowest price in 90 days), distinctly differentiating from sibling tools focused on builds and components.
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 context implies use when searching for discounted items on meupc.net, and siblings cover builds/components, but no explicit when-not or alternative naming is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Builds de PC compartilhadas pela comunidade do meupc.net, com título, preço e componentes
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Número da página | |
| sort | No | Ordenação das builds ('melhores-recentes', 'melhores', 'novas') | melhores-recentes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as pagination behavior, rate limits, or what happens if no builds are found. The description only lists what is included in the builds, which is minimal.
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 conveys the essential purpose and content of the builds, with no unnecessary words. It is front-loaded and to the point.
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?
While the tool has only two parameters and no output schema, the description does not explain pagination or sorting behavior. It is adequate for a simple listing but could mention what each build entry contains beyond title, price, and components.
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% coverage with descriptions for both parameters (sort and page). The description does not add any additional meaning beyond what the schema provides, 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.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool lists PC builds shared by the community, including title, price, and components. This distinguishes it from sibling tools like get_build_details (likely for a single build) and component-related tools.
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 explicit when-to-use or when-not-to-use guidance is provided. Usage context is implied by the name and description, but there are no alternatives mentioned or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Lista componentes por categoria com paginação (processadores, placas-video, placas-mae, memorias, armazenamentos, gabinetes, fontes, monitores)
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Número da página | |
| sort | No | Ordenação (ex: 'menor-preco', 'maior-preco') | |
| category | Yes | Categoria de componente (ex: 'processadores', 'placas-video') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It mentions pagination and sorting but lacks details on authentication, rate limits, or what happens on invalid category. The return format is not described.
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, front-loaded sentence that lists important categories. It could be slightly shortened by omitting the category list since it's in the schema, but remains concise.
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 listing tool with no output schema, the description should detail the response structure (e.g., fields of returned items, pagination metadata). It fails to do so, leaving the agent guessing.
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 description adds minimal extra meaning beyond duplicating the category list and mentioning pagination/sorting. Baseline 3 applies.
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 it lists components by category with pagination, and enumerates the available categories. This differentiates it from sibling tools like search_components and get_component_details.
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 usage for listing components filtered by category, but does not explicitly state when not to use it or provide alternatives. However, the category focus is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Busca componentes de PC por texto no meupc.net (processadores, placas de vídeo, memórias, etc.)
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Número máximo de resultados | |
| query | Yes | Texto para buscar componentes (ex: 'rtx 4070', 'ryzen 7') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description does not disclose behavioral traits such as whether the search is case-sensitive, how results are ordered, any rate limits, or the data source's freshness. As a search tool, it should mention if it uses exact or fuzzy matching.
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 efficiently conveys the tool's core function. No redundant or unnecessary words are present.
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 output schema and no annotations, the description is too brief. It does not explain what the response contains (e.g., list of components, IDs, prices) or how to handle errors. For a search tool with only two parameters, it could be more informative.
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 100%, so baseline is 3. The description adds example values for 'query' and explains the 'limit' parameter, but this adds only minor value beyond the schema's own descriptions.
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 searches PC components by text on meupc.net, listing specific component types. It effectively differentiates from siblings like 'list_components' which likely lists all, and 'get_component_details' for details.
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 when to use (search by text) but does not explicitly state when not to use or mention alternatives. The sibling context provides indirect differentiation, but direct guidance is lacking.
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.
v1.0.0get_build_detailsget_component_detailsget_dealslist_community_buildslist_componentssearch_componentsEach tool has a clearly distinct purpose: retrieving details for builds and components, listing community builds, searching components, listing components by category, and getting deals. No ambiguity between them.
All tools follow a consistent verb_noun pattern in snake_case (e.g., get_build_details, list_components, search_components). The naming is uniform and predictable.
With 6 tools, the server is well-scoped for its purpose of providing PC component and build information. Neither too few nor too many.
The tool surface covers all essential operations for browsing PC components and builds: listing, searching, getting details, viewing community builds, and checking deals. No obvious gaps for a read-only information service.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
PC hardware decision engine for Brazil (pt-BR): compatibility, GPU recommendations, build analysis.
# MCP DadosBR Servidor MCP focado em dados públicos do Brasil. Oferece duas ferramentas simples e…
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