A
licenseA
qualityC
maintenanceA Model Context Protocol server that provides real-time web search capabilities to AI assistants through pluggable search providers, currently integrated with the Brave Search API.
5
16
MIT
Brave Search MCP Server
by arben-adm
Brave Search MCP 서버
이 프로젝트는 Brave Search를 위한 MCP(Model Context Protocol) 서버를 구현하여 Claude와 같은 AI 도우미와의 통합을 가능하게 합니다.
필수 조건
파이썬 3.11+
uv - 빠른 Python 패키지 설치 및 확인 프로그램
Related MCP server: Brave Search MCP Server
설치
Smithery를 통해 설치
Smithery를 통해 Claude Desktop에 Brave Search MCP 서버를 자동으로 설치하려면:
지엑스피1
수동 설치
저장소를 복제합니다.
git clone https://github.com/your-username/brave-search-mcp.git cd brave-search-mcpuv를 사용하여 가상 환경을 만들고 종속성을 설치합니다.
uv venv source .venv/bin/activate # On Windows, use: .venv\Scripts\activate uv pip install -r requirements.txtBrave Search API 키를 설정하세요:
export BRAVE_API_KEY=your_api_key_hereWindows에서는 다음을 사용하세요:
set BRAVE_API_KEY=your_api_key_here
용법
MCP 설정 파일(예:
claude_desktop_config.json)을 구성하여 Brave Search MCP 서버를 포함합니다.{ "mcpServers": { "brave-search": { "command": "uv", "args": [ "--directory", "path-to\\mcp-python\\brave-mcp-search\\src", "run", "server.py" ], "env": { "BRAVE_API_KEY": "YOUR_BRAVE_API_KEY_HERE" } } } }YOUR_BRAVE_API_KEY_HERE실제 Brave API 키로 바꾸세요.업데이트된 구성으로 MCP 호환 AI 어시스턴트를 실행하여 Brave Search MCP 서버를 시작합니다.
이제 서버가 실행되어 MCP 클라이언트의 요청을 수락할 준비가 되었습니다.
이제 MCP 호환 AI 비서(예: Claude)에서 사용 가능한 도구를 호출하여 Brave Search 기능을 사용할 수 있습니다.
사용 가능한 도구
서버는 두 가지 주요 도구를 제공합니다.
brave_web_search: Brave Search API를 사용하여 웹 검색을 수행합니다.brave_local_search: 지역 업체와 장소를 검색합니다.
자세한 사용 정보는 src/server.py 에 있는 도구 docstring을 참조하세요.
개발
프로젝트를 변경하려면:
필요에 따라
src디렉토리의 코드를 수정합니다.종속성을 추가하거나 제거하는 경우
requirements.txt파일을 업데이트하세요.uv pip freeze > requirements.txt변경 사항을 적용하려면 서버를 다시 시작하세요.
문제 해결
문제가 발생할 경우:
Brave API 키가 올바르게 설정되었는지 확인하세요.
모든 종속성이 설치되었는지 확인하세요.
호환되는 Python 버전을 사용하고 있는지 확인하세요.
코드를 변경한 경우 서버를 다시 시작하세요.
특허
이 프로젝트는 MIT 라이선스에 따라 라이선스가 부여되었습니다. 자세한 내용은 라이선스 파일을 참조하세요.
Available Tools
2 toolsbrave_local_searchC
Search for local businesses and places
Args:
query: Location terms
count: Results (1-20
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| count | No |
TDQS
C2.7/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'Search' implies a read-only operation, it doesn't specify authentication requirements, rate limits, data sources, or what happens when no results are found. The description provides minimal behavioral context 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately concise with a clear purpose statement followed by parameter explanations. The formatting with 'Args:' section is helpful, though the incomplete 'Results (1-20' text suggests a typographical error that slightly detracts from professionalism.
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?
For a search tool with 2 parameters, 0% schema description coverage, no annotations, and no output schema, the description is insufficient. It doesn't explain what information is returned, result format, error conditions, or how this differs from the sibling web search tool, leaving significant gaps for an AI agent.
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 provides basic explanations for both parameters ('Location terms' for query, 'Results (1-20' for count), but these are minimal and don't explain format expectations, what constitutes valid 'Location terms', or how the count parameter works with the default value of 20.
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 clearly states the tool's purpose as 'Search for local businesses and places' which is a specific verb+resource combination. However, it doesn't explicitly differentiate from its sibling 'brave_web_search' which likely searches the broader web rather than local businesses.
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?
The description provides no guidance on when to use this tool versus its sibling 'brave_web_search' or any alternatives. There's no mention of appropriate contexts, prerequisites, or exclusions for using this local search functionality.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
brave_web_searchC
Execute web search using Brave Search API with improved results
Args:
query: Search terms
count: Desired number of results (10-20)
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| count | No |
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 carries the full burden of behavioral disclosure. It mentions 'improved results' but doesn't explain what this means (e.g., better ranking, additional metadata). It lacks details on rate limits, authentication needs, error handling, or what the output looks like (e.g., format of search results). For a tool with no 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, starting with the core purpose. The two-sentence structure is efficient, with the second sentence dedicated to parameter details. There's minimal waste, though the formatting with indentation and quotes might slightly affect readability in some contexts.
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 complexity (a web search tool with 2 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't explain the return values (e.g., what 'improved results' include), error conditions, or usage constraints. For a tool that interacts with an external API, more context is needed to ensure reliable agent invocation.
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 0%, so the description must compensate. It adds basic semantics for both parameters: 'query' as 'Search terms' and 'count' as 'Desired number of results (10-20)'. This clarifies the purpose of each parameter beyond the schema's titles ('Query' and 'Count'). However, it doesn't provide deeper context like query syntax examples or why count has a range, leaving room for improvement.
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 clearly states the tool's purpose: 'Execute web search using Brave Search API with improved results.' It specifies the verb ('Execute web search') and resource ('Brave Search API'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from its sibling 'brave_local_search' (e.g., by mentioning this is for general web searches vs. local searches), which prevents a perfect score.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention the sibling tool 'brave_local_search' or any other potential alternatives, nor does it specify contexts or prerequisites for usage. The only implied usage is for web searches, but this is too vague for effective tool selection.
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.
2 tool updates
v1.0.0- First observed
brave_local_search - First observed
brave_web_search
TDQS
B3.2/5.0
Scored across 2 tools
Disambiguation5/5
The two tools have clearly distinct purposes: one is for local business/place searches and the other is for general web searches. The descriptions explicitly differentiate their domains (local vs. web), making it impossible to confuse them. Each tool serves a unique function within the search domain.
Naming Consistency5/5
Both tools follow a perfectly consistent naming pattern: 'brave_' prefix followed by descriptive snake_case (local_search, web_search). The naming convention is uniform across all tools, making them predictable and easy to understand. There are no deviations or mixed styles.
Tool Count3/5
With only 2 tools, the server feels somewhat thin for a search domain that could benefit from more specialized operations (e.g., image search, news search, autocomplete). While the two core search functions are covered, the limited tool count may restrict agent capabilities for broader search-related tasks. It's borderline minimal but functional.
Completeness4/5
The server covers the essential search operations (local and web) well, but there are minor gaps in the search surface. For instance, no tools for image search, news search, or search suggestions/autocomplete are included, which are common in search APIs. However, the core workflows are adequately supported, and agents can work around these omissions.
Maintenance
ActivityInactive
ResponsivenessNo issues
Related MCP Connectors
Visit https://brave.com/search/api/ for a free API key. Search the web, local businesses, images,…
Provides AI assistants with access to Seltz's powerful Web Search capabilities.
Web search, browser automation, scraping, crawling and CAPTCHA solving for AI agents.
Brave Search MCP — independent web index (no Google/Bing dependency)
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