mcp-brave-search
The Brave Search MCP Server integrates the Brave Search API to provide web and local search capabilities:
Web Search: Perform general queries, news, and article searches with pagination, filtering, and freshness controls.
Local Search: Find businesses, restaurants, and services with detailed information (addresses, ratings, opening hours, contact details).
Smart Fallbacks: Automatically defaults to web search if local search yields no results.
Flexible Configuration: Supports Docker and NPX setups with customizable result types and safety levels.
Integrates with Brave Search API to provide web and local search capabilities, with features like pagination, filtering, and smart fallbacks
Click on "Deploy 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-brave-searchfind the best coffee shops near Central Park"
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.
Brave Search MCP Server
An MCP server implementation that integrates the Brave Search API, providing both web and local search capabilities.
Features
Web Search: General queries, news, articles, with pagination and freshness controls
Local Search: Find businesses, restaurants, and services with detailed information
Flexible Filtering: Control result types, safety levels, and content freshness
Smart Fallbacks: Local search automatically falls back to web when no results are found
Related MCP server: Brave Search MCP Server
Tools
brave_web_search
Execute web searches with pagination and filtering
Inputs:
query(string): Search termscount(number, optional): Results per page (max 20)offset(number, optional): Pagination offset (max 9)
brave_local_search
Search for local businesses and services
Inputs:
query(string): Local search termscount(number, optional): Number of results (max 20)
Automatically falls back to web search if no local results found
Configuration
Getting an API Key
Sign up for a Brave Search API account
Choose a plan (Free tier available with 2,000 queries/month)
Generate your API key from the developer dashboard
Usage with Claude Desktop
Add this to your claude_desktop_config.json:
Docker
{
"mcpServers": {
"brave-search": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"BRAVE_API_KEY",
"mcp/brave-search"
],
"env": {
"BRAVE_API_KEY": "YOUR_API_KEY_HERE"
}
}
}
}NPX
{
"mcpServers": {
"brave-search": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-brave-search"
],
"env": {
"BRAVE_API_KEY": "YOUR_API_KEY_HERE"
}
}
}
}Build
Docker build:
docker build -t mcp/brave-search:latest -f src/brave-search/Dockerfile .License
This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.
Available Tools
2 toolsbrave_local_searchA
Searches for local businesses and places using Brave's Local Search API. Best for queries related to physical locations, businesses, restaurants, services, etc. Returns detailed information including:
Business names and addresses
Ratings and review counts
Phone numbers and opening hours Use this when the query implies 'near me' or mentions specific locations. Automatically falls back to web search if no local results are found.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of results (1-20, default 5) | |
| query | Yes | Local search query (e.g. 'pizza near Central Park') |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It discloses automatic fallback to web search and lists returned information (names, ratings, hours). It lacks details on rate limits or authorization, but the key behavior is transparent.
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 concise paragraph with bullet points. It front-loads the purpose, then gives usage context, return info, and a fallback note. No unnecessary words, well-organized.
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?
No output schema, but description explains return details (business names, addresses, ratings, etc.) and fallback behavior. It misses error handling or pagination, but for a local search tool with two simple params, it is sufficiently 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% (both params described), baseline 3. The description adds meaning by specifying query examples ('pizza near Central Park') and default count behavior, plus clarifies what the return values include. This goes beyond schema.
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 for local businesses and places using Brave's Local Search API. It distinguishes from siblings like brave_web_search by specifying physical locations and business entities, and notes a fallback to web search.
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 explicitly says 'Best for queries related to physical locations' and 'Use this when the query implies "near me" or mentions specific locations,' providing clear when-to-use guidance. It does not explicitly state when not to use, but the context is strong.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
brave_web_searchA
Performs a web search using the Brave Search API, ideal for general queries, news, articles, and online content. Use this for broad information gathering, recent events, or when you need diverse web sources. Supports pagination, content filtering, and freshness controls. Maximum 20 results per request, with offset for pagination.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of results (1-20, default 10) | |
| offset | No | Pagination offset (max 9, default 0) | |
| query | Yes | Search query (max 400 chars, 50 words) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Mentions pagination, content filtering, freshness controls, and maximum results (20). However, does not explicitly state it is a read-only operation or discuss rate limits/auth. Adequate but not comprehensive.
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?
Three concise sentences: first states purpose, second provides usage scenarios, third mentions capabilities. No fluff, 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?
Tool has 3 params and no output schema. Description covers purpose, usage, and constraints but lacks explanation of return value format or structure. Could be more complete for agent usage.
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%; baseline 3. Description adds slight value by reiterating max 20 results and offset usage, but no new parameter details beyond schema. Content filtering and freshness controls are mentioned but are not parameters.
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?
Clearly states 'Performs a web search using the Brave Search API' with specific verb+resource. Distinguishes from siblings like brave_answers and brave_local_search by stating 'ideal for general queries, news, articles, and online content.'
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?
Provides explicit usage context: 'ideal for general queries, news, articles, and online content. Use this for broad information gathering, recent events, or when you need diverse web sources.' Lacks explicit when-not-to-use or alternatives, but context is clear.
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
Scored across 2 tools
The two tools have clearly distinct purposes: brave_local_search is for local business and place queries (e.g., 'near me'), while brave_web_search is for general web searches (e.g., news, articles). Their descriptions explicitly differentiate use cases, making misselection unlikely.
Both tools follow a consistent verb_noun pattern with 'brave_' prefix and snake_case: brave_local_search and brave_web_search. This predictable naming scheme enhances readability and agent usability.
With only 2 tools, the server feels thin for a search domain, potentially limiting functionality. While it covers local and web search basics, more specialized tools (e.g., image search, news search) could enhance completeness. The count is borderline but reasonable for a minimal setup.
The server covers core search types (local and web), but there are notable gaps for a search API, such as image search, video search, or news-specific search. Agents can work around this by using web search broadly, but the surface is incomplete for comprehensive search operations.
Maintenance
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