About Zed Brave Search Context Server
Zed Brave Search Context Server adds Brave Search to the Zed AI assistant panel for editor-based web and local business searches. Slash commands support paginated web results, while local searches fall back to web search when none are found.
Key features
- 01Adds search commands to the assistant panel
- 02Supports paginated web searches
- 03Searches for local businesses and services
- 04Falls back to web search when local results are absent
Use cases
- 01Find web references from the Zed panel
- 02Browse web results across pages
- 03Look up local businesses or services
MCP support
The extension uses the Brave Search MCP server and adds web-search and local-search commands to Zed's assistant panel.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEZed Brave Search Context Server
This extension provides a Model Context Server for Brave Search, for use with the Zed AI assistant. It leverages this MCP server.
It adds /brave_web_search and /brave_local_search slash commands to the Assistant Panel.
Configuration
Getting an API Key
To use the extension, first you will need to acquire a Brave 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
{
"context_servers": {
"brave_search": {
"settings": {
"brave_api_key": "<your brave API key>"
}
}
}
}
Usage
/brave_web_search <query> [count] [offset]: Execute web searches with pagination and filtering./brave_local_search <query> [count]: Search for local businesses and services. Automatically falls back to web search if no local results found.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.