Kagi Search
by Kagi
Search the web using Kagi's search API
What is Kagi Search
Kagi MCP server
Setup Intructions
Before anything, ensure you have access to the search API. It is currently in closed beta and available upon request. Please reach out to [email protected] for an invite.
Install uv first.
MacOS/Linux:
curl -LsSf https://astral.sh/uv/install.sh | sh
Windows:
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
Setup with Claude Desktop
# claude_desktop_config.json
# Can find location through:
# Hamburger Menu -> File -> Settings -> Developer -> Edit Config
{
"mcpServers": {
"kagi": {
"command": "uvx",
"args": ["kagimcp"],
"env": {
"KAGI_API_KEY": "YOUR_API_KEY_HERE"
}
}
}
}
Installing via Smithery
Alternatively, you can install Kagi for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install kagimcp --client claude
Ask Claude a question requiring search
e.g. "Who was time's 2024 person of the year?"
Debugging
Run:
npx @modelcontextprotocol/inspector uvx kagimcp
Local/Dev Setup Instructions
Clone repo
git clone https://github.com/kagisearch/kagimcp.git
Install dependencies
Install uv first.
MacOS/Linux:
curl -LsSf https://astral.sh/uv/install.sh | sh
Windows:
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
Then install MCP server dependencies:
cd kagimcp
# Create virtual environment and activate it
uv venv
source .venv/bin/activate # MacOS/Linux
# OR
.venv/Scripts/activate # Windows
# Install dependencies
uv sync
Setup with Claude Desktop
Using MCP CLI SDK
# `pip install mcp[cli]` if you haven't
mcp install /ABSOLUTE/PATH/TO/PARENT/FOLDER/kagimcp/src/kagimcp/server.py -v "KAGI_API_KEY=API_KEY_HERE"
Manually
# claude_desktop_config.json
# Can find location through:
# Hamburger Menu -> File -> Settings -> Developer -> Edit Config
{
"mcpServers": {
"kagi": {
"command": "uv",
"args": [
"--directory",
"/ABSOLUTE/PATH/TO/PARENT/FOLDER/kagimcp",
"run",
"kagimcp"
],
"env": {
"KAGI_API_KEY": "YOUR_API_KEY_HERE"
}
}
}
}
Ask Claude a question requiring search
e.g. "Who was time's 2024 person of the year?"
Debugging
Run:
# If mcp cli installed (`pip install mcp[cli]`)
mcp dev /ABSOLUTE/PATH/TO/PARENT/FOLDER/kagimcp/src/kagimcp/server.py
# If not
npx @modelcontextprotocol/inspector \
uv \
--directory /ABSOLUTE/PATH/TO/PARENT/FOLDER/kagimcp \
run \
kagimcp
Then access MCP Inspector at http://localhost:5173
. You may need to add your Kagi API key in the environment variables in the inspector under KAGI_API_KEY
.
Notes
- Level of logging is adjustable through the
FASTMCP_LOG_LEVEL
environment variable (e.g.FASTMCP_LOG_LEVEL="ERROR"
)- Relevant issue: https://github.com/kagisearch/kagimcp/issues/4
How to Use
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Frequently Asked Questions
What is MCP?
MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.
What are MCP Servers?
MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.
How do MCP Servers work?
MCP Servers follow a client-server architecture where a host application (like Claude Desktop) connects to multiple servers. Each server provides specific functionality through standardized endpoints and protocols, enabling Claude to access data and perform actions through the standardized protocol.
Are MCP Servers secure?
Yes, MCP Servers are designed with security in mind. They run locally with explicit configuration and permissions, require user approval for actions, and include built-in security features to prevent unauthorized access and ensure data privacy.
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