
kagimcp
Un serveur de protocole de contexte de modèle (MCP) pour la recherche Kagi et d'autres outils.
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Kagi MCP server
Setup Intructions
Before anything, unless you are just using non-search tools, ensure you have access to the search API. It is currently in closed beta and available upon request. Please reach out to support@kagi.com 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"
Installing via Smithery
Alternatively, you can install Kagi for Claude Desktop via Smithery:
npx -y @smithery/cli install kagimcp --client claude
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"
"KAGI_SUMMARIZER_ENGINE": "YOUR_ENGINE_CHOICE_HERE" // Defaults to "cecil" engine if env var not present
}
}
}
}
Pose query that requires use of a tool
e.g. "Who was time's 2024 person of the year?" for search, or "summarize this video: https://www.youtube.com/watch?v=jNQXAC9IVRw" for summarizer.
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"
"KAGI_SUMMARIZER_ENGINE": "YOUR_ENGINE_CHOICE_HERE" // Defaults to "cecil" engine if env var not present
}
}
}
}
Pose query that requires use of a tool
e.g. "Who was time's 2024 person of the year?" for search, or "summarize this video: https://www.youtube.com/watch?v=jNQXAC9IVRw" for summarizer.
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
.
Advanced Configuration
- 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
- Summarizer engine can be customized using the
KAGI_SUMMARIZER_ENGINE
environment variable (e.g.KAGI_SUMMARIZER_ENGINE="daphne"
)- Learn about the different summarization engines here
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Reviews

user_JbtLAJHy
As a dedicated user of kagimcp, I must say it's an exceptional tool for optimizing search capabilities. Kagisearch has truly outdone themselves with this product. The integration is seamless, and it significantly enhances efficiency. Highly recommend checking it out!