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Kagi

kagisearch/kagimcp
384
Summary

Kagimcp provides integration with Kagi's search and summarization APIs as an MCP server, enabling Claude and other AI applications to perform web searches and summarize web content and videos. The server exposes tools for executing searches via the Kagi Search API (available in closed beta) and summarizing content using configurable Kagi summarization engines. It solves the problem of giving AI assistants access to current web information and content summarization capabilities by bridging Kagi's search and AI features with the Model Context Protocol.

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Kagi MCP Server

An MCP server backed by the Kagi API. It exposes search and extraction tools to MCP-compatible clients.

Tools

  • kagi_search_fetch - web, news, videos, podcasts, and image search with optional page extracts, filters, and Kagi lenses.
  • kagi_extract - fetch a page's full content as markdown.

Note: The previous kagi_fastgpt and kagi_summarizer tools have been removed. Both are planned to return in a future release.

Requirements

  • A Kagi API key in KAGI_API_KEY.
  • uv for the recommended uvx install path.

Install uv:

curl -LsSf https://astral.sh/uv/install.sh | sh

Windows:

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Client Setup

Codex CLI

codex mcp add kagi --env KAGI_API_KEY=<YOUR_API_KEY_HERE> -- uvx kagimcp

Codex writes MCP configuration to ~/.codex/config.toml.

Claude Desktop

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 in your Claude Desktop config (found through Settings -> Developer -> Edit Config):

{
  "mcpServers": {
    "kagi": {
      "command": "uvx",
      "args": ["kagimcp"],
      "env": {
        "KAGI_API_KEY": "YOUR_API_KEY_HERE"
      }
    }
  }
}

Claude Code

claude mcp add kagi -e KAGI_API_KEY="YOUR_API_KEY_HERE" -- uvx kagimcp

Smithery

npx -y @smithery/cli install kagimcp --client claude

Kiro

Add to your Kiro MCP config file (~/.kiro/settings/mcp.json for global, or .kiro/settings/mcp.json for project-scoped) using the same mcpServers JSON as Claude Desktop. See the Kiro MCP documentation for more details.

OpenCode

Edit the OpenCode configuration file in ~/.config/opencode/opencode.json and add the following:

{
  "mcp": {
    "kagi": {
      "type": "local",
      "command": ["uvx", "kagimcp"],
      "enabled": true,
      "environment": {
        "KAGI_API_KEY": "<YOUR_API_KEY_HERE>"
      }
    }
  }
}

Usage Examples

  • Search: Who was Time's 2024 person of the year?
  • Extract: extract the full content of https://en.wikipedia.org/wiki/Model_Context_Protocol

Configuration

Environment variableDescription
KAGI_API_KEYRequired Kagi API key.
FASTMCP_LOG_LEVELLogging level, for example ERROR.
KAGI_SEARCH_TIMEOUTSearch timeout in seconds. Defaults to 10.
KAGI_EXTRACT_TIMEOUTExtract timeout in seconds. Defaults to 30.
KAGI_MAX_RETRIESMax retry attempts after the first request. Defaults to 2; set 0 to disable retries.
KAGI_HIDDEN_PARAMSComma-separated search params to hide from the LLM-facing schema.

Hideable search params:

workflow, extract_count, limit, include_domains, exclude_domains, time_relative, after, before, file_type, lens_id

Example:

KAGI_HIDDEN_PARAMS="extract_count,after,before,time_relative,include_domains,exclude_domains"

Local Development

git clone https://github.com/kagisearch/kagimcp.git
cd kagimcp
uv sync

Run locally over stdio:

KAGI_API_KEY=<YOUR_API_KEY_HERE> uv run kagimcp

Run with streamable HTTP transport:

KAGI_API_KEY=<YOUR_API_KEY_HERE> uv run kagimcp --http --host 0.0.0.0 --port 8000

Self-Hosting

HTTP mode is multi-tenant: each request supplies its API key via the Authorization: Bearer <key> header instead of a server-wide env var, so one instance can serve multiple users. The repo ships a Dockerfile that installs a pinned kagimcp from PyPI and runs it in HTTP mode. The container respects $PORT so it works on any platform that injects one (Railway, Render, Cloud Run, Fly.io, etc.).

Build and run locally:

docker build -t kagimcp-hosted .
docker run --rm -p 8000:8000 kagimcp-hosted

Smoke test:

curl -sL http://127.0.0.1:8000/mcp -X POST \
  -H "authorization: Bearer $KAGI_API_KEY" \
  -H "content-type: application/json" \
  -H "accept: application/json, text/event-stream" \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}'

To bump the version in production, edit the pin in the Dockerfile and redeploy.

Debugging

Inspect the published package:

npx @modelcontextprotocol/inspector uvx kagimcp

Inspect a local checkout:

npx @modelcontextprotocol/inspector uv --directory /ABSOLUTE/PATH/TO/kagimcp run kagimcp

The inspector is usually available at http://localhost:5173.

Prerelease Instructions

If using a prerelease build, the same installation instructions apply, but use uvx --prerelease allow --from kagimcp==1.0.0rc2 kagimcp instead of uvx kagimcp (replace 1.0.0rc2 with whatever version you're wanting to install).

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Categories
Search & Web Crawling
UpdatedFeb 7, 2026
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