Side-by-Side Model Context Protocol Comparison
Kagi Ken MCP vs DeepSearch
In-depth architectural comparison of the Kagi Ken MCP and DeepSearch MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.
At a Glance & Executive Verdict
Kagi Ken MCP
Search & Data Extraction · Local stdio
Quality: 59/100 (Good) | Auth: API Key required
DeepSearch
Search & Data Extraction · Remote HTTP/SSE
Quality: 67/100 (Great) | Auth: No auth required
Verdict Summary: Choose Kagi Ken MCP if you need specialized Search & Data Extraction tools running via a local process. Choose DeepSearch if your workspace requires Search & Data Extraction integration with remote web transport. Both servers can be configured concurrently in your client's
mcpServers manifest.Which MCP Server Should You Choose?
Choose Kagi Ken MCP when:
- You need dedicated capabilities in the Search & Data Extraction domain.
- You prefer local stdio subprocess transport architecture.
- Your security boundary fits: API Key required (BYOK (Pay Provider Direct)).
- You have access to required keys:
KAGI_SESSION_TOKEN. - Primary tools included: kagi_search_fetch, kagi_summarizer.
D
Choose DeepSearch when:
- You need dedicated capabilities in the Search & Data Extraction domain.
- You prefer remote streaming HTTP/SSE transport architecture.
- Your security boundary fits: No auth required (Free / Open Source).
- Primary tools included: search_people, build_dossier, ask_about_person.
Feature & Specification Comparison
Tools & Capabilities Breakdown
Kagi Ken MCP Tools (2)
kagi_search_fetch
Fetch web results based on one or more queries using the Kagi Search API. Results are numbered continuously for easy reference.
kagi_summarizer
Summarize content from URLs using the Kagi Summarizer API. Supports various document types including webpages, videos, and audio.
DeepSearch Tools (3)
search_people
Resolve one identifier - a name, phone number, email address, or username - to a ranked list of real, distinct people, each with a confidence score. Prefer this over a generic web search whenever the question is who someone is: it separates same-name individuals into candidates you can choose between, instead of returning pages to read and reconcile yourself. Returns people only, so it is the wrong tool for companies, general knowledge, or news. Public sources only - never private accounts or breach data.
build_dossier
Assemble one person's entire public footprint into a single sourced profile: identity, contact details, social accounts unified across platforms, work history, education, relatives, locations, and web mentions - every claim linked to the page it came from. Prefer this over reading search results yourself when you need the whole picture of one person rather than a single fact; it does the cross-platform correlation that a web search leaves to you. Pass a name plus the headline or username from search_people so the right individual is profiled. Repeat profiles are served from a shared cache: free and instant. Public sources only - never private accounts or breach data.
Ready-to-Paste Client Configurations
Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).
Kagi Ken MCP Configuration
DeepSearch Configuration
Frequently Asked Questions
More alternatives to Kagi Ken MCPMore alternatives to DeepSearchSearch & Data Extraction category hub