kagi-ken-mcp

★ 42

livetennisapi-mcp

★ 152

kagi-ken-mcp vs livetennisapi-mcp

Q: Which is better, kagi-ken-mcp or livetennisapi-mcp?

By GitHub stars, livetennisapi-mcp has more community adoption, but the best choice depends on your specific use case.

kagi-ken-mcp: This project is a lightweight Node.js-based Model Context Protocol (MCP) server that enables programmatic access to Kagi's search and summarization services using an existing Kagi session token. It offers an alternative to the official Kagi API, which currently requires invite-only API keys, making Kagi's powerful features available to LLMs and AI agents.; livetennisapi-mcp: This is an MCP (Multi-Agent Protocol) server for the Live Tennis API, designed to provide real-time and historical tennis data to AI agents like Claude, Cursor, and Zed. It allows large language models to query live scores, player statistics, match results, and even odds or win probabilities, depending on the API plan.

TL;DR

kagi-ken-mcpSecurity & Safety · ★ 42

Access Kagi's search and summarizer programmatically without an official API key.

Read kagi-ken-mcp full review →

livetennisapi-mcpAPI Integration · ★ 152

Querying current live tennis match scores and statuses.

Read livetennisapi-mcp full review →

Side-by-Side Comparison

Field

kagi-ken-mcp

livetennisapi-mcp

Features

kagi-ken-mcp

01Fetch web results using Kagi Search with concurrent query processing.

02Summarize content from URLs with customizable output types and languages.

03Utilizes Kagi session tokens stored as an environment variable or file, avoiding the need for an API key.

04Includes comprehensive error handling for connection timeouts, invalid input, and environment variables.

05Designed to integrate with LLMs and AI agents (e.g., Claude Desktop/Code) via the Model Context Protocol.

livetennisapi-mcp

01Provides comprehensive live and historical tennis data for ATP, WTA, Challenger, and ITF matches.

02Integrates seamlessly with LLM agents (Claude, Cursor, Zed) via the MCP protocol.

03Offers a wide range of data points including live scores, player profiles, match results, tournament information, odds, and model win probabilities.

04Supports both local stdio server deployment and a hosted HTTP endpoint for flexible integration.

05Features tier-aware API responses that explain plan requirements to the agent, providing actionable upgrade guidance.

Use Cases

kagi-ken-mcp

↳Access Kagi's search and summarizer programmatically without an official API key.

↳Enable AI models (like Claude) to perform web searches using Kagi's engine.

↳Integrate Kagi's summarizer into automated workflows for URL or text content summarization.

↳Provide Kagi search and summarization as tools for AI agents.

livetennisapi-mcp

↳Querying current live tennis match scores and statuses.

↳Retrieving detailed player rankings, profiles, and recent match results.

↳Analyzing historical head-to-head statistics between tennis players.

↳Integrating real-time tennis statistics and odds into AI agent conversations or applications.

↳Developing AI-powered tools that require access to comprehensive tennis data.

Best For

kagi-ken-mcp

—

livetennisapi-mcp

Hidden Gem

FAQ

What is the difference between kagi-ken-mcp and livetennisapi-mcp?

Both kagi-ken-mcp and livetennisapi-mcp are in the Security & Safety category. kagi-ken-mcp has 42 stars, while livetennisapi-mcp has 152 stars.

Which is better, kagi-ken-mcp or livetennisapi-mcp?

The best choice depends on your use case. Choose kagi-ken-mcp if Access Kagi's search and summarizer programmatically without an official API key., and livetennisapi-mcp if Querying current live tennis match scores and statuses..

Is kagi-ken-mcp free or open source?

Yes, kagi-ken-mcp is open source on GitHub (MIT).

Is livetennisapi-mcp free or open source?

Yes, livetennisapi-mcp is open source on GitHub (MIT).

Cloud Infrastructure

Deploy on DigitalOcean

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Alternatives to kagi-ken-mcp →Alternatives to livetennisapi-mcp →kagi-ken-mcp details →livetennisapi-mcp details →

TL;DR

Side-by-Side Comparison

Features

Use Cases

Best For

FAQ

Deploy on DigitalOcean

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