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Server Hika

@atlas-comstock

Repository

About Server Hika

No overview available yet

#mathgpt#math-solver#math-assistant

Basic information

Category

Other

Transports

stdio

Publisher

atlas-comstock

Submitted by

HioHio Jio

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "server-hika": {
      "command": "#",
      "url": "https://hika.fyi/api/mcp/sse",
      "env": {
        "HIKA_AUTH": "Bearer please find the auth header in hika.fyi"
      }
    }
  }
}

Tools

No tools detected

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Overview

What is Server Hika?

Server Hika is a Server-Sent Events (SSE) implementation for the Hika AI knowledge search tool. It streams real-time AI-generated cognitive perspectives and knowledge extensions to enhance search queries.

How to use Server Hika?

Clone the repository, run npm install, configure environment variables (PORT, HIKA_API_URL, JWT_SECRET), then start with npm start. Client applications connect via EventSource to https://hika.fyi/api/mcp/sse with a JWT Bearer token in the Authorization header.

Key features of Server Hika

  • Real-time AI content streaming via SSE protocol
  • Multiple cognitive perspectives for knowledge exploration
  • Authentication via JWT Bearer tokens
  • Easy integration with the Hika AI ecosystem

Use cases of Server Hika

  • Quickly extend knowledge into related domains
  • Explore different viewpoints on the same question
  • Dive deeper into specific aspects of complex topics

FAQ from Server Hika

How does Server Hika authenticate clients?

Authentication uses JWT Bearer tokens. The token must be sent in the Authorization header as Bearer <token>.

What are the prerequisites to run Server Hika?

Node.js v14.0.0 or higher, understanding of Server-Sent Events, and valid Hika AI authentication credentials are required.

How do I start the Server Hika server?

Run npm start after installing dependencies and setting environment variables.

What types of events does Server Hika emit?

The server emits four event types: perspective, knowledge_extension, deep_dive, and completion (end of stream).

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