mcp-omnisearch

A Model Context Protocol (MCP) server that provides unified access to multiple search providers and AI tools. This server combines the capabilities of Tavily, Perplexity, Kagi, Jina AI, Brave, and Firecrawl to offer comprehensive search, AI responses, content processing, and enhancement features through a single interface.

Features

🔍 Search Tools

Tavily Search: Optimized for factual information with strong citation support. Supports domain filtering through API parameters (include_domains/exclude_domains).
Brave Search: Privacy-focused search with good technical content coverage. Features native support for search operators (site:, -site:, filetype:, intitle:, inurl:, before:, after:, and exact phrases).
Kagi Search: High-quality search results with minimal advertising influence, focused on authoritative sources. Supports search operators in query string (site:, -site:, filetype:, intitle:, inurl:, before:, after:, and exact phrases).

🎯 Search Operators

MCP Omnisearch provides powerful search capabilities through operators and parameters:

Common Search Features

Domain filtering: Available across all providers
- Tavily: Through API parameters (include_domains/exclude_domains)
- Brave & Kagi: Through site: and -site: operators
File type filtering: Available in Brave and Kagi (filetype:)
Title and URL filtering: Available in Brave and Kagi (intitle:, inurl:)
Date filtering: Available in Brave and Kagi (before:, after:)
Exact phrase matching: Available in Brave and Kagi ("phrase")

Example Usage

// Using Brave or Kagi with query string operators
{
  "query": "filetype:pdf site:microsoft.com typescript guide"
}

// Using Tavily with API parameters
{
  "query": "typescript guide",
  "include_domains": ["microsoft.com"],
  "exclude_domains": ["github.com"]
}

Provider Capabilities

Brave Search: Full native operator support in query string
Kagi Search: Complete operator support in query string
Tavily Search: Domain filtering through API parameters

🤖 AI Response Tools

Perplexity AI: Advanced response generation combining real-time web search with GPT-4 Omni and Claude 3
Kagi FastGPT: Quick AI-generated answers with citations (900ms typical response time)

📄 Content Processing Tools

Jina AI Reader: Clean content extraction with image captioning and PDF support
Kagi Universal Summarizer: Content summarization for pages, videos, and podcasts
Tavily Extract: Extract raw content from single or multiple web pages with configurable extraction depth ('basic' or 'advanced'). Returns both combined content and individual URL content, with metadata including word count and extraction statistics
Firecrawl Scrape: Extract clean, LLM-ready data from single URLs with enhanced formatting options
Firecrawl Crawl: Deep crawling of all accessible subpages on a website with configurable depth limits
Firecrawl Map: Fast URL collection from websites for comprehensive site mapping
Firecrawl Extract: Structured data extraction with AI using natural language prompts
Firecrawl Actions: Support for page interactions (clicking, scrolling, etc.) before extraction for dynamic content

🔄 Enhancement Tools

Kagi Enrichment API: Supplementary content from specialized indexes (Teclis, TinyGem)
Jina AI Grounding: Real-time fact verification against web knowledge

Flexible API Key Requirements

MCP Omnisearch is designed to work with the API keys you have available. You don't need to have keys for all providers - the server will automatically detect which API keys are available and only enable those providers.

For example:

If you only have a Tavily and Perplexity API key, only those providers will be available
If you don't have a Kagi API key, Kagi-based services won't be available, but all other providers will work normally
The server will log which providers are available based on the API keys you've configured

This flexibility makes it easy to get started with just one or two providers and add more as needed.

Configuration

This server requires configuration through your MCP client. Here are examples for different environments:

Cline Configuration

Add this to your Cline MCP settings:

{
	"mcpServers": {
		"mcp-omnisearch": {
			"command": "node",
			"args": ["/path/to/mcp-omnisearch/dist/index.js"],
			"env": {
				"TAVILY_API_KEY": "your-tavily-key",
				"PERPLEXITY_API_KEY": "your-perplexity-key",
				"KAGI_API_KEY": "your-kagi-key",
				"JINA_AI_API_KEY": "your-jina-key",
				"BRAVE_API_KEY": "your-brave-key",
				"FIRECRAWL_API_KEY": "your-firecrawl-key"
			},
			"disabled": false,
			"autoApprove": []
		}
	}
}

Claude Desktop with WSL Configuration

For WSL environments, add this to your Claude Desktop configuration:

{
	"mcpServers": {
		"mcp-omnisearch": {
			"command": "wsl.exe",
			"args": [
				"bash",
				"-c",
				"TAVILY_API_KEY=key1 PERPLEXITY_API_KEY=key2 KAGI_API_KEY=key3 JINA_AI_API_KEY=key4 BRAVE_API_KEY=key5 FIRECRAWL_API_KEY=key6 node /path/to/mcp-omnisearch/dist/index.js"
			]
		}
	}
}

Environment Variables

The server uses API keys for each provider. You don't need keys for all providers - only the providers corresponding to your available API keys will be activated:

TAVILY_API_KEY: For Tavily Search
PERPLEXITY_API_KEY: For Perplexity AI
KAGI_API_KEY: For Kagi services (FastGPT, Summarizer, Enrichment)
JINA_AI_API_KEY: For Jina AI services (Reader, Grounding)
BRAVE_API_KEY: For Brave Search
FIRECRAWL_API_KEY: For Firecrawl services (Scrape, Crawl, Map, Extract, Actions)

You can start with just one or two API keys and add more later as needed. The server will log which providers are available on startup.

API

The server implements MCP Tools organized by category:

Search Tools

search_tavily

Search the web using Tavily Search API. Best for factual queries requiring reliable sources and citations.

Parameters:

query (string, required): Search query

Example:

{
	"query": "latest developments in quantum computing"
}

search_brave

Privacy-focused web search with good coverage of technical topics.

Parameters:

query (string, required): Search query

Example:

{
	"query": "rust programming language features"
}

search_kagi

High-quality search results with minimal advertising influence. Best for finding authoritative sources and research materials.

Parameters:

query (string, required): Search query
language (string, optional): Language filter (e.g., "en")
no_cache (boolean, optional): Bypass cache for fresh results

Example:

{
	"query": "latest research in machine learning",
	"language": "en"
}

AI Response Tools

ai_perplexity

AI-powered response generation with real-time web search integration.

Parameters:

query (string, required): Question or topic for AI response

Example:

{
	"query": "Explain the differences between REST and GraphQL"
}

ai_kagi_fastgpt

Quick AI-generated answers with citations.

Parameters:

query (string, required): Question for quick AI response

Example:

{
	"query": "What are the main features of TypeScript?"
}

Content Processing Tools

process_jina_reader

Convert URLs to clean, LLM-friendly text with image captioning.

Parameters:

url (string, required): URL to process

Example:

{
	"url": "https://example.com/article"
}

process_kagi_summarizer

Summarize content from URLs.

Parameters:

url (string, required): URL to summarize

Example:

{
	"url": "https://example.com/long-article"
}

process_tavily_extract

Extract raw content from web pages with Tavily Extract.

Parameters:

url (string | string[], required): Single URL or array of URLs to extract content from
extract_depth (string, optional): Extraction depth - 'basic' (default) or 'advanced'

Example:

{
	"url": [
		"https://example.com/article1",
		"https://example.com/article2"
	],
	"extract_depth": "advanced"
}

Response includes:

Combined content from all URLs
Individual raw content for each URL
Metadata with word count, successful extractions, and any failed URLs

firecrawl_scrape_process

Extract clean, LLM-ready data from single URLs with enhanced formatting options.

Parameters:

url (string | string[], required): Single URL or array of URLs to extract content from
extract_depth (string, optional): Extraction depth - 'basic' (default) or 'advanced'

Example:

{
	"url": "https://example.com/article",
	"extract_depth": "basic"
}

Response includes:

Clean, markdown-formatted content
Metadata including title, word count, and extraction statistics

firecrawl_crawl_process

Deep crawling of all accessible subpages on a website with configurable depth limits.

Parameters:

url (string | string[], required): Starting URL for crawling
extract_depth (string, optional): Extraction depth - 'basic' (default) or 'advanced' (controls crawl depth and limits)

Example:

{
	"url": "https://example.com",
	"extract_depth": "advanced"
}

Response includes:

Combined content from all crawled pages
Individual content for each page
Metadata including title, word count, and crawl statistics

firecrawl_map_process

Fast URL collection from websites for comprehensive site mapping.

Parameters:

url (string | string[], required): URL to map
extract_depth (string, optional): Extraction depth - 'basic' (default) or 'advanced' (controls map depth)

Example:

{
	"url": "https://example.com",
	"extract_depth": "basic"
}

Response includes:

List of all discovered URLs
Metadata including site title and URL count

firecrawl_extract_process

Structured data extraction with AI using natural language prompts.

Parameters:

url (string | string[], required): URL to extract structured data from
extract_depth (string, optional): Extraction depth - 'basic' (default) or 'advanced'

Example:

{
	"url": "https://example.com",
	"extract_depth": "basic"
}

Response includes:

Structured data extracted from the page
Metadata including title, extraction statistics

firecrawl_actions_process

Support for page interactions (clicking, scrolling, etc.) before extraction for dynamic content.

Parameters:

url (string | string[], required): URL to interact with and extract content from
extract_depth (string, optional): Extraction depth - 'basic' (default) or 'advanced' (controls complexity of interactions)

Example:

{
	"url": "https://news.ycombinator.com",
	"extract_depth": "basic"
}

Response includes:

Content extracted after performing interactions
Description of actions performed
Screenshot of the page (if available)
Metadata including title and extraction statistics

Enhancement Tools

enhance_kagi_enrichment

Get supplementary content from specialized indexes.

Parameters:

query (string, required): Query for enrichment

Example:

{
	"query": "emerging web technologies"
}

enhance_jina_grounding

Verify statements against web knowledge.

Parameters:

statement (string, required): Statement to verify

Example:

{
	"statement": "TypeScript adds static typing to JavaScript"
}

Development

Setup

Clone the repository
Install dependencies:

pnpm install

Build the project:

pnpm run build

Run in development mode:

pnpm run dev

Publishing

Update version in package.json
Build the project:

pnpm run build

Publish to npm:

pnpm publish

Troubleshooting

API Keys and Access

Each provider requires its own API key and may have different access requirements:

Tavily: Requires an API key from their developer portal
Perplexity: API access through their developer program
Kagi: Some features limited to Business (Team) plan users
Jina AI: API key required for all services
Brave: API key from their developer portal
Firecrawl: API key required from their developer portal

Rate Limits

Each provider has its own rate limits. The server will handle rate limit errors gracefully and return appropriate error messages.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT License - see the LICENSE file for details.

Acknowledgments

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