# 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.
<a href="https://glama.ai/mcp/servers/gz5wgmptd8">
<img width="380" height="200" src="https://glama.ai/mcp/servers/gz5wgmptd8/badge" alt="Glama badge" />
</a>
## 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
```typescript
// 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:
```json
{
"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:
```json
{
"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:
```json
{
"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:
```json
{
"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:
```json
{
"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:
```json
{
"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:
```json
{
"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:
```json
{
"url": "https://example.com/article"
}
```
#### process_kagi_summarizer
Summarize content from URLs.
Parameters:
- `url` (string, required): URL to summarize
Example:
```json
{
"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:
```json
{
"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:
```json
{
"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:
```json
{
"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:
```json
{
"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:
```json
{
"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:
```json
{
"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:
```json
{
"query": "emerging web technologies"
}
```
#### enhance_jina_grounding
Verify statements against web knowledge.
Parameters:
- `statement` (string, required): Statement to verify
Example:
```json
{
"statement": "TypeScript adds static typing to JavaScript"
}
```
## Development
### Setup
1. Clone the repository
2. Install dependencies:
```bash
pnpm install
```
3. Build the project:
```bash
pnpm run build
```
4. Run in development mode:
```bash
pnpm run dev
```
### Publishing
1. Update version in package.json
2. Build the project:
```bash
pnpm run build
```
3. Publish to npm:
```bash
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](LICENSE) file for details.
## Acknowledgments
Built on:
- [Model Context Protocol](https://github.com/modelcontextprotocol)
- [Tavily Search](https://tavily.com)
- [Perplexity AI](https://perplexity.ai)
- [Kagi Search](https://kagi.com)
- [Jina AI](https://jina.ai)
- [Brave Search](https://search.brave.com)
- [Firecrawl](https://firecrawl.dev)