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, Exa AI, 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 comprehensive operator
support:
site:,-site:,filetype:/ext:,intitle:,inurl:,inbody:,inpage:,lang:,loc:,before:,after:,+term,-term, and exact phrases ("phrase"). - Kagi Search: High-quality search with full operator support:
site:,-site:,filetype:/ext:,intitle:,inurl:,inbody:,inpage:,lang:,loc:,before:,after:,+term,-term, and exact phrases ("phrase"). - Exa Search: AI-powered web search using neural and keyword search. Optimized for AI applications with semantic understanding, content extraction, and research capabilities.
- GitHub Search: Comprehensive code search across public GitHub
repositories with three specialized tools:
- Code Search: Find code examples, function definitions, and
files using advanced syntax (
filename:,path:,repo:,user:,language:,in:file) - Repository Search: Discover repositories with sorting by stars, forks, or recent updates
- User Search: Find GitHub users and organizations
- Code Search: Find code examples, function definitions, and
files using advanced syntax (
🎯 Search Operators
MCP Omnisearch provides powerful search capabilities through operators and parameters:
Search Operator Reference
Brave & Kagi Operators (use in query string):
- Domain:
site:example.com,-site:example.com - File type:
filetype:pdforext:pdf - Location:
intitle:term,inurl:term,inbody:term,inpage:term - Language:
lang:en(ISO 639-1 codes) - Country:
loc:us(ISO 3166-1 codes) - Date:
before:2024,after:2024-01-01 - Exact:
"exact phrase" - Include/Exclude:
+required,-excluded
Tavily (API parameters only):
- Domain filtering:
include_domains,exclude_domains
Example Usage
// Brave/Kagi: Advanced operators in query
{
"query": "filetype:pdf lang:en site:microsoft.com +typescript -javascript",
"provider": "brave"
}
// Brave/Kagi: Search gists
{
"query": "site:gist.github.com claude code settings",
"provider": "brave"
}
// Tavily: API parameters for domain filtering
{
"query": "typescript guide",
"provider": "tavily",
"include_domains": ["microsoft.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
- Exa Search: Domain filtering through API parameters, semantic search with neural understanding
- GitHub Search: Advanced code search syntax with qualifiers:
filename:remote.ts- Search for specific filespath:src/lib- Search within specific directoriesrepo:user/repo- Search within specific repositoriesuser:username- Search within a user's repositorieslanguage:typescript- Filter by programming languagein:file "export function"- Search for text within files
🤖 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)
- Exa Answer: Get direct AI-generated answers to questions using Exa Answer API
📄 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
- Exa Contents: Extract full content from Exa search result IDs
- Exa Similar: Find web pages semantically similar to a given URL using Exa
🔄 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",
"GITHUB_API_KEY": "your-github-key",
"EXA_API_KEY": "your-exa-key",
"FIRECRAWL_API_KEY": "your-firecrawl-key",
"FIRECRAWL_BASE_URL": "http://localhost:3002"
},
"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 GITHUB_API_KEY=key6 EXA_API_KEY=key7 FIRECRAWL_API_KEY=key8 FIRECRAWL_BASE_URL=http://localhost:3002 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 SearchPERPLEXITY_API_KEY: For Perplexity AIKAGI_API_KEY: For Kagi services (FastGPT, Summarizer, Enrichment)JINA_AI_API_KEY: For Jina AI services (Reader, Grounding)BRAVE_API_KEY: For Brave SearchGITHUB_API_KEY: For GitHub search services (Code, Repository, User search)EXA_API_KEY: For Exa AI services (Search, Answer, Contents, Similar)FIRECRAWL_API_KEY: For Firecrawl services (Scrape, Crawl, Map, Extract, Actions)FIRECRAWL_BASE_URL: For self-hosted Firecrawl instances (optional, defaults to Firecrawl cloud service)
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.
GitHub API Key Setup
To use GitHub search features, you'll need a GitHub personal access token with public repository access only for security:
-
Go to GitHub Settings: Navigate to GitHub Settings > Developer settings > Personal access tokens
-
Create a new token: Click "Generate new token" → "Generate new token (classic)"
-
Configure token settings:
-
Name:
MCP Omnisearch - Public Search -
Expiration: Choose your preferred expiration (90 days recommended)
-
Scopes: Leave all checkboxes UNCHECKED
⚠️ Important: Do not select any scopes. An empty scope token can only access public repositories and user profiles, which is exactly what we want for search functionality.
-
-
Generate and copy: Click "Generate token" and copy the token immediately
-
Add to environment: Set
GITHUB_API_KEY=your_token_here
Security Notes:
- This token configuration ensures no access to private repositories
- Only public code search, repository discovery, and user profiles are accessible
- Rate limits: 5,000 requests/hour for code search, 10 requests/minute for code search specifically
- You can revoke the token anytime from GitHub settings if needed
Self-Hosted Firecrawl Configuration
If you're running a self-hosted instance of Firecrawl, you can
configure MCP Omnisearch to use it by setting the FIRECRAWL_BASE_URL
environment variable. This allows you to maintain complete control
over your data processing pipeline.
Self-hosted Firecrawl setup:
- Follow the Firecrawl self-hosting guide
- Set up your Firecrawl instance (default runs on
http://localhost:3002) - Configure MCP Omnisearch with your self-hosted URL:
FIRECRAWL_BASE_URL=http://localhost:3002
# or for a remote self-hosted instance:
FIRECRAWL_BASE_URL=https://your-firecrawl-domain.com
Important notes:
- If
FIRECRAWL_BASE_URLis not set, MCP Omnisearch will default to the Firecrawl cloud service - Self-hosted instances support the same API endpoints (
/v1/scrape,/v1/crawl, etc.) - You'll still need a
FIRECRAWL_API_KEYeven for self-hosted instances - Self-hosted Firecrawl provides enhanced security and customization options
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 querylanguage(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"
}
github_search
Search for code on GitHub using advanced syntax. This tool searches through file contents in public repositories and provides code snippets with metadata.
Parameters:
query(string, required): Search query with GitHub search syntaxlimit(number, optional): Maximum number of results (1-50, default: 10)
Example:
{
"query": "filename:remote.ts @sveltejs/kit",
"limit": 5
}
Advanced query examples:
"filename:config.json path:src"- Find config.json files in src directories"function fetchData language:typescript"- Find fetchData functions in TypeScript"repo:microsoft/vscode extension"- Search within specific repository"user:torvalds language:c"- Search user's repositories for C code
github_repository_search
Discover GitHub repositories with enhanced metadata including stars, forks, language, and last update information.
Parameters:
query(string, required): Repository search querylimit(number, optional): Maximum number of results (1-50, default: 10)sort(string, optional): Sort results by 'stars', 'forks', or 'updated'
Example:
{
"query": "sveltekit remote functions",
"sort": "stars",
"limit": 5
}
github_user_search
Find GitHub users and organizations with profile information.
Parameters:
query(string, required): User/organization search querylimit(number, optional): Maximum number of results (1-50, default: 10)
Example:
{
"query": "Rich-Harris",
"limit": 3
}
exa_search
AI-powered web search using neural and keyword search. Automatically chooses between traditional keyword search and Exa's embeddings-based model to find the most relevant results for your query.
Parameters:
query(string, required): Search querylimit(number, optional): Maximum number of results (1-100, default: 10)include_domains(array, optional): Only include results from these domainsexclude_domains(array, optional): Exclude results from these domains
Example:
{
"query": "latest AI research papers",
"limit": 15,
"include_domains": ["arxiv.org", "scholar.google.com"]
}
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?"
}
exa_answer
Get direct AI-generated answers to questions using Exa Answer API.
Parameters:
query(string, required): Question for AI responseinclude_domains(array, optional): Only include sources from these domainsexclude_domains(array, optional): Exclude sources from these domains
Example:
{
"query": "How does machine learning work?",
"include_domains": ["arxiv.org", "nature.com"]
}
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 fromextract_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 fromextract_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 crawlingextract_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 mapextract_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 fromextract_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 fromextract_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
exa_contents_process
Extract full content from Exa search result IDs.
Parameters:
ids(string | string[], required): Exa search result ID(s) to extract content fromextract_depth(string, optional): Extraction depth - 'basic' (default) or 'advanced'
Example:
{
"ids": ["exa-result-id-123", "exa-result-id-456"],
"extract_depth": "advanced"
}
Response includes:
- Combined content from all result IDs
- Individual raw content for each ID
- Metadata with word count and extraction statistics
exa_similar_process
Find web pages semantically similar to a given URL using Exa.
Parameters:
url(string, required): URL to find similar pages forextract_depth(string, optional): Extraction depth - 'basic' (default) or 'advanced'
Example:
{
"url": "https://arxiv.org/abs/2106.09685",
"extract_depth": "advanced"
}
Response includes:
- Combined content from all similar pages
- Similarity scores and metadata
- Individual content for each similar page
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"
}
Docker Deployment
MCP Omnisearch supports containerized deployment using Docker with MCPO (Model Context Protocol Over HTTP) integration, enabling cloud deployment and OpenAPI access.
Quick Start with Docker
- Using Docker Compose (Recommended):
# Clone the repository
git clone https://github.com/spences10/mcp-omnisearch.git
cd mcp-omnisearch
# Create .env file with your API keys
echo "TAVILY_API_KEY=your-tavily-key" > .env
echo "KAGI_API_KEY=your-kagi-key" >> .env
echo "PERPLEXITY_API_KEY=your-perplexity-key" >> .env
echo "EXA_API_KEY=your-exa-key" >> .env
# Add other API keys as needed
echo "GITHUB_API_KEY=your-github-key" >> .env
# Start the container
docker-compose up -d
- Using Docker directly:
docker build -t mcp-omnisearch .
docker run -d \
-p 8000:8000 \
-e TAVILY_API_KEY=your-tavily-key \
-e KAGI_API_KEY=your-kagi-key \
-e PERPLEXITY_API_KEY=your-perplexity-key \
-e EXA_API_KEY=your-exa-key \
-e GITHUB_API_KEY=your-github-key \
--name mcp-omnisearch \
mcp-omnisearch
Container Environment Variables
Configure the container using environment variables for each provider:
TAVILY_API_KEY: For Tavily SearchPERPLEXITY_API_KEY: For Perplexity AIKAGI_API_KEY: For Kagi services (FastGPT, Summarizer, Enrichment)JINA_AI_API_KEY: For Jina AI services (Reader, Grounding)BRAVE_API_KEY: For Brave SearchGITHUB_API_KEY: For GitHub search servicesEXA_API_KEY: For Exa AI servicesFIRECRAWL_API_KEY: For Firecrawl servicesFIRECRAWL_BASE_URL: For self-hosted Firecrawl instances (optional)PORT: Container port (defaults to 8000)
OpenAPI Access
Once deployed, the MCP server is accessible via OpenAPI at:
- Base URL:
http://your-container-host:8000 - OpenAPI Endpoint:
/omnisearch - Compatible with: OpenWebUI and other tools expecting OpenAPI
Cloud Deployment
The containerized version can be deployed to any container platform that supports Docker:
- Cloud Run (Google Cloud)
- Container Instances (Azure)
- ECS/Fargate (AWS)
- Railway, Render, Fly.io
- Any Kubernetes cluster
Example deployment to a cloud platform:
# Build and tag for your registry
docker build -t your-registry/mcp-omnisearch:latest .
docker push your-registry/mcp-omnisearch:latest
# Deploy with your platform's CLI or web interface
# Configure environment variables through your platform's settings
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
- GitHub: Personal access token with no scopes selected (public access only)
- Exa AI: API key from their dashboard at dashboard.exa.ai
- 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
Please read CONTRIBUTING.md before opening a PR. In short:
- Start by opening an issue to propose your change and align scope.
- Prefer small, focused PRs with a clear explanation (problem → approach → verification).
- Follow provider conventions: use
src/common/http.ts(http_json) for HTTP, read keys fromsrc/config/env.ts, respect timeouts, and surface errors viaProviderError.
License
MIT License - see the LICENSE file for details.
Acknowledgments
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