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MCP Omnisearch

Name: mcp-omnisearch
Author: spences10

v0.0.15•Search & Data Extraction•stable

🔍 A Model Context Protocol (MCP) server providing unified access to multiple search engines (Tavily, Brave, Kagi), AI tools (Perplexity, FastGPT), and content processing services (Jina AI, Kagi). Combines search, AI responses, content processing, and

braveexafirecrawlgithub-searchkagi

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What is MCP Omnisearch?

MCP Omnisearch is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to 🔍 a model context protocol (mcp) server providing unified access to multiple search engines (tavily, brave, kagi), ai tools (perplexity, fastgpt), and content processing services (jina ai, kagi). com...

This server falls under the Search & Data Extraction category on MCPgee, the world's largest MCP server directory with 33,000+ servers.

Features

tavily_search
brave_search
kagi_search
perplexity_search
kagi_fastgpt_search

Use Cases

Search multiple engines simultaneously.

Access Tavily, Brave, and Kagi.

Process content with Jina AI.

spences10

Maintainer

LicenseMIT

Languagetypescript

Versionv0.0.15

UpdatedMay 20, 2026

Statushealthy

Maintenanceactive

Works with

ClaudeOpenAIwindowsmacoslinux

View Source Browse All Servers

Installation

NPM

npx -y mcp-omnisearch

Manual Installation

npx -y mcp-omnisearch

Configuration

Configuration Details

Config File

claude_desktop_config.json

Performance

Response Metrics

Response Time< 200ms

ThroughputMedium

Resource Usage

Memory UsageLow

CPU UsageLow

How to Set Up and Use MCP Omnisearch

MCP Omnisearch is a unified Model Context Protocol server that aggregates multiple search and content-processing providers behind four consistent tools: web search (Tavily, Brave, Kagi, Exa), AI-sourced answers (Kagi FastGPT, Exa, Linkup, Perplexity), GitHub code and repo search, and web content extraction and summarization (Tavily, Kagi, Firecrawl). You only need API keys for the providers you want to use—providers without keys are automatically skipped while the rest continue working.

Prerequisites

Node.js 18 or later and npx installed
API keys for at least one provider (Tavily, Brave, Kagi, Exa, Linkup, Firecrawl, or GitHub)
Claude Desktop or another MCP-compatible client
pnpm (for building from source; optional if using npx)

Obtain API keys for your chosen providers

# Provider sign-up URLs:
# Tavily:    https://tavily.com
# Brave:     https://brave.com/search/api/
# Kagi:      https://kagi.com/settings?p=api
# Exa:       https://exa.ai
# Linkup:    https://linkup.so
# Firecrawl: https://firecrawl.dev
# GitHub:    https://github.com/settings/tokens

Configure Claude Desktop with your API keys

Add mcp-omnisearch to Claude Desktop's configuration file. Include only the environment variables for providers you have keys for.

{
  "mcpServers": {
    "mcp-omnisearch": {
      "command": "npx",
      "args": ["-y", "mcp-omnisearch"],
      "env": {
        "TAVILY_API_KEY": "tvly-your-key",
        "BRAVE_API_KEY": "BSA-your-key",
        "KAGI_API_KEY": "your-kagi-key",
        "GITHUB_API_KEY": "ghp_your-token"
      }
    }
  }
}

Restart Claude Desktop

Save the config and fully restart Claude Desktop (Cmd+Q on macOS, not just close). The four omnisearch tools will appear in the tools panel.

Optionally configure Firecrawl self-hosted instance

If you run a self-hosted Firecrawl instance, set the base URL environment variable in addition to your API key.

{
  "env": {
    "FIRECRAWL_API_KEY": "fc-your-key",
    "FIRECRAWL_BASE_URL": "http://localhost:3002"
  }
}

Control large result handling

For searches that return large result sets, set OMNISEARCH_LARGE_RESULT_MODE to control how results are delivered. `file` saves results to disk (default); `inline` returns them directly in the response.

"OMNISEARCH_LARGE_RESULT_MODE": "inline"

MCP Omnisearch Examples

Client configuration

Claude Desktop config for mcp-omnisearch with Tavily, Brave, Kagi, and GitHub. Remove any keys you do not have — those providers are skipped automatically.

{
  "mcpServers": {
    "mcp-omnisearch": {
      "command": "npx",
      "args": ["-y", "mcp-omnisearch"],
      "env": {
        "TAVILY_API_KEY": "tvly-your-key",
        "BRAVE_API_KEY": "BSA-your-key",
        "KAGI_API_KEY": "your-kagi-key",
        "EXA_API_KEY": "your-exa-key",
        "LINKUP_API_KEY": "your-linkup-key",
        "FIRECRAWL_API_KEY": "fc-your-key",
        "GITHUB_API_KEY": "ghp_your-token"
      }
    }
  }
}

Prompts to try

Example prompts that exercise the four omnisearch tools across different providers.

- "Search for 'React Server Components best practices' using Brave and give me the top 5 results"
- "Use Kagi FastGPT to answer: what are the differences between REST and GraphQL?"
- "Search GitHub for TypeScript files named 'remote.ts' that handle WebSocket connections"
- "Extract and summarize the article at https://example.com/long-article using Firecrawl"
- "Search for 'MCP server tutorial' using both Tavily and Exa and compare the results"

Troubleshooting MCP Omnisearch

All search tools return errors about missing API keys

At least one provider API key must be set. Add the appropriate key(s) to the `env` block in your Claude Desktop config. Verify the env vars are spelled exactly as documented: TAVILY_API_KEY, BRAVE_API_KEY, KAGI_API_KEY, etc.

npx fails to install mcp-omnisearch — 404 or package not found

Run `npm view mcp-omnisearch` to confirm the package exists and check the latest version. Clear the npx cache with `npx clear-npx-cache`. If the npm registry is unavailable, build from source: `git clone https://github.com/spences10/mcp-omnisearch && cd mcp-omnisearch && pnpm install && pnpm run build`.

GitHub search returns 'Bad credentials' errors

Generate a new GitHub personal access token at github.com/settings/tokens with at least `public_repo` scope for public repo searches. Set it as GITHUB_API_KEY in your config. Tokens starting with `ghp_` are fine-grained tokens — ensure they have not expired.

Frequently Asked Questions about MCP Omnisearch

What is MCP Omnisearch?

MCP Omnisearch is a Model Context Protocol (MCP) server that 🔍 a model context protocol (mcp) server providing unified access to multiple search engines (tavily, brave, kagi), ai tools (perplexity, fastgpt), and content processing services (jina ai, kagi). combines search, ai responses, content processing, and It connects AI assistants to external tools and data sources through a standardized interface.

How do I install MCP Omnisearch?

Install via npm with the command: npx -y mcp-omnisearch. Then add the server configuration to your AI client's JSON config file (e.g., claude_desktop_config.json or .cursor/mcp.json).

Which AI clients work with MCP Omnisearch?

MCP Omnisearch works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.

Is MCP Omnisearch free to use?

Yes, MCP Omnisearch is open source and available under the MIT license. You can use it freely in both personal and commercial projects.

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Browse More Search & Data Extraction MCP Servers

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Set Up MCP Omnisearch in Your Editor

Choose your AI client for step-by-step setup instructions.

🖥️

Claude Desktop

macOS & Windows app

⌨️

Claude Code

CLI & terminal

📝

Cursor

AI-first code editor

💻

VS Code

GitHub Copilot MCP

🏄

Windsurf

Codeium AI editor

🔌

Cline

VS Code extension

Quick Config Preview

{
  "mcpServers": {
    "mcp-omnisearch": {
      "command": "npx",
      "args": ["-y", "mcp-omnisearch"]
    }
  }
}

Add this to your claude_desktop_config.json or .cursor/mcp.json

Read the full setup guide →

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