Driflyte MCP Server

MCP Server for Driflyte.

The Driflyte MCP Server exposes tools that allow AI assistants to query and retrieve topic-specific knowledge from recursively crawled and indexed web pages.
With this MCP server, Driflyte acts as a bridge between diverse, topic-aware content sources (web, GitHub, and more) and AI-powered reasoning, enabling richer, more accurate answers.

# What It Does

• Deep Web Crawling: Recursively follows links to crawl and index web pages.
• GitHub Integration: Crawls repositories, issues, and discussions.
• Extensible Resource Support: Future support planned for Slack, Microsoft Teams, Google Docs/Drive, Confluence, JIRA, Zendesk, Salesforce, and more.
• Topic-Aware Indexing: Each document is tagged with one or more topics, enabling targeted, topic-specific retrieval.
• Designed for RAG with RAG: The server itself is built with Retrieval-Augmented Generation (RAG) in mind, and it powers RAG workflows by providing assistants with high-quality, topic-specific documents as grounding context.
• Designed for AI with AI: The system is not just for AI assistants — it is also designed and evolved using AI itself, making it an AI-native component for intelligent knowledge retrieval.

# Usage & Limits

• Free Access: Driflyte is currently free to use.
• No Signup Required: You can start using it immediately — no registration or subscription needed.
• Rate Limits: To ensure fair usage, requests are limited by IP:
  • 100 API requests per 5 minutes per IP address.
• Future changes to usage policies and limits may be introduced as new features and resource integrations become available.

# Prerequisites

• Node.js 18+
• An AI assistant (with MCP client) like Cursor, Claude (Desktop or Code), VS Code, Windsurf, etc ...

# Configurations

# # CLI Arguments

Driflyte MCP server supports the following CLI arguments for configuration:

• - -transport <stdio|streamable-http> - Configures the transport protocol (defaults to stdio).
• - -port <number> – Configures the port number to listen on when using streamable-http transport (defaults to 3000).

# Quick Start

This MCP server (using STDIO or Streamable HTTP transport) can be added to any MCP Client
like VS Code, Claude, Cursor, Windsurf Github Copilot via the @driflyte/mcp-server NPM package.

# # ChatGPT

• Navigate to Settings under your profile and enable Developer Mode under the Connectors option.
• In the chat panel, click the + icon, and from the dropdown, select Developer Mode.
  You’ll see an option to add sources/connectors.
• Enter the following MCP Server details and then click Create:
  • Name: Driflyte
  • MCP Server URL: https://mcp.driflyte.com/openai
  • Authentication: No authentication
  • Trust Setting: Check I trust this application

See How to set up a remote MCP server and connect it to ChatGPT deep research
and MCP server tools now in ChatGPT – developer mode for more info.

# # Claude Code

Run the following command.
See Claude Code MCP docs for more info.

# # # Local Server

claude mcp add driflyte - - npx -y @driflye/mcp-server

# # # Remote Server

claude mcp add - -transport http driflyte https://mcp.driflyte.com/mcp

# # Claude Desktop

# # # Local Server

Add the following configuration into the claude_desktop_config.json file.
See the Claude Desktop MCP docs for more info.

{
  "mcpServers": {
    "driflyte": {
      "command": "npx",
      "args": ["-y", "@driflyte/mcp-server"]
    }
  }
}

# # # Remote Server

Go to the Settings > Connectors > Add Custom Connector in the Claude Desktop and add the new MCP server with the following fields:

• Name: Driflyte
• Remote MCP server URL: https://mcp.driflyte.com/mcp

# # Copilot Coding Agent

Add the following configuration to the mcpServers section of your Copilot Coding Agent configuration through
Repository > Settings > Copilot > Coding agent > MCP configuration.
See the Copilot Coding Agent MCP docs for more info.

# # # Local Server

{
  "mcpServers": {
    "driflyte": {
      "type": "local",
      "command": "npx",
      "args": ["-y", "@driflyte/mcp-server"]
    }
  }
}

# # # Remote Server

{
  "mcpServers": {
    "driflyte": {
      "type": "http",
      "url": "https://mcp.driflyte.com/mcp"
    }
  }
}

# # Cursor

Add the following configuration into the ~/.cursor/mcp.json file (or .cursor/mcp.json in your project folder).
Or setup by 🖱️One Click Installation.
See the Cursor MCP docs for more info.

# # # Local Server

{
  "mcpServers": {
    "driflyte": {
      "command": "npx",
      "args": ["-y", "@driflyte/mcp-server"]
    }
  }
}

# # # Remote Server

{
  "mcpServers": {
    "driflyte": {
      "url": "https://mcp.driflyte.com/mcp"
    }
  }
}

# # Gemini CLI

Add the following configuration into the ~/.gemini/settings.json file.
See the Gemini CLI MCP docs for more info.

# # # Local Server

{
  "mcpServers": {
    "driflyte": {
      "command": "npx",
      "args": ["-y", "@driflyte/mcp-server"]
    }
  }
}

# # # Remote Server

{
  "mcpServers": {
    "driflyte": {
      "httpUrl": "https://mcp.driflyte.com/mcp"
    }
  }
}

# # Smithery

Run the following command.
You can find your Smithery API key here.
See the Smithery CLI docs for more info.

npx -y @smithery/cli install @serkan-ozal/driflyte-mcp-server - -client <SMITHERY-CLIENT-NAME> - -key <SMITHERY-API-KEY>

# # VS Code

Add the following configuration into the .vscode/mcp.json file.
Or setup by 🖱️One Click Installation.
See the VS Code MCP docs for more info.

# # # Local Server

{
  "mcp": {
    "servers": {
      "driflyte": {
        "type": "stdio",
        "command": "npx",
        "args": ["-y", "@driflyte/mcp-server"]
      }
    }
  }
}

# # # Remote Server

{
  "mcp": {
    "servers": {
      "driflyte": {
        "type": "http",
        "url": "https://mcp.driflyte.com/mcp"
      }
    }
  }
}

# # Windsurf

Add the following configuration into the ~/.codeium/windsurf/mcp_config.json file.
See the Windsurf MCP docs for more info.

# # # Local Server

{
  "mcpServers": {
    "driflyte": {
      "command": "npx",
      "args": ["-y", "@driflyte/mcp-server"]
    }
  }
}

# # # Remote Server

{
  "mcpServers": {
    "driflyte": {
      "serverUrl": "https://mcp.driflyte.com/mcp"
    }
  }
}

# Components

# # Tools

• list-topics: Returns a list of topics for which resources (web pages, etc ...) have been crawled and content is available.
  This allows AI assistants to discover the most relevant and up-to-date subject areas currently indexed by the crawler.
  • Input Schema: No input parameter supported.
  • Output Schema:
    • topics:
      • Optinal: false
      • Type: Array<string>
      • Description: List of the supported topics.
• search: Given a list of topics and a user question, this tool retrieves the top-K most relevant documents from the crawled content.
  It is designed to help AI assistants surface the most contextually appropriate and up-to-date information for a specific topic and query.
  This enables more informed and accurate responses based on real-world, topic-tagged web content.
  • Input Schema:
    • topics
      • Optinal: false
      • Type: Array<string>
      • Description: A list of one or more topic identifiers to constrain the search space.
        Only documents tagged with at least one of these topics will be considered.
    • query
      • Optinal: false
      • Type: string
      • Description: The natural language query or question for which relevant information is being sought.
        This will be used to rank documents by semantic relevance.
    • topK
      • Optinal: true
      • Type: number
      • Default Value: 10
      • Min Value: 1
      • Max Value: 30
      • Description: The maximum number of relevant documents to return.
        Results are sorted by descending relevance score.
  • Output Schema:
    • documents:
      • Optional: false
      • Type: Array<Document>
      • Description: Matched documents to the search query.
      • Type: Document:
        • content
          • Optinal: false
          • Type: string
          • Description: Related content (full or partial) of the matched document.
        • metadata
          • Optinal: false
          • Type: Map<string, any>
          • Description: Metadata of the document and related content in key-value format.
        • score
          • Optinal: false
          • Type: number
          • Min Value: 0
          • Max Value: 1
          • Description: Similarity score (between 0 and 1) for the content of the document.

# # Resources

N/A

# Roadmap

• Support more content types (.pdf, .ppt/.pptx, .doc/.docx, and many others applicable including audio and video file formats ...)
• Integrate with more data sources (Slack, Teams, Google Docs/Drive, Confluence, JIRA, Zendesk, Salesforce, etc ...))
• And more topics with their resources

# Issues and Feedback

Please use GitHub Issues for any bug report, feature request and support.

# Contribution

If you would like to contribute, please

• Fork the repository on GitHub and clone your fork.
• Create a branch for your changes and make your changes on it.
• Send a pull request by explaining clearly what is your contribution.

Tip:
Please check the existing pull requests for similar contributions and
consider submit an issue to discuss the proposed feature before writing code.

# License

Licensed under MIT.