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by cwinux

341 downloads

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Media

Description

# 🦌 DeerFlow [![Python 3.12+](https://img.shields.io/badge/python-3.12+-blue.svg)](https://www.python.org/downloads/) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) [English](./README.md) | [简体中文](./README_zh.md) |…

About

Details

Author: cwinux
Downloads: 341
Categories: Media

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name Image

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "image": {
            "github": {
                "command": "npx",
                "args": [
                    "-y",
                    "@modelcontextprotocol/server-github"
                ],
                "env": {
                    "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "image": {
            "github": {
                "command": "npx",
                "args": [
                    "-y",
                    "@modelcontextprotocol/server-github"
                ],
                "env": {
                    "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "image": {
            "github": {
                "command": "npx",
                "args": [
                    "-y",
                    "@modelcontextprotocol/server-github"
                ],
                "env": {
                    "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
                }
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "image": {
            "github": {
                "command": "npx",
                "args": [
                    "-y",
                    "@modelcontextprotocol/server-github"
                ],
                "env": {
                    "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "image": {
            "github": {
                "command": "npx",
                "args": [
                    "-y",
                    "@modelcontextprotocol/server-github"
                ],
                "env": {
                    "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "image": {
            "github": {
                "command": "npx",
                "args": [
                    "-y",
                    "@modelcontextprotocol/server-github"
                ],
                "env": {
                    "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
                }
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "image": {
            "github": {
                "command": "npx",
                "args": [
                    "-y",
                    "@modelcontextprotocol/server-github"
                ],
                "env": {
                    "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "image": {
            "github": {
                "command": "npx",
                "args": [
                    "-y",
                    "@modelcontextprotocol/server-github"
                ],
                "env": {
                    "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "image": {
            "github": {
                "command": "npx",
                "args": [
                    "-y",
                    "@modelcontextprotocol/server-github"
                ],
                "env": {
                    "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
                }
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "image": {
            "github": {
                "command": "npx",
                "args": [
                    "-y",
                    "@modelcontextprotocol/server-github"
                ],
                "env": {
                    "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "image": {
            "github": {
                "command": "npx",
                "args": [
                    "-y",
                    "@modelcontextprotocol/server-github"
                ],
                "env": {
                    "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "image": {
            "github": {
                "command": "npx",
                "args": [
                    "-y",
                    "@modelcontextprotocol/server-github"
                ],
                "env": {
                    "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
                }
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "image": {
            "github": {
                "command": "npx",
                "args": [
                    "-y",
                    "@modelcontextprotocol/server-github"
                ],
                "env": {
                    "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "image": {
            "github": {
                "command": "npx",
                "args": [
                    "-y",
                    "@modelcontextprotocol/server-github"
                ],
                "env": {
                    "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "image": {
            "github": {
                "command": "npx",
                "args": [
                    "-y",
                    "@modelcontextprotocol/server-github"
                ],
                "env": {
                    "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
                }
            }
        }
    }
}

From the repository

—

`create_or_update_file`

Create or update a single file in a GitHub repository

`search_repositories`

Search for GitHub repositories

`create_repository`

Create a new GitHub repository in your account

`get_file_contents`

Get the contents of a file or directory from a GitHub repository

`push_files`

Push multiple files to a GitHub repository in a single commit

`create_issue`

Create a new issue in a GitHub repository

`create_pull_request`

Create a new pull request in a GitHub repository

`fork_repository`

Fork a GitHub repository to your account or specified organization

`create_branch`

Create a new branch in a GitHub repository

`list_commits`

Get list of commits of a branch in a GitHub repository

`list_issues`

List issues in a GitHub repository with filtering options

`update_issue`

Update an existing issue in a GitHub repository

`add_issue_comment`

Add a comment to an existing issue

`search_code`

Search for code across GitHub repositories

`search_issues`

Search for issues and pull requests across GitHub repositories

`search_users`

Search for users on GitHub

`get_issue`

Get details of a specific issue in a GitHub repository.

`get_pull_request`

Get details of a specific pull request

`list_pull_requests`

List and filter repository pull requests

`create_pull_request_review`

Create a review on a pull request

`merge_pull_request`

Merge a pull request

`get_pull_request_files`

Get the list of files changed in a pull request

`get_pull_request_status`

Get the combined status of all status checks for a pull request

`update_pull_request_branch`

Update a pull request branch with the latest changes from the base branch

`get_pull_request_comments`

Get the review comments on a pull request

`get_pull_request_reviews`

Get the reviews on a pull request

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "image": {
            "github": {
                "command": "npx",
                "args": [
                    "-y",
                    "@modelcontextprotocol/server-github"
                ],
                "env": {
                    "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
                }
            }
        }
    }
}

McpServers

{
    "github": {
        "command": "npx",
        "args": [
            "-y",
            "@modelcontextprotocol/server-github"
        ],
        "env": {
            "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
        }
    }
}

🦌 DeerFlow

English | 简体中文 | 日本語

> Originated from Open Source, give back to Open Source.

DeerFlow (Deep Exploration and Efficient Research Flow) is a community-driven Deep Research framework that builds upon the incredible work of the open source community. Our goal is to combine language models with specialized tools for tasks like web search, crawling, and Python code execution, while giving back to the community that made this possible.

Please visit our official website for more details.

Demo

Video

https://github.com/user-attachments/assets/f3786598-1f2a-4d07-919e-8b99dfa1de3e

In this demo, we showcase how to use DeerFlow to:
- Seamlessly integrate with MCP services
- Conduct the Deep Research process and produce a comprehensive report with images
- Create podcast audio based on the generated report

Replays

- How tall is Eiffel Tower compared to tallest building?
- What are the top trending repositories on GitHub?
- Write an article about Nanjing's traditional dishes
- How to decorate a rental apartment?
- Visit our official website to explore more replays.

---

📑 Table of Contents

- 🚀 Quick Start
- 🌟 Features
- 🏗️ Architecture
- 🛠️ Development
- 🗣️ Text-to-Speech Integration
- 📚 Examples
- ❓ FAQ
- 📜 License
- 💖 Acknowledgments
- ⭐ Star History

Quick Start

DeerFlow is developed in Python, and comes with a web UI written in Node.js. To ensure a smooth setup process, we recommend using the following tools:

Recommended Tools

- uv: Simplify Python environment and dependency management. uv automatically creates a virtual environment in the root directory and installs all required packages for you—no need to manually install Python environments.

- nvm:
Manage multiple versions of the Node.js runtime effortlessly.

- pnpm:
Install and manage dependencies of Node.js project.

Environment Requirements

Make sure your system meets the following minimum requirements: - Python: Version 3.12+ - Node.js: Version 22+

Installation

# Clone the repository
git clone https://github.com/bytedance/deer-flow.git
cd deer-flow
Install dependencies, uv will take care of the python interpreter and venv creation, and install the required packages
uv sync
Configure .env with your API keys
Tavily: https://app.tavily.com/home
Brave_SEARCH: https://brave.com/search/api/
volcengine TTS: Add your TTS credentials if you have them
cp .env.example .env
See the 'Supported Search Engines' and 'Text-to-Speech Integration' sections below for all available options
Configure conf.yaml for your LLM model and API keys
Please refer to 'docs/configuration_guide.md' for more details
cp conf.yaml.example conf.yaml
Install marp for ppt generation
https://github.com/marp-team/marp-cli?tab=readme-ov-file#use-package-manager
brew install marp-cli

Optionally, install web UI dependencies via pnpm:

cd deer-flow/web
pnpm install

Configurations

Please refer to the Configuration Guide for more details.

> [!NOTE]
> Before you start the project, read the guide carefully, and update the configurations to match your specific settings and requirements.

Console UI

The quickest way to run the project is to use the console UI.

# Run the project in a bash-like shell
uv run main.py

Web UI

This project also includes a Web UI, offering a more dynamic and engaging interactive experience.
> [!NOTE]
> You need to install the dependencies of web UI first.

# Run both the backend and frontend servers in development mode
On macOS/Linux
./bootstrap.sh -d
On Windows
bootstrap.bat -d

Open your browser and visit http://localhost:3000 to explore the web UI.

Explore more details in the web directory.

Supported Search Engines

DeerFlow supports multiple search engines that can be configured in your .env file using the SEARCH_API variable:

- Tavily (default): A specialized search API for AI applications
- Requires TAVILY_API_KEY in your .env file
- Sign up at: https://app.tavily.com/home

- DuckDuckGo: Privacy-focused search engine
- No API key required

- Brave Search: Privacy-focused search engine with advanced features
- Requires BRAVE_SEARCH_API_KEY in your .env file
- Sign up at: https://brave.com/search/api/

- Arxiv: Scientific paper search for academic research
- No API key required
- Specialized for scientific and academic papers

To configure your preferred search engine, set the SEARCH_API variable in your .env file:

# Choose one: tavily, duckduckgo, brave_search, arxiv
SEARCH_API=tavily

Features

Core Capabilities

- 🤖 LLM Integration
- It supports the integration of most models through litellm.
- Support for open source models like Qwen
- OpenAI-compatible API interface
- Multi-tier LLM system for different task complexities

Tools and MCP Integrations

- 🔍 Search and Retrieval
- Web search via Tavily, Brave Search and more
- Crawling with Jina
- Advanced content extraction

- 🔗 MCP Seamless Integration
- Expand capabilities for private domain access, knowledge graph, web browsing and more
- Facilitates integration of diverse research tools and methodologies

Human Collaboration

- 🧠 Human-in-the-loop
- Supports interactive modification of research plans using natural language
- Supports auto-acceptance of research plans

- 📝 Report Post-Editing
- Supports Notion-like block editing
- Allows AI refinements, including AI-assisted polishing, sentence shortening, and expansion
- Powered by tiptap

Content Creation

- 🎙️ Podcast and Presentation Generation
- AI-powered podcast script generation and audio synthesis
- Automated creation of simple PowerPoint presentations
- Customizable templates for tailored content

Architecture

DeerFlow implements a modular multi-agent system architecture designed for automated research and code analysis. The system is built on LangGraph, enabling a flexible state-based workflow where components communicate through a well-defined message passing system.

Architecture Diagram
> See it live at deerflow.tech

The system employs a streamlined workflow with the following components:

1. Coordinator: The entry point that manages the workflow lifecycle
- Initiates the research process based on user input
- Delegates tasks to the planner when appropriate
- Acts as the primary interface between the user and the system

…

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Description

About

Details

Jump to

Setting up with Highlight

From the repository

create_or_update_file

search_repositories

create_repository

get_file_contents

push_files

create_issue

create_pull_request

fork_repository

create_branch

list_commits

list_issues

update_issue

add_issue_comment

search_code

search_issues

search_users

get_issue

get_pull_request

list_pull_requests

create_pull_request_review

merge_pull_request

get_pull_request_files

get_pull_request_status

update_pull_request_branch

get_pull_request_comments

get_pull_request_reviews

Claude Desktop / Cursor

McpServers

🦌 DeerFlow

Demo

Video

Replays

📑 Table of Contents

Quick Start

Recommended Tools

Environment Requirements

Installation

Install dependencies, uv will take care of the python interpreter and venv creation, and install the required packages

Configure .env with your API keys

Tavily: https://app.tavily.com/home

Brave_SEARCH: https://brave.com/search/api/

volcengine TTS: Add your TTS credentials if you have them

See the 'Supported Search Engines' and 'Text-to-Speech Integration' sections below for all available options

Configure conf.yaml for your LLM model and API keys

Please refer to 'docs/configuration_guide.md' for more details

Install marp for ppt generation

https://github.com/marp-team/marp-cli?tab=readme-ov-file#use-package-manager

Configurations

Console UI

Web UI

On macOS/Linux

On Windows

Supported Search Engines

Features

Core Capabilities

Tools and MCP Integrations

Human Collaboration

Content Creation

Architecture

Install

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`create_or_update_file`

`search_repositories`

`create_repository`

`get_file_contents`

`push_files`

`create_issue`

`create_pull_request`

`fork_repository`

`create_branch`

`list_commits`

`list_issues`

`update_issue`

`add_issue_comment`

`search_code`

`search_issues`

`search_users`

`get_issue`

`get_pull_request`

`list_pull_requests`

`create_pull_request_review`

`merge_pull_request`

`get_pull_request_files`

`get_pull_request_status`

`update_pull_request_branch`

`get_pull_request_comments`

`get_pull_request_reviews`