claude-to-deerflow

Manage DeerFlow AI agent platform interactions via HTTP API requests.

Updated Aug 27, 2026

Search Tags:#research #AI agent #memory management #HTTP API #conversation thread

Ready to run

npx skills add https://github.com/ainlper/dra-drb2 --skill claude-to-deerflow-ainlper

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: claude-to-deerflow
Source: https://github.com/ainlper/dra-drb2/tree/main/deer-flow/skills/public/claude-to-deerflow
Command: npx skills add https://github.com/ainlper/dra-drb2 --skill claude-to-deerflow-ainlper

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill allows you to interact with the DeerFlow AI agent platform, enabling a range of operations from sending messages and starting conversations to managing DeerFlow memory and delegating complex research tasks.

Core Features & Use Cases

DeerFlow Interaction: Send messages, questions, and instructions to DeerFlow.
Conversations and Threads: Start and manage conversation threads with DeerFlow.
Status and Health Checks: Verify the operational status of DeerFlow.
Model and Skill Management: List and manage available models, skills, and agents in DeerFlow.
Memory Management: Interact with DeerFlow memory to store and retrieve context.
File Uploads: Upload files to DeerFlow threads.
Research Tasks: Delegate complex research tasks to DeerFlow.
Use Case: Suppose you need to conduct a deep research task that requires analysis and synthesis of data from various sources. You can use this Skill to delegate the task to DeerFlow, leveraging its AI agents and tools.

Quick Start

Use the 'claude-to-deerflow' skill to send a message to DeerFlow and get a response.

Frequently Asked Questions about claude-to-deerflow

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I interact with the DeerFlow AI agent platform via HTTP API?▼

You can interact with the DeerFlow AI agent platform via HTTP API by using this Skill to send messages, manage conversation threads, check operational status, and execute complex research tasks. It requires proper configuration of environment variables to handle API responses effectively.

Can I delegate complex research tasks to an AI agent using DeerFlow?▼

Yes, you can delegate complex research tasks to an AI agent using DeerFlow. This Skill handles HTTP API requests to delegate analysis and synthesis of data from various sources, leveraging DeerFlow's AI agents and tools to execute the research.

What's the best way to manage memory and conversation threads in DeerFlow?▼

The best way to manage memory and conversation threads in DeerFlow is through this Skill's HTTP API interactions. It allows you to start and manage conversation threads, interact with DeerFlow memory to store context, and retrieve stored information for continuous operations.

Does managing DeerFlow API requests require specific environment variable configuration?▼

Yes, managing DeerFlow API requests requires specific environment variable configuration. This Skill needs proper configuration of environment variables and handling of API responses to perform tasks such as messaging, checking status, and managing memory effectively.

How do I upload files to DeerFlow conversation threads?▼

You can upload files to DeerFlow conversation threads by utilizing this Skill's HTTP API interaction capabilities. It manages the API requests necessary to attach files to existing threads, alongside sending messages and delegating research tasks to the platform.

Why should I use a dedicated Skill for DeerFlow status and health checks?▼

You should use a dedicated Skill for DeerFlow status and health checks to verify the operational status of the platform before executing tasks. It manages the HTTP API requests required to list available models, skills, and agents, ensuring the system is ready for complex research.