claude-to-deerflow

Q: How do I install claude-to-deerflow?

Run npx skills add https://github.com/bytedance/deer-flow --skill claude-to-deerflow in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/claude-to-deerflow/ (personal) or .claude/skills/claude-to-deerflow/ (project).

by bytedanceProductivity & Automation

Interact with DeerFlow AI agent platform via its HTTP API. Use this skill when the user wants to send messages or questions to DeerFlow for research/analysis, start a DeerFlow conversation thread, check DeerFlow status or health, list available models/skills/agents in DeerFlow, manage DeerFlow memory, upload files to DeerFlow threads, or delegate complex research tasks to DeerFlow. Also use when the user mentions deerflow, deer flow, or wants to run a deep research task that DeerFlow can handle.

Installs: 3.9K
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Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/bytedance/deer-flow --skill claude-to-deerflow

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads claude-to-deerflow automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

DeerFlow Skill

Communicate with a running DeerFlow instance via its HTTP API. DeerFlow is an AI agent platform built on LangGraph that orchestrates sub-agents for research, code execution, web browsing, and more.

Architecture

DeerFlow exposes two API surfaces behind an Nginx reverse proxy:

Service	Direct Port	Via Proxy	Purpose
Gateway API	8001	`$DEERFLOW_GATEWAY_URL`	REST endpoints and embedded agent runtime
LangGraph-compatible API	8001	`$DEERFLOW_LANGGRAPH_URL`	Agent threads, runs, streaming

Environment Variables

All URLs are configurable via environment variables. Read these env vars before making any request.

Variable	Default	Description
`DEERFLOW_URL`	`http://localhost:2026`	Unified proxy base URL
`DEERFLOW_GATEWAY_URL`	`${DEERFLOW_URL}`	Gateway API base (models, skills, memory, uploads)
`DEERFLOW_LANGGRAPH_URL`	`${DEERFLOW_URL}/api/langgraph`	LangGraph API base (threads, runs)

When making curl calls, always resolve the URL like this:

# Resolve base URLs from env (do this FIRST before any API call)
DEERFLOW_URL="${DEERFLOW_URL:-http://localhost:2026}"
DEERFLOW_GATEWAY_URL="${DEERFLOW_GATEWAY_URL:-$DEERFLOW_URL}"
DEERFLOW_LANGGRAPH_URL="${DEERFLOW_LANGGRAPH_URL:-$DEERFLOW_URL/api/langgraph}"

Available Operations

1. Health Check

Verify DeerFlow is running:

curl -s "$DEERFLOW_GATEWAY_URL/health"

2. Send a Message (Streaming)

This is the primary operation. It creates a thread and streams the agent's response.

Step 1: Create a thread

curl -s -X POST "$DEERFLOW_LANGGRAPH_URL/threads" \
  -H "Content-Type: application/json" \
  -d '{}'

Response: {"thread_id": "<uuid>", ...}

Step 2: Stream a run

curl -s -N -X POST "$DEERFLOW_LANGGRAPH_URL/threads/<thread_id>/runs/stream" \
  -H "Content-Type: application/json" \
  -d '{
    "assistant_id": "lead_agent",
    "input": {
      "messages": [
        {
          "type": "human",
          "content": [{"type": "text", "text": "YOUR MESSAGE HERE"}]
        }
      ]
    },
    "stream_mode": ["values", "messages-tuple"],
    "stream_subgraphs": true,
    "config": {
      "recursion_limit": 1000
    },
    "context": {
      "thinking_enabled": true,
      "is_plan_mode": true,
      "subagent_enabled": true,
      "thread_id": "<thread_id>"
    }
  }'

The response is an SSE stream. Each event has the format:

event: <event_type>
data: <json_data>

Key event types:

metadata — run metadata including run_id
values — full state snapshot with messages array
messages-tuple — incremental message updates (AI text chunks, tool calls, tool results)
end — stream is complete

Context modes (set via context):

Flash mode: thinking_enabled: false, is_plan_mode: false, subagent_enabled: false
Standard mode: thinking_enabled: true, is_plan_mode: false, subagent_enabled: false
Pro mode: thinking_enabled: true, is_plan_mode: true, subagent_enabled: false
Ultra mode: thinking_enabled: true, is_plan_mode: true, subagent_enabled: true

3. Continue a Conversation

To send follow-up messages, reuse the same thread_id from step 2 and POST another run with the new message.

4. List Models

curl -s "$DEERFLOW_GATEWAY_URL/api/models"

Returns: {"models": [{"name": "...", "provider": "...", ...}, ...]}

5. List Skills

curl -s "$DEERFLOW_GATEWAY_URL/api/skills"

Returns: {"skills": [{"name": "...", "enabled": true, ...}, ...]}

6. Enable/Disable a Skill

curl -s -X PUT "$DEERFLOW_GATEWAY_URL/api/skills/<skill_name>" \
  -H "Content-Type: application/json" \
  -d '{"enabled": true}'

7. List Agents

curl -s "$DEERFLOW_GATEWAY_URL/api/agents"

Returns: {"agents": [{"name": "...", ...}, ...]}

8. Get Memory

curl -s "$DEERFLOW_GATEWAY_URL/api/memory"

Returns user context, facts, and conversation history summaries.

9. Upload Files to a Thread

curl -s -X POST "$DEERFLOW_GATEWAY_URL/api/threads/<thread_id>/uploads" \
  -F "files=@/path/to/file.pdf"

Supports PDF, PPTX, XLSX, DOCX — automatically converts to Markdown.

10. List Uploaded Files

curl -s "$DEERFLOW_GATEWAY_URL/api/threads/<thread_id>/uploads/list"

11. Get Thread History

curl -s "$DEERFLOW_LANGGRAPH_URL/threads/<thread_id>/history"

12. List Threads

curl -s -X POST "$DEERFLOW_LANGGRAPH_URL/threads/search" \
  -H "Content-Type: application/json" \
  -d '{"limit": 20, "sort_by": "updated_at", "sort_order": "desc"}'

Usage Script

For sending messages and collecting the full response, use the helper script:

bash /path/to/skills/claude-to-deerflow/scripts/chat.sh "Your question here"

See scripts/chat.sh for the implementation. The script:

Checks health
Creates a thread
Streams the run and collects the final AI response
Prints the result

Parsing SSE Output

The stream returns SSE events. To extract the final AI response from a values event:

Look for the last event: values block
Parse its data JSON
The messages array contains all messages; the last one with type: "ai" is the response
The content field of that message is the AI's text reply

Error Handling

If health check fails, DeerFlow is not running. Inform the user they need to start it.
If the stream returns an error event, extract and display the error message.
Common issues: port not open, services still starting up, config errors.

Tips

For quick questions, use flash mode (fastest, no planning).
For research tasks, use pro or ultra mode (enables planning and sub-agents).
You can upload files first, then reference them in your message.
Thread IDs persist — you can return to a conversation later.

FAQ

What does the claude-to-deerflow skill do?

How do I install claude-to-deerflow?

Run npx skills add https://github.com/bytedance/deer-flow --skill claude-to-deerflow in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/claude-to-deerflow/ (personal) or .claude/skills/claude-to-deerflow/ (project).

Which AI agents can use claude-to-deerflow?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is claude-to-deerflow safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains claude-to-deerflow?

It is published by bytedance in bytedance/deer-flow. It has 3,851 recorded installs.

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claude-to-deerflow

Install

Install

Describe the task

Review the result

SKILL.md

DeerFlow Skill

Architecture

Environment Variables

Available Operations

1. Health Check

2. Send a Message (Streaming)

3. Continue a Conversation

4. List Models

5. List Skills

6. Enable/Disable a Skill

7. List Agents

8. Get Memory

9. Upload Files to a Thread

10. List Uploaded Files

11. Get Thread History

12. List Threads

Usage Script

Parsing SSE Output

Error Handling

Tips

FAQ

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