claude-to-deerflow

Original：🇺🇸 English

Translated

2 scripts

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.

3installs

Sourcebytedance/deer-flow

Added on2026-03-09

NPX Install

npx skill4agent add bytedance/deer-flow claude-to-deerflow

SKILL.md Content

View Translation Comparison →

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	`$DEERFLOW_GATEWAY_URL`	REST endpoints (models, skills, memory, uploads)
LangGraph API	2024	`$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:

bash

# 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:

bash

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

bash

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

Response:

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

Step 2: Stream a run

bash

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

bash

curl -s "$DEERFLOW_GATEWAY_URL/api/models"

Returns:

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

5. List Skills

bash

curl -s "$DEERFLOW_GATEWAY_URL/api/skills"

Returns:

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

6. Enable/Disable a Skill

bash

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

7. List Agents

bash

curl -s "$DEERFLOW_GATEWAY_URL/api/agents"

Returns:

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

8. Get Memory

bash

curl -s "$DEERFLOW_GATEWAY_URL/api/memory"

Returns user context, facts, and conversation history summaries.

9. Upload Files to a Thread

bash

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

bash

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

11. Get Thread History

bash

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

12. List Threads

bash

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

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.

claude-to-deerflow

NPX Install

Tags

SKILL.md Content

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