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Agent skill

DeerFlow HTTP API Client

by bytedance in bytedance/deer-flow

Talks to a running DeerFlow agent platform over its HTTP API to send research questions, stream replies, check health and manage models, skills, memory and uploads.

MITAuto-check passedAgent Workflows

Install DeerFlow HTTP API Client

skills CLI
$ npx skills add bytedance/deer-flow --skill claude-to-deerflow -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install bytedance/deer-flow claude-to-deerflow --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/bytedance/deer-flow.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/public/claude-to-deerflow .claude/skills/claude-to-deerflow && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
claude-to-deerflow
GitHub stars
84k
Used in
1 other repo
Token cost
~1.7k tokens
SKILL.md length
505 words
Files
3 (incl. scripts)
Skills in repo
23
Repo updated
First seen
Licence
MIT

At a glance

Talks to a running DeerFlow agent platform over its HTTP API to send research questions, stream replies, check health and manage models, skills, memory and uploads.

  • Works in 12 steps: Health Check → Send a Message (Streaming) → Continue a Conversation → …
  • Delegating a long research task to a running DeerFlow instance
  • SKILL.md covers Architecture, Environment Variables, Available Operations and Usage Script, plus 3 more sections
  • Runs Shell scripts from its folder; calls curl and bash

What it does

DeerFlow is an agent platform built on LangGraph, and it exposes two API surfaces behind an Nginx reverse proxy: a Gateway API for REST endpoints such as models, skills, memory and uploads, and a LangGraph-compatible API for threads, runs and streaming. The agent reads the `DEERFLOW_URL` variable, which defaults to `http://localhost:2026`, along with the optional gateway and LangGraph overrides, before making any request.

The main operation creates a thread and then streams a run, reading the server-sent events as they arrive, starting with run metadata. A health check hits `/health` first, and helper scripts `scripts/chat.sh` and `scripts/status.sh` wrap chatting and status checks. The skill also covers listing models, skills and agents, managing memory and uploading files to threads, so a long research task can be handed to DeerFlow.

When your agent uses it

  • Delegating a long research task to a running DeerFlow instance
  • Checking that a DeerFlow server is up before sending work
  • Listing the models, skills or agents available in DeerFlow
  • Uploading a file to a DeerFlow thread for analysis

Example prompts

  • “Ask DeerFlow to research the current state of solid-state battery manufacturing and stream me the answer.”
  • “Check whether my DeerFlow server is healthy.”
  • “List the models and skills available in DeerFlow.”
  • “Upload report.pdf to a new DeerFlow thread and ask for a summary.”

Requirements

  • A running DeerFlow instance
  • `curl` to call its HTTP API

Workflow steps

12 steps, taken from the step headings in SKILL.md.

  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

What it can do on your machine

Read from SKILL.md and the folder at commit 8a3350a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • curl
    • bash

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use curl, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

DeerFlow HTTP API Client loads about 1.7k tokens when it runs. Until then it costs about 130 tokens; SKILL.md has 505 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~130
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from bytedance/deer-flow at commit 8a3350a, republished under its MIT licence (© bytedance). 505 words, ~1,713 tokens.

Download SKILL.mdSave it as .claude/skills/claude-to-deerflow/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
claude-to-deerflow
description
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.

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:

ServiceDirect PortVia ProxyPurpose
Gateway API8001$DEERFLOW_GATEWAY_URLREST endpoints and embedded agent runtime
LangGraph-compatible API8001$DEERFLOW_LANGGRAPH_URLAgent threads, runs, streaming

Environment Variables

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

VariableDefaultDescription
DEERFLOW_URLhttp://localhost:2026Unified proxy base URL
DEERFLOW_GATEWAY_URL${DEERFLOW_URL}Gateway API base (models, skills, memory, uploads)
DEERFLOW_LANGGRAPH_URL${DEERFLOW_URL}/api/langgraphLangGraph 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.

Show full SKILL.md (208 more words)Show less
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:

  1. Checks health
  2. Creates a thread
  3. Streams the run and collects the final AI response
  4. 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.

© bytedance, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (scripts) in skills/public/claude-to-deerflow of bytedance/deer-flow.

  • SKILL.md
  • scripts/chat.sh
  • scripts/status.sh

Open the folder on GitHubat commit 8a3350a

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in bytedance/deer-flow, which our catalogue first saw on October 7, 2026.

Compare with similar skills

DeerFlow HTTP API Client next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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AI Agent Developmentaiskillstore/marketplace4333 repos~1kAutomated safety check: PassNone
Lindy Reference Architecturejeremylongshore/tons-of-skills-marketplace2.8k—~3.2kAutomated safety check: PassMIT
Claw Multi AgentLeoYeAI/openclaw-master-skills2.2k—~5.5kAutomated safety check: PassMIT

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Works with

Categories

Questions about DeerFlow HTTP API Client

What does DeerFlow HTTP API Client do?

Talks to a running DeerFlow agent platform over its HTTP API to send research questions, stream replies, check health and manage models, skills, memory and uploads. DeerFlow is an agent platform built on LangGraph, and it exposes two API surfaces behind an Nginx reverse proxy: a Gateway API for REST endpoints such as models, skills, memory and uploads, and a LangGraph-compatible API for threads, runs and streaming. The agent reads the `DEERFLOW_URL` variable, which defaults to `http://localhost:2026`, along with the optional gateway and LangGraph overrides, before making any request.

When should I use DeerFlow HTTP API Client?

DeerFlow HTTP API Client fits situations like: delegating a long research task to a running DeerFlow instance; checking that a DeerFlow server is up before sending work; listing the models, skills or agents available in DeerFlow; uploading a file to a DeerFlow thread for analysis.

How do I install DeerFlow HTTP API Client in Claude Code?

Run `npx skills add bytedance/deer-flow --skill claude-to-deerflow -a claude-code`. Or copy the skill folder (skills/public/claude-to-deerflow in bytedance/deer-flow) into .claude/skills/claude-to-deerflow in your project. Claude Code loads it when a task matches its description.

How do I install DeerFlow HTTP API Client in Codex?

Run `npx skills add bytedance/deer-flow --skill claude-to-deerflow -a codex`. Or copy the skill folder (skills/public/claude-to-deerflow in bytedance/deer-flow) into .agents/skills/claude-to-deerflow in your project. Codex loads it when a task matches its description.

Can I use DeerFlow HTTP API Client in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add bytedance/deer-flow --skill claude-to-deerflow -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/claude-to-deerflow, .gemini/skills/claude-to-deerflow, .github/skills/claude-to-deerflow and .opencode/skills/claude-to-deerflow in your project.

What does DeerFlow HTTP API Client need to run?

Going by SKILL.md and its folder, DeerFlow HTTP API Client needs a shell for the scripts in its folder and the command-line tools its instructions call (curl and bash). Our summary lists: A running DeerFlow instance; `curl` to call its HTTP API.

Does DeerFlow HTTP API Client access the network?

SKILL.md contains no URLs. Its commands use curl, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is DeerFlow HTTP API Client safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does DeerFlow HTTP API Client use?

DeerFlow HTTP API Client is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does DeerFlow HTTP API Client use?

About 1.7k tokens (SKILL.md is roughly 6.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to DeerFlow HTTP API Client?

Skills that share tags, products or a category with DeerFlow HTTP API Client: Mission Control Agent API (builderz-labs/mission-control, 6.3k stars), Agents Build (aws/agent-toolkit-for-aws, 2.8k stars), AI Agent Development (aiskillstore/marketplace, 433 stars) and Lindy Reference Architecture (jeremylongshore/tons-of-skills-marketplace, 2.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains DeerFlow HTTP API Client?

bytedance (a GitHub organization) maintains it in bytedance/deer-flow, which has 83,674 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on October 11, 2026.

Source: bytedance/deer-flow on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.