# Black Forest Labs

```json
{
  "name": "Black Forest Labs",
  "slug": "bfl",
  "url": "https://composio.dev/toolkits/bfl",
  "markdown_url": "https://composio.dev/toolkits/bfl.md",
  "logo_url": "https://logos.composio.dev/api/bfl",
  "categories": [
    "ai & machine learning"
  ],
  "is_composio_managed": false,
  "updated_at": "2026-10-08T05:31:06.178Z"
}
```

![Black Forest Labs logo](https://logos.composio.dev/api/bfl)

## Description

Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with Black Forest Labs MCP or direct API to generate images, edit visual content, create videos, and monitor generation jobs through natural language.

## Summary

Black Forest Labs provides hosted FLUX models for generating and editing images and videos.
It offers fast, flexible media creation with asynchronous processing and fine-tuning support.

## Categories

- ai & machine learning

## Toolkit Details

- Tools: 14

## Images

- Logo: https://logos.composio.dev/api/bfl

## Authentication

- **Api Key**
  - Type: `api_key`
  - Description: Api Key authentication for Black Forest Labs.
  - Setup:
    - Configure Api Key credentials for Black Forest Labs.
    - Use the credentials when creating an auth config in Composio.

## Suggested Prompts

- Generate a product image with FLUX
- Edit a portrait using a text prompt
- Check remaining Black Forest Labs credits

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `BFL_DEBLUR_IMAGE` | Deblur Image | Submit a paid asynchronous deblurring of an authorized image. Returns the task ID, exact polling URL, and quoted cost without waiting. |
| `BFL_EDIT_VIDEO` | Edit Video | Submit a paid asynchronous prompt-directed edit of an authorized source video. Returns the task ID, exact polling URL, and quoted per-second cost without waiting for or downloading the result. |
| `BFL_ERASE_IMAGE_OBJECT` | Erase Image Object | Submit a paid asynchronous removal of a masked object from an authorized image. Returns the task ID, exact polling URL, and quoted cost without waiting for or downloading the result. |
| `BFL_GENERATE_FINETUNED_IMAGE` | Generate Fine-Tuned Image | Submit a paid asynchronous FLUX fine-tuned image generation using an existing LoRA. Returns the task ID, exact polling URL, and quoted cost; it does not wait for or download the result. |
| `BFL_GENERATE_OR_EDIT_FLUX_2_KLEIN_IMAGE` | Generate or Edit FLUX.2 Klein Image | Submit a paid asynchronous FLUX.2 Klein image generation or authorized reference-image edit with the stable 4B or 9B model. Returns the task ID, exact polling URL, and quoted cost without waiting for or downloading the result. |
| `BFL_GENERATE_OR_EDIT_IMAGE` | Generate or Edit Image | Submit a paid asynchronous FLUX 3 image generation or authorized reference-image edit. Returns a task ID, exact polling URL, and quoted cost without waiting for or downloading the result. Moderation may end the task without media. Result URLs expire quickly; download promptly and preserve the original bytes and C2PA provenance metadata. |
| `BFL_GENERATE_VIDEO` | Generate Video | Submit a paid asynchronous FLUX 3 video task from text, authorized keyframes, a source video, or a prior draft cache. Video is charged by duration and resolution. Returns a task ID and exact polling URL without waiting for or downloading outputs. |
| `BFL_GET_CREDITS` | Get Credit Balance | Return the connected BFL project's current credit balance so funds can be checked before a paid generation or editing request. |
| `BFL_GET_FINETUNE` | Get Fine-Tune | Return details for one BFL fine-tune by ID; an absent or inaccessible fine-tune is reported as not found without distinguishing access denial. |
| `BFL_GET_GENERATION_RESULT` | Get Generation Result | Fetch one status update for an asynchronous BFL task using its exact returned polling URL or task ID. Returns pending, moderation, error, not-found, and ready states without looping, downloading media, or incurring a new generation charge. |
| `BFL_LIST_FINETUNES` | List Fine-Tunes | Return all fine-tunes accessible to the connected BFL project in one unpaginated response. |
| `BFL_OUTPAINT_IMAGE` | Outpaint Image | Submit a paid asynchronous expansion of an authorized image onto a larger canvas of at most 4,194,304 pixels. Fast mode requires a base64 source; high mode also accepts HTTP(S) URLs. Returns the task ID, exact polling URL, and quoted cost without waiting for or downloading the result. |
| `BFL_UPSCALE_VIDEO` | Upscale Video | Submit a paid asynchronous upscale for the first 20 seconds of an authorized video, with an optional content prompt and 1.5x-3x scale target. Returns the task ID, exact polling URL, and quoted cost without waiting. BFL charges video upscaling per output megapixel-second. |
| `BFL_VIRTUAL_TRY_ON` | Virtual Try-On | Submit a paid asynchronous virtual try-on using authorized person and garment images. Returns the task ID, exact polling URL, and quoted cost without waiting. |

## Supported Triggers

None listed.

## Installation and MCP Setup

### Path 1: SDK Installation

#### Path 1, Step 1: Install Composio

Install the Composio SDK, the OpenAI provider, and the OpenAI SDK
```python
pip install composio composio_openai openai
```

```typescript
npm install @composio/core @composio/openai openai
```

#### Path 1, Step 2: Create a Composio session

Initialize Composio with the OpenAI Responses provider and create a session scoped to Black Forest Labs
```python
import json
from openai import OpenAI
from composio import Composio
from composio_openai import OpenAIResponsesProvider

composio = Composio(provider=OpenAIResponsesProvider())
client = OpenAI()

session = composio.create(user_id="your-user-id", toolkits=["bfl"])
tools = session.tools()
```

```typescript
import OpenAI from "openai";
import { Composio } from "@composio/core";
import { OpenAIResponsesProvider } from "@composio/openai";

const composio = new Composio({ provider: new OpenAIResponsesProvider() });
const client = new OpenAI();

const session = await composio.create("your-user-id", { toolkits: ["bfl"] });
const tools = await session.tools();
```

#### Path 1, Step 3: Run Black Forest Labs tools with your agent

Send a request, execute the Black Forest Labs tool calls through the session, and print the final answer
```python
response = client.responses.create(
    model="gpt-5.6-sol",
    tools=tools,
    input=[{"role": "user", "content": "Generate an image of a red fox in a snowy forest at sunrise"}],
)

while True:
    tool_calls = [o for o in response.output if o.type == "function_call"]
    if not tool_calls:
        break
    results = composio.provider.handle_tool_calls(response=response, session=session)
    response = client.responses.create(
        model="gpt-5.6-sol",
        tools=tools,
        previous_response_id=response.id,
        input=[
            {"type": "function_call_output", "call_id": call.call_id, "output": json.dumps(results[i])}
            for i, call in enumerate(tool_calls)
        ],
    )

print(response.output_text)
```

```typescript
let response = await client.responses.create({
  model: "gpt-5.6-sol",
  tools,
  input: [{ role: "user", content: "Generate an image of a red fox in a snowy forest at sunrise" }],
});

while (response.output.some((o) => o.type === "function_call")) {
  const outputs = await composio.provider.handleToolCalls(session, response.output);
  response = await client.responses.create({
    model: "gpt-5.6-sol",
    tools,
    previous_response_id: response.id,
    input: outputs,
  });
}

console.log(response.output_text);
```

### Path 2: MCP Server Setup

#### Path 2, Step 1: Install Composio

Install the Composio SDK and your agent framework
```python
pip install composio claude-agent-sdk
```

```typescript
npm install @composio/core ai @ai-sdk/mcp @ai-sdk/openai
```

#### Path 2, Step 2: Create a session with MCP enabled

Create a session scoped to Black Forest Labs and read its MCP URL and headers
```python
from composio import Composio

composio = Composio()
session = composio.create(user_id="your-user-id", toolkits=["bfl"], mcp=True)
```

```typescript
import { Composio } from "@composio/core";

const composio = new Composio();
const { mcp } = await composio.create("your-user-id", {
  toolkits: ["bfl"],
  mcp: true,
});
```

#### Path 2, Step 3: Connect your agent to the MCP server

Pass the session's MCP URL and headers to your agent and run a Black Forest Labs request
```python
import asyncio
from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions, AssistantMessage, TextBlock

options = ClaudeAgentOptions(
    mcp_servers={
        "composio": {
            "type": "http",
            "url": session.mcp.url,
            "headers": session.mcp.headers,
        }
    },
    system_prompt="You are a helpful assistant with access to Black Forest Labs tools.",
    tools=[],
    allowed_tools=["mcp__composio__*"],
)

async def main():
    async with ClaudeSDKClient(options=options) as client:
        await client.query("Generate an image of a red fox in a snowy forest at sunrise")
        async for message in client.receive_response():
            if isinstance(message, AssistantMessage):
                for block in message.content:
                    if isinstance(block, TextBlock):
                        print(block.text)

asyncio.run(main())
```

```typescript
import { createMCPClient } from "@ai-sdk/mcp";
import { openai } from "@ai-sdk/openai";
import { generateText, stepCountIs } from "ai";

const client = await createMCPClient({
  transport: { type: "http", url: mcp.url, headers: mcp.headers },
});

const { text } = await generateText({
  model: openai("gpt-5.6-sol"),
  tools: await client.tools(),
  prompt: "Generate an image of a red fox in a snowy forest at sunrise",
  stopWhen: stepCountIs(10),
});

console.log(text);
await client.close();
```

## Why Use Composio?

### 1. AI Native Black Forest Labs Integration

- Supports both Black Forest Labs MCP and direct API based integrations
- Structured, LLM-friendly schemas for reliable FLUX image and video generation
- Rich coverage for creating media, polling results, managing fine-tunes, and checking credits

### 2. Managed Auth

- Securely stores and uses your Black Forest Labs API key
- Central place to manage, scope, and revoke Black Forest Labs access
- Per user and per environment credentials instead of hard-coded keys

### 3. Agent Optimized Design

- Tools are tuned using real error and success rates to improve reliability over time
- Comprehensive execution logs so you always know what ran, when, and on whose behalf

### 4. Enterprise Grade Security

- Fine-grained RBAC so you control which agents and users can access Black Forest Labs
- Scoped, least privilege access to Black Forest Labs generation and project resources
- Full audit trail of agent actions to support review and compliance

## Use Black Forest Labs with any AI Agent Framework

Choose a framework you want to connect Black Forest Labs with:

- [ChatGPT](https://composio.dev/toolkits/bfl/framework/chatgpt)
- [Claude Cowork](https://composio.dev/toolkits/bfl/framework/claude-cowork)
- [Hermes](https://composio.dev/toolkits/bfl/framework/hermes-agent)
- [Atomic Agent](https://composio.dev/toolkits/bfl/framework/atomic-agent)

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## Frequently Asked Questions

### Do I need my own developer credentials to use Black Forest Labs with Composio?

Yes, Black Forest Labs requires you to configure your own API key. Once set up, Composio handles secure credential storage and API request handling for you.

### Can I use multiple toolkits together?

Yes! Composio's Tool Router enables agents to use multiple toolkits. [Learn more](https://docs.composio.dev/tool-router/overview).

### Is Composio secure?

Composio is SOC 2 and ISO 27001 compliant with all data encrypted in transit and at rest. [Learn more](https://trust.composio.dev).

### What if the API changes?

Composio maintains and updates all toolkit integrations automatically, so your agents always work with the latest API versions.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)