# Fireworks AI

```json
{
  "name": "Fireworks AI",
  "slug": "fireworks_ai",
  "url": "https://composio.dev/toolkits/fireworks_ai",
  "markdown_url": "https://composio.dev/toolkits/fireworks_ai.md",
  "logo_url": "https://logos.composio.dev/api/fireworks_ai",
  "categories": [
    "ai & machine learning"
  ],
  "is_composio_managed": false,
  "updated_at": "2026-08-20T15:34:58.906Z"
}
```

![Fireworks AI logo](https://logos.composio.dev/api/fireworks_ai)

## Description

Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with Fireworks AI MCP or direct API to run model inference, manage deployments, create datasets, launch fine-tuning jobs, and review evaluations through natural language.

## Summary

Fireworks AI is a serverless AI platform for model inference, fine-tuning, deployments, datasets, and evaluations.
Use it to run fast open-model workflows without managing GPU infrastructure.

## Categories

- ai & machine learning

## Toolkit Details

- Tools: 9

## Images

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

## Authentication

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

## Suggested Prompts

- List active Fireworks AI deployments
- Run Llama inference on customer text
- Create dataset for fine tuning

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `FIREWORKS_AI_CREATE_CHAT_COMPLETION` | Create Chat Completion | Generate one non-streaming OpenAI-compatible chat completion from role-based messages using a caller-supplied Fireworks model or deployment ID. |
| `FIREWORKS_AI_CREATE_EMBEDDINGS` | Create Embeddings | Create embedding vectors for one or more caller-provided inputs using a caller-supplied Fireworks embedding model. |
| `FIREWORKS_AI_GENERATE_MODEL_RESPONSE` | Generate Model Response | Generate one non-streaming Responses API result, optionally continuing a stored response or using function, MCP, or SSE tools; storage is off by default. |
| `FIREWORKS_AI_GET_DEPLOYMENT` | Get Deployment | Return configuration and serving status for one Fireworks deployment without scaling or modifying it. |
| `FIREWORKS_AI_GET_MODEL` | Get Model | Return metadata and status for one model resource in a Fireworks account; this does not test whether the model can serve inference. |
| `FIREWORKS_AI_LIST_ACCOUNTS` | List Accounts | Return one page of Fireworks accounts accessible to the API key so an agent can obtain account IDs for model and deployment discovery. |
| `FIREWORKS_AI_LIST_DEPLOYMENTS` | List Deployments | Return one page of deployment resources in a Fireworks account for deployment ID discovery and serving-capacity and status inspection. |
| `FIREWORKS_AI_LIST_MODELS` | List Models | Return one page of model resources in a Fireworks account for model-ID discovery and status inspection; availability for inference is not guaranteed. |
| `FIREWORKS_AI_RERANK_DOCUMENTS` | Rerank Documents | Rank a provided document list by relevance to a query using an optional caller-supplied Fireworks reranker model. |

## Supported Triggers

None listed.

## Installation and MCP Setup

### Path 1: SDK Installation

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

Install the Composio SDK
```python
pip install composio_openai
```

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

#### Path 1, Step 2: Initialize Composio and Create Tool Router Session

Import and initialize Composio client, then create a Tool Router session
```python
from openai import OpenAI
from composio import Composio
from composio_openai import OpenAIResponsesProvider

composio = Composio(provider=OpenAIResponsesProvider())
openai = OpenAI()
session = composio.create(user_id='your-user-id')
```

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

const composio = new Composio({
  provider: new OpenAIResponsesProvider(),
});
const openai = new OpenAI({});
const session = await composio.create('your-user-id');
```

#### Path 1, Step 3: Execute Fireworks AI Tools via Tool Router with Your Agent

Get tools from Tool Router session and execute Fireworks AI actions with your Agent
```python
tools = session.tools
response = openai.responses.create(
  model='gpt-4.1',
  tools=tools,
  input=[{
    'role': 'user',
    'content': 'List active Fireworks AI deployments'
  }]
)
result = composio.provider.handle_tool_calls(
  response=response,
  user_id='your-user-id'
)
print(result)
```

```typescript
const tools = session.tools;
const response = await openai.responses.create({
  model: 'gpt-4.1',
  tools: tools,
  input: [{
    role: 'user',
    content: 'List active Fireworks AI deployments'
  }],
});
const result = await composio.provider.handleToolCalls(
  'your-user-id',
  response.output
);
console.log(result);
```

### Path 2: MCP Server Setup

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

Install the Composio SDK for Python or TypeScript
```python
pip install composio claude-agent-sdk
```

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

#### Path 2, Step 2: Initialize Client and Create Tool Router Session

Import and initialize the Composio client, then create a Tool Router session for Fireworks AI
```python
from composio import Composio
from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions

composio = Composio(api_key='your-composio-api-key')
session = composio.create(user_id='your-user-id')
url = session.mcp.url
```

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

const composio = new Composio({ apiKey: 'your-api-key' });
const session = await composio.create('your-user-id');
console.log(`Tool Router session created: ${session.mcp.url}`);
```

#### Path 2, Step 3: Connect to AI Agent

Use the MCP server with your AI agent (Anthropic Claude or Mastra)
```python
import asyncio

options = ClaudeAgentOptions(
    permission_mode='bypassPermissions',
    mcp_servers={
        'tool_router': {
            'type': 'http',
            'url': url,
            'headers': {
                'x-api-key': 'your-composio-api-key'
            }
        }
    },
    system_prompt='You are a helpful assistant with access to Fireworks AI tools.',
    max_turns=10
)

async def main():
    async with ClaudeSDKClient(options=options) as client:
        await client.query('List active Fireworks AI deployments')
        async for message in client.receive_response():
            if hasattr(message, 'content'):
                for block in message.content:
                    if hasattr(block, 'text'):
                        print(block.text)

asyncio.run(main())
```

```typescript
import { openai } from '@ai-sdk/openai';
import { experimental_createMCPClient as createMCPClient } from '@ai-sdk/mcp';
import { generateText } from 'ai';

const client = await createMCPClient({
  transport: {
    type: 'http',
    url: session.mcp.url,
    headers: {
      'x-api-key': 'your-composio-api-key',
    },
  },
});

const tools = await client.tools();
const { text } = await generateText({
  model: openai('gpt-4o'),
  tools,
  messages: [{
    role: 'user',
    content: 'List active Fireworks AI deployments'
  }],
  maxSteps: 5,
});

console.log(`Agent: ${text}`);
```

## Why Use Composio?

### 1. AI Native Fireworks AI Integration

- Supports both Fireworks AI MCP and direct API based integrations
- Structured, LLM-friendly schemas for reliable model, dataset, deployment, and evaluation actions
- Rich coverage for reading, writing, and querying Fireworks AI resources without bespoke integration code

### 2. Managed Auth

- Secure API key handling so your agents don't need hard-coded Fireworks AI credentials
- Central place to manage, scope, and revoke Fireworks AI access
- Per user and per environment credentials for safer development and production use

### 3. Agent Optimized Design

- Tools are designed so language models can reliably understand Fireworks AI actions and inputs
- Execution logs show what your agent ran, when it ran, and which Fireworks AI account it used
- Cleaner error handling helps agents recover when an inference, dataset, or deployment action needs adjustment

### 4. Enterprise Grade Security

- Fine-grained RBAC so you control which agents and users can access Fireworks AI
- Scoped, least privilege access to Fireworks AI resources like models, deployments, datasets, and evaluations
- Full audit trail of agent actions to support review, debugging, and compliance

## Use Fireworks AI with any AI Agent Framework

Choose a framework you want to connect Fireworks AI with:

None listed.

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## Frequently Asked Questions

### Do I need my own developer credentials to use Fireworks AI with Composio?

Yes, Fireworks AI 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)