# Eden AI

```json
{
  "name": "Eden AI",
  "slug": "eden_ai",
  "url": "https://composio.dev/toolkits/eden_ai",
  "markdown_url": "https://composio.dev/toolkits/eden_ai.md",
  "logo_url": "https://logos.composio.dev/api/eden_ai",
  "categories": [
    "ai & machine learning"
  ],
  "is_composio_managed": false,
  "updated_at": "2026-08-20T15:31:38.407Z"
}
```

![Eden AI logo](https://logos.composio.dev/api/eden_ai)

## Description

Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with Eden AI MCP or direct API to generate text, analyze images, transcribe audio, and process documents through natural language.

## Summary

Eden AI is a unified AI API for text, image, audio, document, and multimodal models.
Use it to route workloads across providers without rebuilding provider-specific integrations.

## Categories

- ai & machine learning

## Toolkit Details

- Tools: 10

## Images

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

## Authentication

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

## Suggested Prompts

- Classify support tickets using Eden AI
- Generate product images with Eden AI
- Transcribe meeting audio through Eden AI

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `EDEN_AI_COUNT_ANTHROPIC_TOKENS` | Count Anthropic Tokens | Count input tokens for an Anthropic-format message request before generation, including system content and tool definitions. |
| `EDEN_AI_CREATE_ANTHROPIC_MESSAGE` | Create Anthropic Message | Generate a non-streaming Anthropic-compatible message with content blocks, stop reason, token usage, provider metadata, and Eden AI cost. Each call runs a paid model and consumes Eden AI credits. |
| `EDEN_AI_CREATE_CHAT_COMPLETION` | Create Chat Completion | Generate a non-streaming OpenAI-compatible chat completion with a current Eden AI model and return its choices, token usage, provider, and cost. Each call runs a paid model and consumes Eden AI credits. |
| `EDEN_AI_CREATE_EMBEDDINGS` | Create Embeddings | Create embeddings for one text or a batch of texts and return vectors with model, usage, provider, and cost metadata. Each call runs a paid model and consumes Eden AI credits. |
| `EDEN_AI_CREATE_RESPONSE` | Create Response | Create or continue a synchronous OpenAI Responses-compatible text response, stored by default for later retrieval, and return its ID, structured output, text, usage, provider, and cost. |
| `EDEN_AI_DISCOVER_CAPABILITIES` | Discover AI Capabilities | Find current Eden AI models or inspect Universal AI feature schemas, providers, pricing, and regions before an execution call. |
| `EDEN_AI_GET_COST_OVERVIEW` | Get Cost Overview | Return current account credits and, when a date range is supplied, aggregated consumption filtered by provider or subfeature. |
| `EDEN_AI_GET_RESPONSE` | Get Response | Retrieve a previously stored Responses API object by ID, including its status, text output, structured output, usage, and canonical model. |
| `EDEN_AI_MODERATE_TEXT` | Moderate Text | Classify one text or a batch of texts for safety categories and return flags, category scores, applied input types, provider, and cost. Each call runs a paid model and consumes Eden AI credits. |
| `EDEN_AI_RUN_UNIVERSAL_AI` | Run Universal AI | Run one synchronous Eden AI Universal AI feature using a current model and feature-specific input. Call DISCOVER_CAPABILITIES first for the exact model ID and runtime input schema. Returns normalized output, provider, and cost, with the raw provider response only when requested. Each call runs a paid model and consumes Eden AI credits. |

## 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 Eden AI Tools via Tool Router with Your Agent

Get tools from Tool Router session and execute Eden AI actions with your Agent
```python
tools = session.tools
response = openai.responses.create(
  model='gpt-4.1',
  tools=tools,
  input=[{
    'role': 'user',
    'content': 'Use Eden AI to summarize this product review text and classify its sentiment: The setup was fast, but the export quality needs work.'
  }]
)
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: 'Use Eden AI to summarize this product review text and classify its sentiment: The setup was fast, but the export quality needs work.'
  }],
});
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 Eden 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 Eden AI tools.',
    max_turns=10
)

async def main():
    async with ClaudeSDKClient(options=options) as client:
        await client.query('Use Eden AI to summarize this product review text and classify its sentiment: The setup was fast, but the export quality needs work.')
        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: 'Use Eden AI to summarize this product review text and classify its sentiment: The setup was fast, but the export quality needs work.'
  }],
  maxSteps: 5,
});

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

## Why Use Composio?

### 1. AI Native Eden AI Integration

- Supports both Eden AI MCP and direct API based integrations
- Structured, LLM-friendly schemas for reliable text, image, audio, document, and multimodal execution
- Use Eden AI through Tool Router sessions or MCP servers created with mcp.create()

### 2. Managed Auth

- Store Eden AI API keys securely instead of hard-coding them in agent code
- Create scoped Eden AI auth configs with auth_configs.create() and connect user API keys with connected_accounts.link()
- Manage, rotate, and revoke Eden AI access from one place across users and environments

### 3. Agent Optimized Design

- Tools are tuned for AI agents, so model prompts map cleanly to Eden AI actions
- Clear input schemas help agents choose the right Eden AI capability for summaries, transcription, classification, OCR, and generation
- Comprehensive execution logs show what ran, when, and on whose behalf

### 4. Enterprise Grade Security

- Fine-grained RBAC so you control which agents and users can access Eden AI
- Scoped, least privilege access to Eden AI credentials and workloads
- Full audit trail of agent actions to support review, debugging, and compliance

## Use Eden AI with any AI Agent Framework

Choose a framework you want to connect Eden AI with:

None listed.

## Related Toolkits

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- [All images ai](https://composio.dev/toolkits/all_images_ai) - All-Images.ai is an AI-powered image generation and management platform. It helps you create, search, and organize images effortlessly with advanced AI capabilities.
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- [Apipie ai](https://composio.dev/toolkits/apipie_ai) - Apipie ai is an AI model aggregator offering a single API for accessing top AI models from multiple providers. It helps developers build cost-efficient, latency-optimized AI solutions without juggling multiple integrations.
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- [Bigml](https://composio.dev/toolkits/bigml) - BigML is a machine learning platform that lets you build, train, and deploy predictive models from your data. Its intuitive interface and robust API make machine learning accessible and efficient.
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## Frequently Asked Questions

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

Yes, Eden AI requires you to configure your own API key credentials. 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)