# How to integrate Typefully MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Typefully MCP with OpenAI Agents SDK",
  "toolkit": "Typefully",
  "toolkit_slug": "typefully",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/typefully/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/typefully/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-10-12T13:32:00.464Z"
}
```

## Introduction

This guide walks you through connecting Typefully to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Typefully agent that can draft a new ai-generated tweet thread, list your recently published typefully posts, fetch unread notifications from your typefully inbox through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Typefully account through Composio's Typefully MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Typefully with

- [Claude Code](https://composio.dev/toolkits/typefully/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/typefully/framework/claude-cowork)
- [Claude Agent SDK](https://composio.dev/toolkits/typefully/framework/claude-agents-sdk)
- [Codex](https://composio.dev/toolkits/typefully/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/typefully/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/typefully/framework/hermes-agent)
- [Atomic Agent](https://composio.dev/toolkits/typefully/framework/atomic-agent)
- [Google ADK](https://composio.dev/toolkits/typefully/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/typefully/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/typefully/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/typefully/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/typefully/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/typefully/framework/crew-ai)
- [Pydantic AI](https://composio.dev/toolkits/typefully/framework/pydantic-ai)
- [AutoGen](https://composio.dev/toolkits/typefully/framework/autogen)

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Install the necessary dependencies
- Initialize Composio and create a Tool Router session for Typefully
- Configure an AI agent that can use Typefully as a tool
- Run a live chat session where you can ask the agent to perform Typefully operations

## What is OpenAI Agents SDK?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.
Key features include:
- Hosted MCP Tools: Connect to external services through hosted MCP endpoints
- SQLite Sessions: Persist conversation history across interactions
- Simple API: Clean interface with Agent, Runner, and tool configuration
- Streaming Support: Real-time response streaming for interactive applications

## What is the Typefully MCP server, and what's possible with it?

The Typefully MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Typefully account. It provides structured and secure access to your Typefully workspace, so your agent can create content drafts, manage notifications, and stay on top of publishing activity on your behalf.
- Automated content drafting: Let your agent generate and save new draft posts directly to your Typefully account for later review or editing.
- Real-time notification retrieval: Ask your agent to fetch your latest Typefully notifications, filtered by inbox or activity, so you never miss important updates.
- Review recently published content: Quickly get a list of your most recent published drafts, making it easy to track your publishing history and monitor engagement.
- Manage scheduled drafts: Have your agent pull up all your recently scheduled drafts, helping you keep tabs on your content calendar and upcoming posts.
- Effortless notification management: Direct your agent to mark notifications as read, keeping your workspace tidy and ensuring you stay focused on what matters.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `TYPEFULLY_CREATE_DRAFT` | Create Draft (v2) | Create a new draft with platform-specific content for multi-platform publishing. Use this action when you need to create a draft that can target multiple social media platforms (X, LinkedIn, Threads, Bluesky, Mastodon) simultaneously. The draft can be saved for later editing, scheduled for a specific time or next available slot, or published immediately. Supports scheduling options via publish_at: "now" for immediate publishing, "next-free-slot" for your next available posting window, or an ISO 8601 datetime string with timezone for a specific scheduled time. |
| `TYPEFULLY_CREATE_TAG` | Create Tag | Creates a new tag for organizing drafts within a social set in Typefully. Use this action when you need to add a new organizational tag to help categorize and group drafts within a specific social account. The tag's slug is automatically generated from the provided name. |
| `TYPEFULLY_DELETE_DRAFT` | Delete Draft | Permanently deletes a draft from Typefully. This action cannot be undone. Use this action when you need to remove a draft that is no longer needed. WARNING: This is a destructive operation. Once deleted, the draft cannot be recovered. |
| `TYPEFULLY_GET_CURRENT_USER` | Get Current User | Get the current authenticated user's information. Returns user details including profile information, email, signup date, and optional profile image URL. Use this action when you need to retrieve the profile information of the currently authenticated Typefully user, such as for displaying user details or verifying authentication. |
| `TYPEFULLY_GET_DRAFT` | Get Draft | Retrieves a single draft by its ID with full details including platform-specific content, tags, status, and scheduling information. Use this action when you need to retrieve comprehensive details about a specific draft in Typefully. This action requires both the social_set_id and draft_id path parameters to identify the specific draft. |
| `TYPEFULLY_GET_MEDIA_STATUS` | Get Media Status | Check the processing status of an uploaded media file. Use when you need to poll the status of a media file after uploading it. Poll this endpoint until status becomes 'ready' before using the media in drafts. Returns status (processing/ready/failed) and media_urls when ready. This action is read-only and idempotent. |
| `TYPEFULLY_GET_QUEUE` | Get Queue | Get the scheduled content queue for a social set within a date range. Returns upcoming scheduled drafts organized by day with their scheduled times. Use this action when you need to view what content is scheduled for a specific date range for a particular social media account in Typefully. |
| `TYPEFULLY_GET_QUEUE_SCHEDULE` | Get Queue Schedule | Get the queue schedule configuration for a social set, including posting slots and timezone settings. Use this action when you need to retrieve the scheduling rules and timezone configuration for a social media account in Typefully. |
| `TYPEFULLY_GET_SOCIAL_SET` | Get Social Set | Get detailed information about a specific social set, including all connected platforms (X, LinkedIn, Mastodon, Threads, Bluesky) with account details and profile information. Use this action when you need to retrieve the details and platform connections for a specific social set by its ID. |
| `TYPEFULLY_INITIALIZE_MEDIA_UPLOAD` | Initialize Media Upload | Initializes a media upload by returning a presigned URL. Use when you need to upload images, videos, GIFs, or PDFs to attach to draft posts. First call this action to get a `media_id` and `upload_url`. Then PUT your file content directly to the `upload_url`. Finally, use the `media_id` in your draft content to attach the media. This action is idempotent — calling it multiple times with the same parameters will return new (unused) presigned URLs. |
| `TYPEFULLY_LIST_DRAFTS` | List Drafts | List drafts for a social set with filtering and sorting options. Use this action when you need to retrieve drafts from a specific social set in Typefully. Supports filtering by status (draft, scheduled, published) and tags, and results are ordered by last edited date (most recent first) by default. Results are paginated with support for limit/offset-based pagination. |
| `TYPEFULLY_LIST_SOCIAL_SETS` | List Social Sets | List all social sets (groups of connected platform accounts) accessible to the authenticated user. Returns paginated list of social sets with basic info including id, username, name, and profile image. Use this action when you need to retrieve social sets for a user or display available accounts. |
| `TYPEFULLY_LIST_TAGS` | List Tags | List all tags for a social set. Tags help organize and categorize drafts. Use this action when you need to retrieve all tags associated with a specific social set to organize, filter, or categorize drafts within Typefully. |
| `TYPEFULLY_RESOLVE_LINKED_IN_ORGANIZATION` | Resolve LinkedIn Organization | Resolve a LinkedIn organization from its public URL. Returns the organization URN needed for mentions in LinkedIn posts. Use this action when you need to get the LinkedIn organization identifier to include company or school mentions in posts. |
| `TYPEFULLY_UPDATE_DRAFT` | Update Draft | Update an existing draft with partial update semantics. Use this action when you need to modify specific fields of an existing draft. Only the fields you provide will be updated; omitted fields remain unchanged. This action supports updating: content/title, scheduling (publish_at), tags, scratchpad notes, sharing options, or platform configurations. Note: Cannot update drafts that have already been published. |
| `TYPEFULLY_UPDATE_QUEUE_SCHEDULE` | Update Queue Schedule | Replace the queue schedule configuration for a social set. Defines the posting slots for scheduled content. Use this action when you need to update or configure the posting schedule for a social account, such as changing the days and times when content should be published. This performs a full replacement of the schedule rules — existing rules will be overwritten with the new rules provided. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Typefully MCP server is an implementation of the Model Context Protocol that connects your AI agent to Typefully. It provides structured and secure access so your agent can perform Typefully operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before starting, make sure you have:
- Composio API Key and OpenAI API Key
- Primary know-how of OpenAI Agents SDK
- A live Typefully project
- Some knowledge of Python or Typescript

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) and create an API key. You'll need credits to use the models, or you can connect to another model provider.
- Keep the API key safe.
Composio API Key
- Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Go to Settings and copy your API key.

### 2. Install dependencies

Install the Composio SDK and the OpenAI Agents SDK.
```python
pip install composio_openai_agents openai-agents python-dotenv
```

```typescript
npm install @composio/openai-agents @openai/agents dotenv
```

### 3. Set up environment variables

Create a .env file and add your OpenAI and Composio API keys.
```bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com
```

### 4. Import dependencies

What's happening:
- You're importing all necessary libraries.
- The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Typefully.
```python
import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
```

### 5. Set up the Composio instance

No description provided.
```python
load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
```

```typescript
dotenv.config();

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
```

### 6. Create a Tool Router session

What is happening:
- You give the Tool Router the user id and the toolkits you want available. Here, it is only typefully.
- The router checks the user's Typefully connection and prepares the MCP endpoint.
- The returned session.mcp.url is the MCP URL that your agent will use to access Typefully.
- This approach keeps things lightweight and lets the agent request Typefully tools only when needed during the conversation.
```python
# Create a Typefully Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["typefully"]
)

mcp_url = session.mcp.url
```

```typescript
// Create Tool Router session for Typefully
const session = await composio.create(userId as string, {
  toolkits: ['typefully'],
});
const mcpUrl = session.mcp.url;
```

### 7. Configure the agent

No description provided.
```python
# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Typefully. "
        "Help users perform Typefully operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
```

```typescript
// Configure agent with MCP tool
const agent = new Agent({
  name: 'Assistant',
  model: 'gpt-5',
  instructions:
    'You are a helpful assistant that can access Typefully. Help users perform Typefully operations through natural language.',
  tools: [
    hostedMcpTool({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: 'never',
    }),
  ],
});
```

### 8. Start chat loop and handle conversation

No description provided.
```python
print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
```

```typescript
// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

// Simple CLI
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: 'You: ',
});

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

rl.on('line', async (userInput) => {
  const text = userInput.trim();

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

  if (!text) {
    rl.prompt();
    return;
  }

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

rl.on('close', () => {
  console.log('\n👋 Session ended.');
  process.exit(0);
});
```

## Complete Code

```python
import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["typefully"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Typefully. "
        "Help users perform Typefully operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['typefully'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new Agent({
    name: 'Assistant',
    model: 'gpt-5',
    instructions:
      'You are a helpful assistant that can access Typefully. Help users perform Typefully operations through natural language.',
    tools: [
      hostedMcpTool({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

  // Simple CLI
  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: ',
  });

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

  rl.on('line', async (userInput) => {
    const text = userInput.trim();

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

    if (!text) {
      rl.prompt();
      return;
    }

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\n');
    }

    rl.prompt();
  });

  rl.on('close', () => {
    console.log('\nSession ended.');
    process.exit(0);
  });
}

main().catch((err) => {
  console.error('Fatal error:', err);
  process.exit(1);
});
```

## Conclusion

This was a starter code for integrating Typefully MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Typefully.
Key features:
- Hosted MCP tool integration through Composio's Tool Router
- SQLite session persistence for conversation history
- Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

## How to build Typefully MCP Agent with another framework

- [Claude Code](https://composio.dev/toolkits/typefully/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/typefully/framework/claude-cowork)
- [Claude Agent SDK](https://composio.dev/toolkits/typefully/framework/claude-agents-sdk)
- [Codex](https://composio.dev/toolkits/typefully/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/typefully/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/typefully/framework/hermes-agent)
- [Atomic Agent](https://composio.dev/toolkits/typefully/framework/atomic-agent)
- [Google ADK](https://composio.dev/toolkits/typefully/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/typefully/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/typefully/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/typefully/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/typefully/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/typefully/framework/crew-ai)
- [Pydantic AI](https://composio.dev/toolkits/typefully/framework/pydantic-ai)
- [AutoGen](https://composio.dev/toolkits/typefully/framework/autogen)

## Related Toolkits

- [Composio](https://composio.dev/toolkits/composio) - Composio is an integration platform that connects AI agents with hundreds of business tools. It streamlines authentication and lets you trigger actions across services—no custom code needed.
- [Composio search](https://composio.dev/toolkits/composio_search) - Composio search is a unified web search toolkit spanning travel, e-commerce, news, financial markets, images, and more. It lets you and your apps tap into up-to-date web data from a single, easy-to-integrate service.
- [Perplexityai](https://composio.dev/toolkits/perplexityai) - Perplexityai delivers natural, conversational AI models for generating human-like text. Instantly get context-aware, high-quality responses for chat, search, or complex workflows.
- [Browser tool](https://composio.dev/toolkits/browser_tool) - Browser tool is a virtual browser integration that lets AI agents interact with the web programmatically. It enables automated browsing, scraping, and action-taking from any AI workflow.
- [Ai ml api](https://composio.dev/toolkits/ai_ml_api) - Ai ml api is a suite of AI/ML models for natural language and image tasks. It provides fast, scalable access to advanced AI capabilities for your apps and workflows.
- [Aivoov](https://composio.dev/toolkits/aivoov) - Aivoov is an AI-powered text-to-speech platform offering 1,000+ voices in over 150 languages. Instantly turn written content into natural, human-like audio for any application.
- [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.
- [AltTextLab](https://composio.dev/toolkits/alt_text_lab) - AltTextLab is an AI service that generates accessible, SEO-aware alt text for images. It helps teams make image content easier to understand, index, and publish.
- [Anthropic administrator](https://composio.dev/toolkits/anthropic_administrator) - Anthropic administrator is an API for managing Anthropic organizational resources like members, workspaces, and API keys. It helps you automate admin tasks and streamline resource management across your Anthropic organization.
- [Api labz](https://composio.dev/toolkits/api_labz) - Api labz is a platform offering a suite of AI-driven APIs and workflow tools. It helps developers automate tasks and build smarter, more efficient applications.
- [Apiframe](https://composio.dev/toolkits/apiframe) - Apiframe is an API platform for generating and managing AI images, videos, music, uploads, assets, jobs, and custom LoRAs. It gives developers one clean API for creative AI workflows without juggling multiple model providers.
- [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.
- [Arize AX](https://composio.dev/toolkits/arize_ax) - Arize AX is an AI engineering platform for tracing, evaluating, and improving AI applications. Use it to debug LLM behavior, compare experiments, and improve production AI quality.
- [Artificial Analysis](https://composio.dev/toolkits/artificial_analysis) - Artificial Analysis is an independent benchmarking platform for AI models and API providers. Use it to compare model intelligence, coding, math, pricing, latency, throughput, and arena rankings.
- [AssemblyAI](https://composio.dev/toolkits/assemblyai) - AssemblyAI is a speech-to-text and audio intelligence API for uploaded or hosted media. Use it to turn audio and video into accurate transcripts, summaries, and insights.
- [Astica ai](https://composio.dev/toolkits/astica_ai) - Astica ai provides APIs for computer vision, NLP, and voice synthesis. Integrate advanced AI features into your app with a single API key.
- [Avoma](https://composio.dev/toolkits/avoma) - Avoma is an AI meeting assistant for recording, transcribing, analyzing, and managing meetings, calls, notes, scorecards, and conversation intelligence. It helps teams turn conversations into searchable notes, follow-ups, coaching insights, and revenue intelligence.
- [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.
- [Black Forest Labs](https://composio.dev/toolkits/bfl) - 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.
- [Bland AI](https://composio.dev/toolkits/bland_ai) - Bland AI is a conversational AI platform for building voice agents, phone calls, messaging, and communication workflows. Use it to automate calling, evaluate conversations, and run voice operations at scale.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Typefully MCP?

With a standalone Typefully MCP server, the agents and LLMs can only access a fixed set of Typefully tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Typefully and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Typefully tools.

### Can I manage the permissions and scopes for Typefully while using Tool Router?

Yes, absolutely. You can configure which Typefully scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

### How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Typefully data and credentials are handled as safely as possible.

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