# Speechmatics

```json
{
  "name": "Speechmatics",
  "slug": "speechmatics",
  "url": "https://composio.dev/toolkits/speechmatics",
  "markdown_url": "https://composio.dev/toolkits/speechmatics.md",
  "logo_url": "https://logos.composio.dev/api/speechmatics",
  "categories": [
    "ai & machine learning"
  ],
  "is_composio_managed": false,
  "updated_at": "2026-08-20T15:34:14.221Z"
}
```

![Speechmatics logo](https://logos.composio.dev/api/speechmatics)

## Description

Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with Speechmatics MCP or direct API to submit transcription jobs, track processing status, retrieve transcripts, and review usage reports through natural language.

## Summary

Speechmatics is a speech-to-text API for async audio and video transcription.
It gives you accurate transcripts, job control, and usage reporting at scale.

## Categories

- ai & machine learning

## Toolkit Details

- Tools: 7

## Images

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

## Authentication

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

## Suggested Prompts

- Transcribe yesterday's customer interview recording
- Check status of latest transcription jobs
- Retrieve transcript for completed media job

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `SPEECHMATICS_CREATE_TRANSCRIPTION_JOB` | Create Transcription Job | Create an asynchronous Speechmatics transcription job from a publicly fetchable media URL and return its job ID. |
| `SPEECHMATICS_DELETE_TRANSCRIPTION_JOB` | Delete Transcription Job | Delete a transcription job and its associated transcript and resources, optionally forcing termination of a running job. |
| `SPEECHMATICS_DISCOVER_SPEECH_FEATURES` | Discover Speech Features | Return Speechmatics' current Batch languages, locales, domains, translation support, and language-identification capabilities. |
| `SPEECHMATICS_GET_TRANSCRIPT` | Get Transcript | Retrieve a transcription job's completed transcript as structured JSON v2, plain text, or SRT text. |
| `SPEECHMATICS_GET_TRANSCRIPTION_JOB` | Get Transcription Job | Get a transcription job's status, configuration, duration, and processing errors, optionally waiting briefly for a terminal state. |
| `SPEECHMATICS_GET_USAGE` | Get Usage | Get Batch transcription counts and audio duration aggregated over an optional UTC date range. |
| `SPEECHMATICS_LIST_TRANSCRIPTION_JOBS` | List Transcription Jobs | List transcription jobs in the connected US1 project, newest first, with an agent-controlled continuation cursor. |

## 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 Speechmatics Tools via Tool Router with Your Agent

Get tools from Tool Router session and execute Speechmatics actions with your Agent
```python
tools = session.tools
response = openai.responses.create(
  model='gpt-4.1',
  tools=tools,
  input=[{
    'role': 'user',
    'content': 'List my recent Speechmatics transcription jobs and show their statuses'
  }]
)
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 my recent Speechmatics transcription jobs and show their statuses'
  }],
});
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 Speechmatics
```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 Speechmatics tools.',
    max_turns=10
)

async def main():
    async with ClaudeSDKClient(options=options) as client:
        await client.query('List my recent Speechmatics transcription jobs and show their statuses')
        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 my recent Speechmatics transcription jobs and show their statuses'
  }],
  maxSteps: 5,
});

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

## Why Use Composio?

### 1. AI Native Speechmatics Integration

- Supports both Speechmatics MCP and direct API based integrations
- Structured, LLM-friendly schemas for reliable transcription, job lookup, and transcript retrieval
- Pre-built tools mean your agent can work with Speechmatics without custom integration code

### 2. Secure API Key Auth

- Speechmatics uses API key auth, and Composio keeps those keys out of your agent code
- Create auth configs with auth_configs.create() and link user credentials with connected_accounts.link()
- Central place to manage, scope, and revoke Speechmatics access per user and environment

### 3. Agent Optimized Design

- Tools are tuned for language models, so agents can submit jobs, check status, and fetch transcripts with less guesswork
- Comprehensive execution logs help you see what ran, when, and on whose behalf
- Works with Tool Router sessions and MCP flows, including mcp.create() based server setup where supported

### 4. Enterprise Grade Security

- Fine-grained RBAC so you control which agents and users can access Speechmatics
- Scoped, least privilege access for transcription and reporting workflows
- Full audit trail of agent actions to support review, debugging, and compliance

## Use Speechmatics with any AI Agent Framework

Choose a framework you want to connect Speechmatics with:

None listed.

## Related Toolkits

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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 Speechmatics with Composio?

Yes, Speechmatics 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)