# POMA Grill

```json
{
  "name": "POMA Grill",
  "slug": "poma_grill",
  "url": "https://composio.dev/toolkits/poma_grill",
  "markdown_url": "https://composio.dev/toolkits/poma_grill.md",
  "logo_url": "https://logos.composio.dev/api/poma_grill",
  "categories": [
    "document & file management"
  ],
  "is_composio_managed": false,
  "updated_at": "2026-10-03T05:32:35.906Z"
}
```

![POMA Grill logo](https://logos.composio.dev/api/poma_grill)

## Description

Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with POMA Grill MCP or direct API to ingest documents, index content, retrieve prompt-ready context, and manage project scopes through natural language.

## Summary

POMA Grill is a project-scoped context engine for ingesting and indexing documents.
Use it to manage indexed content and retrieve prompt-ready context for LLMs.

## Categories

- document & file management

## Toolkit Details

- Tools: 17

## Images

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

## Authentication

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

## Suggested Prompts

- Retrieve prompt-ready context for onboarding docs
- Search indexed specs for API breaking changes
- Summarize recent contract clauses from POMA Grill

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `POMA_GRILL_CANCEL_BUCKET_INGEST_TASK` | Cancel Bucket Ingest Task | Irreversibly cancel a non-terminal POMA Grill bucket-ingest task. Already terminal tasks cannot be cancelled. |
| `POMA_GRILL_CANCEL_INGEST_JOB` | Cancel Ingest Job | Request best-effort cancellation and removal of an ingestion job. A successful response does not guarantee that completed job metadata disappears. |
| `POMA_GRILL_DELETE_DOCUMENT` | Delete Document | Permanently delete one deliberately selected indexed document, including its vectors and stored assets. This action cannot be undone. |
| `POMA_GRILL_GET_BUCKET_INGEST_TASK` | Get Bucket Ingest Task | Get the current state, progress, processing rate, credential status, and recent failures for a POMA Grill bucket-ingest task. |
| `POMA_GRILL_GET_DOCUMENT` | Get Document | Get metadata for one indexed document by its document ID. |
| `POMA_GRILL_GET_INGEST_JOB` | Get Ingest Job | Get an ingestion job's current status and usage; poll this after Ingest Document until status is done, failed, or blocked. Grill jobs may pass through indexing before reaching a terminal state. |
| `POMA_GRILL_INGEST_DOCUMENT` | Ingest Document | Upload one file or provide one public remote URL for asynchronous indexing, and return the ingestion job ID to poll with Get Ingest Job. |
| `POMA_GRILL_LIST_BUCKET_INGEST_FAILURES` | List Bucket Ingest Failures | Return one page of failed items for a bucket ingest task, ordered by item ID, with an opaque cursor for the next page. |
| `POMA_GRILL_LIST_DOCUMENTS` | List Documents | List one page of document metadata from the connected project. |
| `POMA_GRILL_PAUSE_BUCKET_INGEST_TASK` | Pause Bucket Ingest Task | Pause a non-terminal bucket ingest task in paused_user state. Processing halts on the next scheduler tick while the task continues to occupy its account's active-task slot. |
| `POMA_GRILL_PREVIEW_BUCKET_INGEST` | Preview Bucket Ingest | Validate S3 or GCS credentials and preview matching source objects without creating a bucket-ingest task. Sensitive credentials are sent to POMA and exposed to the action execution environment. |
| `POMA_GRILL_RESUME_BUCKET_INGEST_TASK` | Resume Bucket Ingest Task | Resume a bucket ingest task paused by the user, restoring its pre-pause state and waking processing for the next scheduler tick. |
| `POMA_GRILL_RETRY_BUCKET_INGEST_FAILURES` | Retry Bucket Ingest Failures | Retry all or selected failed items in a bucket ingest task that is in done_with_errors or materialising. Refresh purged source credentials first. |
| `POMA_GRILL_SEARCH_DOCUMENTS` | Search Documents | Search indexed content across the project or within one document, returning either prompt-ready context or structured matching chunks. |
| `POMA_GRILL_SUBMIT_BUCKET_INGEST` | Submit Bucket Ingest | Create an asynchronous task to ingest matching objects from an S3 or GCS bucket into POMA Grill, optionally delivering results to another bucket. Source and destination credentials are sensitive inputs sent to POMA and exposed to the action execution environment. |
| `POMA_GRILL_UPDATE_BUCKET_INGEST_CREDENTIALS` | Update Bucket Ingest Credentials | Replace and validate the source credentials for an active bucket ingest task. A task paused for a source credential error resumes materialising on success. |
| `POMA_GRILL_UPDATE_DOCUMENT_ATTRIBUTES` | Update Document Attributes | Set, change, or remove selected typed attributes on one indexed document. Null attribute values remove those attributes; omitted names are unchanged. |

## 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 POMA Grill Tools via Tool Router with Your Agent

Get tools from Tool Router session and execute POMA Grill actions with your Agent
```python
tools = session.tools
response = openai.responses.create(
  model='gpt-4.1',
  tools=tools,
  input=[{
    'role': 'user',
    'content': 'YOUR_SPECIFIC_PROMPT_HERE'
  }]
)
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: 'YOUR_SPECIFIC_PROMPT_HERE'
  }],
});
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 POMA Grill
```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 POMA Grill tools.',
    max_turns=10
)

async def main():
    async with ClaudeSDKClient(options=options) as client:
        await client.query('YOUR_SPECIFIC_PROMPT_HERE')
        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: 'YOUR_SPECIFIC_PROMPT_HERE'
  }],
  maxSteps: 5,
});

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

## Why Use Composio?

### 1. AI Native POMA Grill Integration

- Supports both POMA Grill MCP and direct API based integrations
- Structured, LLM-friendly schemas for reliable tool execution
- Rich coverage for reading, writing, and querying your POMA Grill data

### 2. Managed Auth

- Built-in OAuth handling with automatic token refresh and rotation
- Central place to manage, scope, and revoke POMA Grill 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 POMA Grill
- Scoped, least privilege access to POMA Grill resources
- Full audit trail of agent actions to support review and compliance

## Use POMA Grill with any AI Agent Framework

Choose a framework you want to connect POMA Grill with:

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

## Related Toolkits

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- [Google Docs](https://composio.dev/toolkits/googledocs) - Google Docs is a cloud-based word processor that enables document creation and real-time collaboration. Its seamless sharing and version history make team editing and content management a breeze.
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- [ActiveMerge](https://composio.dev/toolkits/active_merge) - ActiveMerge is a document automation platform for generating documents, images, merged files, and e-signature workflows. It helps teams turn templates and stored files into finished, shareable documents faster.
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## Frequently Asked Questions

### Do I need my own developer credentials to use POMA Grill with Composio?

Yes, POMA Grill 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)