# PromptHub

```json
{
  "name": "PromptHub",
  "slug": "prompt_hub",
  "url": "https://composio.dev/toolkits/prompt_hub",
  "markdown_url": "https://composio.dev/toolkits/prompt_hub.md",
  "logo_url": "https://logos.composio.dev/api/prompthub",
  "categories": [
    "ai & machine learning"
  ],
  "is_composio_managed": false,
  "updated_at": "2026-10-04T15:14:45.158Z"
}
```

![PromptHub logo](https://logos.composio.dev/api/prompthub)

## Description

Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with PromptHub MCP or direct API to retrieve prompts, run versioned prompts, compare revisions, and manage prompt metadata through natural language.

## Summary

PromptHub is a prompt management platform for versioning, retrieving, and executing prompts through an API.
It helps teams ship reliable AI features with traceable prompt changes and reusable prompt assets.

## Categories

- ai & machine learning

## Toolkit Details

- Tools: 4

## Images

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

## Authentication

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

## Suggested Prompts

- Retrieve latest PromptHub production prompt
- Run PromptHub support prompt with variables
- Compare PromptHub revisions before deployment

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `PROMPT_HUB_GET_CURRENT_TEAM` | Get Current Team | Return the current PromptHub team ID for the connected account. Use it when a team-scoped operation must target an explicit team. |
| `PROMPT_HUB_GET_PROJECT_HEAD` | Get Project Head | Retrieve a project's latest committed prompt and model configuration, with optional branch and variable resolution. |
| `PROMPT_HUB_LIST_PROJECTS` | List Projects | List projects in a PromptHub team, optionally filtered by group, model, or provider. |
| `PROMPT_HUB_RUN_PROJECT` | Run Project | Execute a committed PromptHub project prompt with optional variables and return the generated text, usage, cost, and timing metadata. This invokes the configured LLM, consumes the PromptHub plan's LLM request quota, and creates persistent run history in the project's Logs tab. |

## Supported Triggers

None listed.

## Installation and MCP Setup

### Path 1: SDK Installation

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

Install the Composio SDK, the OpenAI provider, and the OpenAI SDK
```python
pip install composio composio_openai openai
```

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

#### Path 1, Step 2: Create a Composio session

Initialize Composio with the OpenAI Responses provider and create a session scoped to PromptHub
```python
import json
from openai import OpenAI
from composio import Composio
from composio_openai import OpenAIResponsesProvider

composio = Composio(provider=OpenAIResponsesProvider())
client = OpenAI()

session = composio.create(user_id="your-user-id", toolkits=["prompt_hub"])
tools = session.tools()
```

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

const composio = new Composio({ provider: new OpenAIResponsesProvider() });
const client = new OpenAI();

const session = await composio.create("your-user-id", { toolkits: ["prompt_hub"] });
const tools = await session.tools();
```

#### Path 1, Step 3: Run PromptHub tools with your agent

Send a request, execute the PromptHub tool calls through the session, and print the final answer
```python
response = client.responses.create(
    model="gpt-5.6-sol",
    tools=tools,
    input=[{"role": "user", "content": "Retrieve the latest production version of my PromptHub prompt named customer-support-agent and show its variables"}],
)

while True:
    tool_calls = [o for o in response.output if o.type == "function_call"]
    if not tool_calls:
        break
    results = composio.provider.handle_tool_calls(response=response, session=session)
    response = client.responses.create(
        model="gpt-5.6-sol",
        tools=tools,
        previous_response_id=response.id,
        input=[
            {"type": "function_call_output", "call_id": call.call_id, "output": json.dumps(results[i])}
            for i, call in enumerate(tool_calls)
        ],
    )

print(response.output_text)
```

```typescript
let response = await client.responses.create({
  model: "gpt-5.6-sol",
  tools,
  input: [{ role: "user", content: "Retrieve the latest production version of my PromptHub prompt named customer-support-agent and show its variables" }],
});

while (response.output.some((o) => o.type === "function_call")) {
  const outputs = await composio.provider.handleToolCalls(session, response.output);
  response = await client.responses.create({
    model: "gpt-5.6-sol",
    tools,
    previous_response_id: response.id,
    input: outputs,
  });
}

console.log(response.output_text);
```

### Path 2: MCP Server Setup

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

Install the Composio SDK and your agent framework
```python
pip install composio claude-agent-sdk
```

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

#### Path 2, Step 2: Create a session with MCP enabled

Create a session scoped to PromptHub and read its MCP URL and headers
```python
from composio import Composio

composio = Composio()
session = composio.create(user_id="your-user-id", toolkits=["prompt_hub"], mcp=True)
```

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

const composio = new Composio();
const { mcp } = await composio.create("your-user-id", {
  toolkits: ["prompt_hub"],
  mcp: true,
});
```

#### Path 2, Step 3: Connect your agent to the MCP server

Pass the session's MCP URL and headers to your agent and run a PromptHub request
```python
import asyncio
from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions, AssistantMessage, TextBlock

options = ClaudeAgentOptions(
    mcp_servers={
        "composio": {
            "type": "http",
            "url": session.mcp.url,
            "headers": session.mcp.headers,
        }
    },
    system_prompt="You are a helpful assistant with access to PromptHub tools.",
    tools=[],
    allowed_tools=["mcp__composio__*"],
)

async def main():
    async with ClaudeSDKClient(options=options) as client:
        await client.query("Retrieve the latest production version of my PromptHub prompt named customer-support-agent and show its variables")
        async for message in client.receive_response():
            if isinstance(message, AssistantMessage):
                for block in message.content:
                    if isinstance(block, TextBlock):
                        print(block.text)

asyncio.run(main())
```

```typescript
import { createMCPClient } from "@ai-sdk/mcp";
import { openai } from "@ai-sdk/openai";
import { generateText, stepCountIs } from "ai";

const client = await createMCPClient({
  transport: { type: "http", url: mcp.url, headers: mcp.headers },
});

const { text } = await generateText({
  model: openai("gpt-5.6-sol"),
  tools: await client.tools(),
  prompt: "Retrieve the latest production version of my PromptHub prompt named customer-support-agent and show its variables",
  stopWhen: stepCountIs(10),
});

console.log(text);
await client.close();
```

## Why Use Composio?

### 1. AI Native PromptHub Integration

- Supports both PromptHub MCP and direct API based integrations
- Structured, LLM-friendly schemas for reliable prompt retrieval and execution
- Rich coverage for reading, running, and querying your PromptHub prompt library

### 2. Managed Auth

- Bring your PromptHub API key and connect it with auth_configs.create()
- Link user access with connected_accounts.link() instead of hard-coding keys in agent code
- Composio handles secure credential storage and API request handling for PromptHub

### 3. Agent Optimized Design

- Tools are shaped so agents can understand PromptHub prompts, versions, and execution inputs clearly
- Execution logs show which prompt was fetched or run, when it happened, and on whose behalf
- Create MCP sessions with mcp.create() so Claude, Cursor, and other MCP clients can use PromptHub naturally

### 4. Enterprise Grade Security

- Fine-grained RBAC so you control which agents and users can access PromptHub
- Scoped, least privilege access to PromptHub prompt resources
- Full audit trail of agent actions to support review, rollback, and compliance

## Use PromptHub with any AI Agent Framework

Choose a framework you want to connect PromptHub with:

None listed.

## Related Toolkits

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## Frequently Asked Questions

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

Yes, PromptHub requires you to configure your own API key credentials. Once set up, Composio handles secure credential storage and API request handling for you. You can create the auth config with auth_configs.create(), link users with connected_accounts.link(), and expose PromptHub over MCP with mcp.create().

### 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)