# PromptLayer

```json
{
  "name": "PromptLayer",
  "slug": "promptlayer",
  "url": "https://composio.dev/toolkits/promptlayer",
  "markdown_url": "https://composio.dev/toolkits/promptlayer.md",
  "logo_url": "https://logos.composio.dev/api/promptlayer",
  "categories": [
    "ai & machine learning"
  ],
  "is_composio_managed": false,
  "updated_at": "2026-10-04T15:06:20.335Z"
}
```

![PromptLayer logo](https://logos.composio.dev/api/promptlayer)

## Description

Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with PromptLayer MCP or direct API to version prompts, run evaluations, inspect request logs, and analyze LLM performance through natural language.

## Summary

PromptLayer is a prompt management and observability platform for LLM apps.
Use it to version prompts, run evaluations, trace requests, and analyze model behavior.

## Categories

- ai & machine learning

## Toolkit Details

- Tools: 16

## Images

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

## Authentication

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

## Suggested Prompts

- List failed PromptLayer requests today
- Compare prompt versions by evaluation score
- Run saved PromptLayer prompt with variables

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `PROMPTLAYER_GET_PROMPT_TEMPLATE` | Get Prompt Template | Retrieve a prompt template version, release label, messages, model metadata, snippets, and optionally provider-ready kwargs without executing it. |
| `PROMPTLAYER_GET_REGISTERED_TOOL` | Get Registered Tool | Retrieve a PromptLayer registered tool definition by ID or name at a selected version or release label without test execution. |
| `PROMPTLAYER_GET_REQUEST_LOG` | Get Request Log | Retrieve one PromptLayer request log with its recorded input, output, timing, usage, metadata, tags, and scores. |
| `PROMPTLAYER_GET_SKILL_COLLECTION` | Get Skill Collection | Retrieve a PromptLayer skill collection and its files as JSON at a selected version or release label. |
| `PROMPTLAYER_GET_TABLE` | Get Table | Retrieve one PromptLayer Table's metadata and per-sheet row counts by UUID. |
| `PROMPTLAYER_GET_WORKFLOW` | Get Workflow | Retrieve a PromptLayer workflow definition by ID or name at a specific version or release label without running it. |
| `PROMPTLAYER_LIST_FOLDER_ENTITIES` | List Folder Entities | Browse or search PromptLayer folders and registry entities in the API-key workspace, optionally recursively and with metadata. |
| `PROMPTLAYER_LIST_PROMPT_TEMPLATES` | List Prompt Templates | Search and page through PromptLayer prompt templates and snippets without executing a model. |
| `PROMPTLAYER_LIST_REGISTERED_TOOLS` | List Registered Tools | List and filter tools defined in PromptLayer's tool registry without executing them. |
| `PROMPTLAYER_LIST_SKILL_COLLECTIONS` | List Skill Collections | List and filter PromptLayer skill collections available in the API-key workspace. |
| `PROMPTLAYER_LIST_TABLE_COLUMNS` | List Table Columns | List one page of user and optionally system columns for a PromptLayer Table sheet. |
| `PROMPTLAYER_LIST_TABLE_ROWS` | List Table Rows | Read one page of rows and cells from a PromptLayer Table sheet, with optional schema and execution aggregates. |
| `PROMPTLAYER_LIST_TABLES` | List Tables | Search and page through PromptLayer Tables by folder, name, or referenced prompt. |
| `PROMPTLAYER_LIST_TABLE_SHEETS` | List Table Sheets | List one page of sheets in a PromptLayer Table, optionally filtering by referenced prompt. |
| `PROMPTLAYER_LIST_WORKFLOWS` | List Workflows | Search and page through PromptLayer workflows without running them. |
| `PROMPTLAYER_SEARCH_REQUEST_LOGS` | Search Request Logs | Search PromptLayer request logs by text or structured filters and return one rate-limited page sorted by operational fields. |

## 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 PromptLayer
```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=["promptlayer"])
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: ["promptlayer"] });
const tools = await session.tools();
```

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

Send a request, execute the PromptLayer 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": "List failed PromptLayer requests from the last 24 hours and summarize the main error patterns"}],
)

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: "List failed PromptLayer requests from the last 24 hours and summarize the main error patterns" }],
});

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 PromptLayer and read its MCP URL and headers
```python
from composio import Composio

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

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

const composio = new Composio();
const { mcp } = await composio.create("your-user-id", {
  toolkits: ["promptlayer"],
  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 PromptLayer 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 PromptLayer tools.",
    tools=[],
    allowed_tools=["mcp__composio__*"],
)

async def main():
    async with ClaudeSDKClient(options=options) as client:
        await client.query("List failed PromptLayer requests from the last 24 hours and summarize the main error patterns")
        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: "List failed PromptLayer requests from the last 24 hours and summarize the main error patterns",
  stopWhen: stepCountIs(10),
});

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

## Why Use Composio?

### 1. AI Native PromptLayer Integration

- Supports both PromptLayer MCP and direct API based integrations
- Structured, LLM-friendly schemas for reliable prompt, log, and evaluation workflows
- Rich coverage for reading, writing, and querying your PromptLayer data without bespoke integration code

### 2. Managed Auth

- PromptLayer uses API key auth, and Composio keeps those keys out of your agent code
- Create auth configs with auth_configs.create() and link user accounts with connected_accounts.link()
- Use per user and per environment credentials instead of hard-coded PromptLayer keys

### 3. Agent Optimized Design

- Tools are tuned for LLMs, so agents can safely inspect PromptLayer runs, evaluations, and prompt versions
- Comprehensive execution logs help you see what ran, when, and on whose behalf
- Use mcp.create() or Tool Router sessions to connect PromptLayer to Claude, ChatGPT, Cursor, and other agents

### 4. Enterprise Grade Security

- Fine-grained RBAC helps you control which agents and users can access PromptLayer
- Scoped, least privilege access keeps PromptLayer prompt and observability data protected
- Full audit trails make agent activity easier to review, debug, and govern

## Use PromptLayer with any AI Agent Framework

Choose a framework you want to connect PromptLayer with:

None listed.

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## Frequently Asked Questions

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

Yes, PromptLayer 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)