# CrewAI (/docs/providers/crewai)

The CrewAI provider transforms Devcaster tools into CrewAI's [BaseTool](https://docs.crewai.com/concepts/tools) format with built-in execution.

**Install**

```bash
pip install devcaster devcaster_crewai crewai
```

**Configure API Keys**

> Set `DEVCASTER_API_KEY` with your API key from [Settings](https://platform.devcaster.dev/?next_page=/settings) and `OPENAI_API_KEY` with your [OpenAI API key](https://platform.openai.com/api-keys).

```txt title=".env"
DEVCASTER_API_KEY=xxxxxxxxx
OPENAI_API_KEY=xxxxxxxxx
```
**Create session and run**

```python
from crewai import Agent, Crew, Task
from devcaster import Devcaster
from devcaster_crewai import CrewAIProvider

devcaster = Devcaster(provider=CrewAIProvider())

# Create a session for your user
session = devcaster.create(user_id="user_123")
tools = session.tools()

agent = Agent(
    role="Email Agent",
    goal="Send emails on behalf of the user",
    backstory="You are an AI agent that sends emails using Gmail.",
    tools=tools,
    llm="gpt-5.2",
)

task = Task(
    description="Send an email to john@example.com with the subject 'Hello' and body 'Hello from Devcaster!'",
    agent=agent,
    expected_output="Confirmation that the email was sent",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)
```

---

📚 **More documentation:** [View all docs](https://docs.devcaster.dev/llms.txt) | [Cookbooks](https://docs.devcaster.dev/llms.mdx/cookbooks) | [API Reference](https://docs.devcaster.dev/llms.mdx/reference)

---

# Devcaster SDK — Instructions for AI Code Generators

**Purpose:** Enforce only the **current** and **correct** patterns for integrating [Devcaster](https://devcaster.dev/) tools into AI agents.
**Scope:** All AI-generated code using Devcaster must follow these guardrails.

---

## 1. Correct Devcaster Integration

Devcaster supports two integration modes: **Native Tools** (with a provider package) and **MCP** (no provider package needed).

### Native Tools

```python
# ✅ CORRECT — Python (defaults to OpenAI)
from devcaster import Devcaster

devcaster = Devcaster()
session = devcaster.create(user_id="user_123")
tools = session.tools()
# Pass tools to your agent/LLM framework
```

```typescript
// ✅ CORRECT — TypeScript (defaults to OpenAI)
import { Devcaster } from "@devcaster/core";

const devcaster = new Devcaster();
const session = await devcaster.create("user_123");
const tools = await session.tools();
// Pass tools to your agent/LLM framework
```

For other providers, pass the provider explicitly. Provider packages follow the naming convention: `devcaster_<provider>` for Python, `@devcaster/<provider>` for TypeScript.

### MCP

Use `session.mcp.url` and `session.mcp.headers` with any MCP-compatible client (Claude Desktop, Cursor, OpenAI Agents, etc.). No provider package needed.

---

## 2. CRITICAL INSTRUCTIONS FOR AI MODELS

### 2.1 — ALWAYS DO THE FOLLOWING

1. **Use `devcaster.create(user_id)`** to create a session — this is the entry point for all Devcaster integrations.
2. **Use `session.tools()`** for native tool integration or **`session.mcp.url`** for MCP integration.
3. **Import** from the correct provider package (`devcaster_<provider>` for Python, `@devcaster/<provider>` for TypeScript).
4. **Pass `user_id` to `devcaster.create()`**, not to individual tool calls.

### 2.2 — NEVER DO THE FOLLOWING

1. **Do not** instruct users to manually create auth configs or connected accounts before running.
2. **Do not** import from `devcaster_openai` / `@devcaster/openai` when using OpenAI Agents SDK — use `devcaster_openai_agents` / `@devcaster/openai-agents` instead.

### 2.3 — DISCOURAGED (do not use unless user explicitly asks)

Do **not** generate `devcaster.tools.get()`, `devcaster.tools.execute()`, or `devcaster.provider.handle_tool_calls()` unless the user explicitly requests direct tool execution. These are a supported but **not recommended** low-level interface.

