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5-Minute Quickstart

Get a FastAgentic agent running in under 5 minutes.

Prerequisites

  • Python 3.10+
  • uv (recommended) or pip
  • OpenAI API key (or Anthropic)

Step 1: Create Project (30 seconds)

# Create directory
mkdir my-agent && cd my-agent

# Initialize with uv
uv init
uv add "fastagentic[pydanticai]"

Step 2: Create Agent (1 minute)

Create app.py:

from fastagentic import App, agent_endpoint, tool
from fastagentic.adapters.pydanticai import PydanticAIAdapter
from pydantic import BaseModel
from pydantic_ai import Agent

# Create your agent
agent = Agent(
    model="openai:gpt-4o-mini",
    system_prompt="You are a helpful assistant.",
)

# Add a tool
@agent.tool
async def get_time() -> str:
    """Get current time."""
    from datetime import datetime
    return datetime.now().strftime("%H:%M:%S")

# Create FastAgentic app
app = App(title="My Agent", version="1.0.0")

# Define request/response
class ChatRequest(BaseModel):
    message: str

class ChatResponse(BaseModel):
    response: str

# Expose as endpoint
@agent_endpoint(
    path="/chat",
    runnable=PydanticAIAdapter(agent),
    input_model=ChatRequest,
    output_model=ChatResponse,
    stream=True,
)
async def chat(request: ChatRequest) -> ChatResponse:
    pass

Step 3: Set API Key (10 seconds)

export OPENAI_API_KEY="sk-your-key"

Step 4: Run (30 seconds)

uv run fastagentic run

Output: 

Starting FastAgentic server...
  App: app:app
  URL: http://127.0.0.1:8000

Step 5: Test (1 minute)

uv run fastagentic agent chat

FastAgentic Agent CLI
> What time is it?

The current time is 14:32:15.

> /quit

Option B: curl

curl -X POST http://localhost:8000/chat \
  -H "Content-Type: application/json" \
  -d '{"message": "What time is it?"}'

Option C: OpenAPI Docs

Open http://localhost:8000/docs in your browser.

What You Get

Interface URL
REST API POST /chat
OpenAPI Docs /docs
MCP Schema /mcp/schema
Health Check /health

Next Steps

Add more tools

@agent.tool
async def search(query: str) -> str:
    """Search for information."""
    return f"Results for: {query}"

Enable streaming

Already enabled! Use SSE client or Agent CLI.

Add authentication

app = App(
    title="My Agent",
    oidc_issuer="https://auth.example.com",
)

Enable persistence

# Start Redis
docker run -d -p 6379:6379 redis

# Update app.py
app = App(
    title="My Agent",
    durable_store="redis://localhost:6379",
)

Use with Claude Desktop (MCP)

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "my-agent": {
      "command": "fastagentic",
      "args": ["mcp", "serve", "app:app"],
      "cwd": "/path/to/my-agent"
    }
  }
}

Complete Example

"""Complete FastAgentic agent in one file."""

from datetime import datetime
from fastagentic import App, agent_endpoint, tool, resource
from fastagentic.adapters.pydanticai import PydanticAIAdapter
from pydantic import BaseModel
from pydantic_ai import Agent

# Agent with tools
agent = Agent(
    model="openai:gpt-4o-mini",
    system_prompt="You are a helpful assistant with access to tools.",
)

@agent.tool
async def get_time() -> str:
    """Get the current time."""
    return datetime.now().strftime("%Y-%m-%d %H:%M:%S")

@agent.tool
async def calculate(expression: str) -> str:
    """Calculate a math expression."""
    try:
        return str(eval(expression))
    except:
        return "Error"

# FastAgentic app
app = App(title="Quick Agent", version="1.0.0")

class ChatRequest(BaseModel):
    message: str

class ChatResponse(BaseModel):
    response: str

@agent_endpoint(
    path="/chat",
    runnable=PydanticAIAdapter(agent),
    input_model=ChatRequest,
    output_model=ChatResponse,
    stream=True,
    mcp_tool="chat",
)
async def chat(request: ChatRequest) -> ChatResponse:
    pass

@resource(name="info", uri="info")
async def info() -> dict:
    return {"name": "Quick Agent", "version": "1.0.0"}

# Run: uv run fastagentic run

Troubleshooting

"Module not found"

uv sync  # Reinstall dependencies

"API key not set"

export OPENAI_API_KEY="sk-..."
# Or for Anthropic:
export ANTHROPIC_API_KEY="sk-ant-..."

Port already in use

uv run fastagentic run --port 8001

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