Authentication

from upsonic import Task, Agent

# MCP server with authentication
class AuthenticatedMCP:
    command = "npx"
    args = ["-y", "@company/private-mcp-server"]
    env = {
        "API_KEY": "your_api_key_here",
        "API_SECRET": "your_api_secret_here",
        "AUTH_TOKEN": "bearer_token_here"
    }

# Multiple servers with different auth
class GitHubMCP:
    command = "npx"
    args = ["-y", "@modelcontextprotocol/server-github"]
    env = {
        "GITHUB_PERSONAL_ACCESS_TOKEN": "ghp_xxxxx"
    }

class SlackMCP:
    command = "uvx"
    args = ["mcp-server-slack"]
    env = {
        "SLACK_BOT_TOKEN": "xoxb-xxxxx",
        "SLACK_TEAM_ID": "T1234567"
    }

# Create task with authenticated tools
task = Task(
    description="Fetch the latest open issues from the repository 'my-project/repo' using the GitHub tool, then send a summary of these issues to the '#dev-team' channel on Slack.",
    tools=[GitHubMCP, SlackMCP]
)

# Create agent
agent = Agent(
    name="Integration Agent",
    model="openai/gpt-4o"
)

# Execute
result = agent.do(task)
print(result)

import os
from upsonic import Task, Agent

# Load from environment
class SecureMCP:
    command = "npx"
    args = ["-y", "@company/mcp-server"]
    env = {
        "API_KEY": os.getenv("MCP_API_KEY"),
        "API_SECRET": os.getenv("MCP_API_SECRET")
    }

task = Task(
    description="Connect to the secure company MCP server and retrieve the latest confidential report.",
    tools=[SecureMCP]
)

agent = Agent(name="Secure Agent", model="openai/gpt-4o")
result = agent.do(task)
print(result)

from upsonic import Task, Agent

# SSE server with authentication headers
class AuthenticatedSSE:
    url = "https://mcp-server.com/sse"
    # Note: Authentication for SSE typically handled server-side
    # Pass credentials via URL parameters or configure server-side

task = Task(
    description="Connect to the real-time SSE MCP server and listen for the latest status updates.",
    tools=[AuthenticatedSSE]
)

agent = Agent(name="SSE Agent", model="openai/gpt-4o")
result = agent.do(task)
print(result)