klavis 0.1.2

Klavis AI (https://www.klavis.ai)

Klavis AI Python SDK

Klavis AI - Open Source MCP Integrations for AI Applications. This Python package provides a convenient way to interact with the Klavis AI API (https://www.klavis.ai).

Installation

You can install the Klavis AI Python SDK using pip:

pip install klavis

Getting Started

To use the SDK, you need to obtain an API key from Klavis AI.

Here's a basic example of how to configure the client and make an API call:

import os
from pprint import pprint

from klavis import ApiClient, Configuration
from klavis.api import McpServerApi
from klavis.models import CreateServerRequest, ServerName, CallToolRequest

# Replace 'YOUR_API_KEY' with your actual Klavis API key
# You can also set the KLAVIS_API_KEY environment variable
api_key = os.environ.get("KLAVIS_API_KEY", "YOUR_API_KEY") 
if api_key == "YOUR_API_KEY":
    print("Warning: API Key not configured. Please set the KLAVIS_API_KEY environment variable or replace 'YOUR_API_KEY'.")
    # exit(1) # Consider exiting if the key is required for all operations

config = Configuration(
    host="https://api.klavis.ai", # Default production server
    api_key=api_key,
)

# Create an API client instance
api_client = ApiClient(config)

# Example: Using the MCP Server API
mcp_api = McpServerApi(api_client)

try:
    # 1. Create a server instance for a specific MCP (e.g., GitHub)
    print("\n--- Creating a server instance ---")
    create_request = CreateServerRequest(
        server_name=ServerName.GITHUB, 
        user_id="example_user_id",        # Replace with a relevant user identifier
        platform_name="example_platform"  # Replace with your platform name
    )
    instance = mcp_api.create_server_instance(create_request)
    instance_id = instance.instance_id
    server_url = instance.server_url
    print("Instance created:")
    pprint(instance.to_dict())

    # (Optional) Check instance details
    print("\n--- Getting instance details ---")
    instance_details = mcp_api.get_server_instance(instance_id)
    print("Instance details:")
    pprint(instance_details.to_dict())
    
    # (Optional) If the server requires authentication (e.g., PAT for GitHub), 
    # you might need to set it after the OAuth flow or manually.
    # See OAuth endpoints and set_instance_auth_token. 
    # For GitHub, you'd typically complete the OAuth flow first.
    # The server_url obtained above includes the instance_id and handles routing.

    # 2. Call a tool on the created instance
    # Ensure the instance is properly authenticated if required by the tool.
    print("\n--- Calling a tool (GitHub Search Repositories) ---")
    call_request = CallToolRequest(
        server_url=server_url,                # Use the URL from the create step
        tool_name="github_search_repositories", # Tool name for the specific MCP
        tool_args={"query": "klavis ai"}      # Arguments required by the tool
    )
    tool_result = mcp_api.call_server_tool(call_request)
    print("Tool call result:")
    pprint(tool_result.to_dict())

    # 3. Clean up: Delete the instance when done
    print("\n--- Deleting instance ---")
    delete_result = mcp_api.delete_server_instance(instance_id)
    print("Deletion result:")
    pprint(delete_result.to_dict())

except Exception as e:
    print(f"An API error occurred: {e}")

Available APIs

This SDK provides access to the following Klavis AI API functionalities:

• MCP Server API (klavis.api.McpServerApi): Manage MCP server instances, list and call tools on connected MCPs (like Slack, GitHub, Jira, etc.).
• OAuth APIs (e.g., klavis.api.SlackOauthApi, klavis.api.GithubOauthApi, etc.): Handle OAuth flows for different services to authenticate MCP instances.
• White Labeling API (klavis.api.WhiteLabelingApi): Manage OAuth white labeling configurations.

Please refer to the docs and directories or the official Klavis AI API documentation for details on all available methods and models.

Authentication

Authentication is handled via an API key passed as a Bearer token in the Authorization header. The Configuration object manages this automatically when you provide your api_key.

from klavis import Configuration

config = Configuration(
    api_key="YOUR_API_KEY", 
)

Documentation

For more detailed information on the API endpoints and models, please refer to the Klavis AI API Documentation.

Contributing

Contributions are welcome! Please refer to the main repository's contribution guidelines.

License

This SDK is distributed under the terms of the LICENSE file.