Arcanna MCP Server
by siscale
The Arcanna MCP server enables users to interact with Arcanna's AI use cases through the Model Context Protocol (MCP). It facilitates communication between MCP clients and Arcanna's AI functionalities.
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What is Arcanna MCP Server?
The Arcanna MCP Server acts as an intermediary, allowing users to leverage Arcanna's AI capabilities via the Model Context Protocol. It provides a set of tools and functionalities to manage resources, execute code, query events, manage jobs, provide feedback, and monitor system health within the Arcanna ecosystem.
How to use Arcanna MCP Server?
The server can be deployed using a Docker image or a PyPi package. Configuration involves adding the server entry to the mcpServers section in the MCP client config file (e.g., claude_desktop_config.json for Claude Desktop). The configuration specifies the command to run the server (e.g., docker run) and environment variables for API key and host.
Key features of Arcanna MCP Server
Resource Management
Python Coding (code generation, execution, saving)
Query Arcanna events
Job Management (create, retrieve, start, stop, train)
Feedback System
Health Monitoring
Use cases of Arcanna MCP Server
Integrating Arcanna's AI models with MCP-compatible clients.
Automating resource management within the Arcanna platform.
Generating and executing code within Arcanna's environment.
Monitoring and managing AI jobs within Arcanna.
Improving model accuracy through feedback integration.
FAQ from Arcanna MCP Server
What is the purpose of the Arcanna MCP Server?
What is the purpose of the Arcanna MCP Server?
It allows users to interact with Arcanna's AI use cases through the Model Context Protocol (MCP).
How do I configure the server?
How do I configure the server?
Add an entry to the mcpServers section in your MCP client config file, specifying the command and environment variables.
What are some key features of the server?
What are some key features of the server?
Resource Management, Python Coding, Query Arcanna events, Job Management, Feedback System, and Health Monitoring.
How can I deploy the server?
How can I deploy the server?
You can use either the Docker image or the PyPi package.
What is the health_check tool used for?
What is the health_check tool used for?
It verifies the server status and the validity of the Management API key.