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Arcanna Input MCP Server

@siscale

Arcanna Input MCP Server について

概要はまだありません

基本情報

カテゴリ

その他

ライセンス

Apache-2.0 license

ランタイム

python

トランスポート

stdio

公開者

siscale

設定

標準の設定はありません

このサーバーの README には解析可能な MCP 設定ブロックが含まれていません。インストール手順はリポジトリをご確認ください。

リポジトリ

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Arcanna Input MCP Server?

Arcanna Input MCP Server enables users to interact with Arcanna's AI use cases that use external API integration through the Model Context Protocol (MCP). It is designed for developers using MCP clients like Claude Desktop.

How to use Arcanna Input MCP Server?

Configure the server in your MCP client configuration file (e.g., claude_desktop_config.json) using a Docker image or PyPI package. Set the environment variables ARCANNA_INPUT_API_KEY, ARCANNA_HOST, and ARCANNA_USER. Then invoke the MCP client as usual to access the exposed tools.

Key features of Arcanna Input MCP Server

  • Job Management: Create, retrieve, start, stop, and train jobs
  • Event Processing: Send events for AI-powered decision making
  • Feedback System: Provide feedback on decisions to improve model accuracy
  • Health Monitoring: Check server and API key status

Use cases of Arcanna Input MCP Server

  • Automate AI job lifecycle management from an MCP client
  • Submit events to Arcanna for real-time decision making
  • Retrieve and monitor job status and processing metrics
  • Provide feedback to fine-tune AI models

FAQ from Arcanna Input MCP Server

What are the prerequisites to run Arcanna Input MCP Server?

Docker is required if using the Docker image. Alternatively, you can install the server via PyPI.

How do I configure the server for use with Claude Desktop?

Add the entry shown in the README to the mcpServers section of your claude_desktop_config.json, providing your Arcanna API key, host, and username as environment variables.

What tools does Arcanna Input MCP Server provide?

It provides tools for job management (get all jobs, get job by ID, get job by name, get job labels), event management (send event, send event with custom ID), and health checking.

What runtime dependencies does the server have?

The server requires an MCP client to connect, and depending on the install method, a Docker runtime or Python environment. No additional runtime beyond the API key and host are specified.

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