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Arcanna Input MCP Server

Arcanna Input MCP Server

Local
github.com/siscaleAI & Agents0Updated 81w ago

About Arcanna Input MCP Server

Arcanna Input MCP Server connects MCP clients to Arcanna AI use cases that integrate external APIs. It provides tools for job operations, event submission, feedback, and service health checks.

Key features

  1. 01Create, retrieve, start, stop, and train jobs
  2. 02Submit events for AI decisions
  3. 03Send events with custom identifiers
  4. 04Provide decision feedback
  5. 05Check server and API key status

Use cases

  1. 01Manage Arcanna external-input jobs
  2. 02Submit events for AI-powered decisions
  3. 03Send feedback on decisions
  4. 04Verify server health and API-key validity

MCP support

The server exposes Arcanna job, event, feedback, and health operations as tools for MCP clients.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Arcanna Input MCP Server

The Arcanna Input MCP server allows user to interact with Arcanna's AI use cases that use external api integration through the Model Context Protocol (MCP).

Usage with Claude Desktop or other MCP Clients

Configuration

Add the following entry to the mcpServers section in your MCP client config file (claude_desktop_config.json for Claude Desktop).

Use docker image (https://hub.docker.com/r/arcanna/arcanna-input-mcp-server) or PyPi package (https://pypi.org/project/arcanna-mcp-input-server)
Building local image from this repository
Prerequisites
Configuration
  1. Change directory to the directory where the Dockerfile is.
  2. Run docker build -t arcanna/arcanna-input-mcp-server . --progress=plain --no-cache
  3. Add the configuration bellow to your claude desktop/mcp client config.
{
  "mcpServers": {
    "arcanna-input-mcp-server": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "ARCANNA_INPUT_API_KEY",
        "-e",
        "ARCANNA_HOST",
        "-e",
        "ARCANNA_USER",
        "arcanna/arcanna-input-mcp-server"
      ],
      "env": {
        "ARCANNA_INPUT_API_KEY": "<YOUR_ARCANNA_API_KEY_HERE>",
        "ARCANNA_HOST": "<YOUR_ARCANNA_HOST_HERE>",
        "ARCANNA_USER": "<YOUR_USERNAME_HERE>"
      }
    }
  }
}

Features

  • 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

Tools

Job Management
  • get_external_input_jobs

    • Retrieve all jobs associated with your API key
    • Returns a list of job details including status, labels, and processing metrics
  • get_external_input_job_by_id

    • Retrieve specific job details by ID
  • get_external_input_job_by_name

    • Retrieve specific job details by name
  • get_external_input_job_labels

    • Retrieve decision labels for a specific job
Event Management
  • send_event_to_external_input_job

    • Submit an event to Arcanna for AI decision-making
  • send_event_with_id_to_external_input_job

    • Submit an event with a custom identifier
System Health
  • health_check_input_server
    • Verify server status and API key validity
    • Returns API key authorization status

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.