Arcanna MCP Server
Description
# Arcanna MCP Server The Arcanna MCP server allows user to interact with Arcanna's AI use cases 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…
About
# Arcanna MCP Server The Arcanna MCP server allows user to interact with Arcanna's AI use cases 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`…
Details
- Author
- siscale
- Downloads
- 237
- Categories
- Cloud Service, AI, Automation, API, Other
Jump to
- Resource Management: Create, update, and retrieve Arcanna resources (jobs, integrations)
- Python Coding: Generate, execute, and save code as an Arcanna integration
- Query Arcanna events: Retrieve events processed by Arcanna with multiple filters
- Job Management: Create, retrieve, start, stop, and train jobs
- Feedback System: Provide feedback on decisions to improve model accuracy
- Health Monitoring: Check server and API key status
Configure the server by adding the arcanna-mcp-server entry to the mcpServers section in your MCP client config file (e.g., claude_desktop_config.json for Claude Desktop). You can run it via Docker (image: arcanna/arcanna-mcp-server) or install the PyPI package (arcanna-mcp-server). Set the environment variables ARCANNA_MANAGEMENT_API_KEY and ARCANNA_HOST with your Arcana credentials.
Arcanna MCP Server
The Arcanna MCP server allows user to interact with Arcanna's AI use cases through the Model Context Protocol (MCP).
Usage with Claude Desktop or other MCP Clients
Configuration
Add the following entry to themcpServers section in your MCP client config file (claude_desktop_config.json for Claude
Desktop).
Use docker image (https://hub.docker.com/r/arcanna/arcanna-mcp-server) or PyPi package (https://pypi.org/project/arcanna-mcp-server/)
Building local image from this repository
Prerequisites
- Docker - https://docs.docker.com/engine/install/Configuration
1. Change directory to the directory where the Dockerfile is. 2. Run ``docker build -t arcanna/arcanna-mcp-server . --progress=plain --no-cache3. Add the configuration bellow to your claude desktop/mcp client config.
json
{
"mcpServers": {
"arcanna-mcp-server": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"ARCANNA_MANAGEMENT_API_KEY",
"-e",
"ARCANNA_HOST",
"arcanna/arcanna-mcp-server"
],
"env": {
"ARCANNA_MANAGEMENT_API_KEY": "<ARCANNA_MANAGEMENT_API_KEY>",
"ARCANNA_HOST": "<YOUR_ARCANNA_HOST_HERE>"
}
}
}
}
``
Features
- Resource Management: Create, update and retrieve Arcanna resources (jobs, integrations) - Python Coding: Code generation, execution and saving the code block as an Arcanna integration - Query Arcanna events: Query events processed by Arcanna - Job Management: Create, retrieve, start, stop, and train jobs - Feedback System: Provide feedback on decisions to improve model accuracy - Health Monitoring: Check server and API key statusTools
Query Arcanna events
- query_arcanna_events - Used to get events processed by Arcanna, multiple filters can be provided- get_filter_fields
- used as a helper tool (retrieve Arcanna possible fields to apply filters on)
Resource Management
- upsert_resources - Create/update Arcanna resources- get_resources
- Retrieve Arcanna resources (jobs/integrations)
- delete_resources
- Delete Arcanna resources
- integration_parameters_schema
- used in this context as a helper tool
Python Coding
- generate_code_agent - Used to generate code- execute_code
- Used to execute the generated code
- save_code
- Use to save the code block in Arcanna pipeline as an integration
Job Management
- start_job - Begin event ingestion for a job- stop_job
- Stop event ingestion for a job
- train_job
- Train the job's AI model using the provided feedback
Feedback System
- add_feedback_to_event - Provide feedback on AI decisions for model improvementSystem Health
- health_check - Verify server status and Management API key validity - Returns Management API key authorization statusSign in to leave a review
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