Arcanna MCP Server

Interagieren Sie mit den KI-Anwendungsfällen von Arcanna über das Model Context Protocol (MCP).

Dokumentation

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 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

Change directory to the directory where the Dockerfile is.
Run docker build -t arcanna/arcanna-mcp-server . --progress=plain --no-cache
Add the configuration bellow to your claude desktop/mcp client config.

{
  "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>"
      }
    }
  }
}

Servers

One package, three MCP servers. Install once; each executable is a separate server, so a client attaches only what it needs. All three use the same environment (ARCANNA_HOST, ARCANNA_MANAGEMENT_API_KEY, optional ARCANNA_AGENTS_HOST, TRANSPORT_MODE=stdio|sse, PORT for sse). Tools are filtered by the API key's scopes.

Executable	MCP name	Covers
`arcanna-mcp-server`	`arcanna`	Jobs, integrations, events, feedback, buckets, metrics, IaC, roles, platform, code blocks
`arcanna-agents-mcp`	`arcanna-agents`	Agentic workflows: create, update, run, human-in-the-loop sessions
`arcanna-rag-mcp`	`arcanna-rag`	RAG documents, collections and tags

Docker: the image's entrypoint is arcanna-mcp-server; run another server with e.g. docker run -i --rm --entrypoint arcanna-agents-mcp -e ARCANNA_HOST -e ARCANNA_MANAGEMENT_API_KEY arcanna/arcanna-mcp-server.

Tools

arcanna-mcp-server

jobs: start_job, stop_job, train_job, get_job_status, get_job_input_state, reset_job_input_state, submit_training_config_validation, get_training_config_validation, list_training_config_validations, cancel_training_config_validation
resources: search_integrations, get_integration_details, search_jobs, get_job_details, list_integration_types, get_integration_type_metadata, get_job_category_metadata, create_integration, update_integration, delete_integration, create_job, update_job, delete_job, check_integration_health, list_llm_models, get_job_decision_points, apply_iac, export_iac, get_roles, upsert_roles, delete_roles
events: query_arcanna_events, count_events, get_field_stats, get_field_groups, get_filter_fields, get_fields_mapping, get_event_explanation, get_similar_events, get_event_agentic_workflows, get_job_outliers, add_feedback_to_event, clear_event_feedback, add_agentic_notes, reprocess_events, reprocess_event_by_id, delete_events, ingest_event, export_event_by_id, transfer_event
buckets: query_buckets, get_bucket, get_similar_buckets, reprocess_buckets, request_bucket_model_update, request_bucket_model_update_by_filters, approve_bucket_feedback, update_bucket_feedback_state, delete_buckets
metrics: get_job_metrics, get_job_and_model_metrics, get_model_metrics, request_model_metrics_recompute, get_platform_metrics, get_internal_metrics, get_field_metrics, export_feedback, set_production_date
platform: health_check, get_platform_info, get_system_timestamp, delete_storage_data
code_blocks: generate_code_instructions, execute_code, execute_code_async, save_code

arcanna-agents-mcp

workflows: list_agentic_workflows, get_agentic_workflow_by_id, create_agentic_workflow, update_agentic_workflow, run_agentic_workflow, test_agentic_workflow, list_agent_tools, list_llm_providers, get_workflow_session, answer_workflow_decision, continue_workflow_session, stop_workflow_sessions

arcanna-rag-mcp

documents: query_rag_documents, get_rag_document, upload_rag_documents, update_rag_document, delete_rag_document, approve_rag_document, reject_rag_document, retry_rag_document, get_rag_pipeline_status
collections: query_rag_collections, create_rag_collection, update_rag_collection, delete_rag_collection, create_rag_subcollection, update_rag_subcollection, delete_rag_subcollection, list_rag_tags

Breaking changes in 0.2.0

The single server was split into three and tools were renamed or replaced. Tool names referenced in roles, assistant tool settings or agentic workflows must be updated by hand:

Removed / renamed	Use instead
`upsert_resources`	`create_integration / update_integration / create_job / update_job`
`get_resources`	`search_integrations / search_jobs / get_integration_details / get_job_details`
`delete_resources`	`delete_integration / delete_job`
`integration_parameters_schema`	`get_integration_type_metadata`
`setup_integration`	`create_integration`
`setup_job`	`create_job`
`metrics_job`	`get_job_metrics`
`metrics_job_and_latest_model`	`get_job_and_model_metrics`
`metrics_model`	`get_model_metrics`
`metrics_model_request_recompute_metrics`	`request_model_metrics_recompute`
`agents_tool_discovery`	`list_agent_tools`
`get_llm_integrations`	`list_llm_providers`

Agentic tools moved from the arcanna server to arcanna-agents. execute_code now runs a saved code block integration on a stored event (the inline test endpoint no longer exists); save_code saves through IaC.

Development

venv/bin/uv sync
.venv/bin/python -m pytest -q tests
.venv/bin/python -m pyright src

Tools are generated from the Arcanna OpenAPI specs, then trimmed by hand:

Refresh the specs from a modular-framework checkout (see scripts/dump_specs.py).
Map the tool in scripts/tool_map.py (server, module, operationId, scopes).
.venv/bin/python scripts/gen_tools.py appends a stub to the module; add it to export_tools() and trim the docstring to: what it does, when to use it vs its neighbour, response shape, cost, and what not to use it for. tests/test_tools.py checks mapping, scopes, descriptions, docstring length and the called endpoint.