Goal: Integrate a client for the newly released Alanube MCP server, which exposes 30 e-invoicing tools for AI agents via JSON-RPC.
Key tasks:
- Create
AlanubeMCPClient: a class handling connection to the MCP endpoint (https://sandbox-mcp.alanube.co/mcp/rd) and token-based authentication.
- Map tools to Python methods across the three catalog layers:
- Orchestration (priority):
issue_and_track_rd_document
- Issuance/Status: 10 pairs for each e-CF type (31–47)
- Diagnostics:
diagnose_rd_api_error, validate_rd_request_payload
- Support key flows: synchronous (immediate response) and asynchronous (configurable polling via
max_status_checks and status_check_interval_ms).
- Tests and examples against the sandbox, including the documented quick start.
Expected outcome: issue and track e-invoices from Python with a clean API like:
client = AlanubeMCPClient(api_token="...")
result = client.issue_and_track_document(
document_type_code="32",
payload={...},
wait_for_final_status=True
)
Goal: Integrate a client for the newly released Alanube MCP server, which exposes 30 e-invoicing tools for AI agents via JSON-RPC.
Key tasks:
AlanubeMCPClient: a class handling connection to the MCP endpoint (https://sandbox-mcp.alanube.co/mcp/rd) and token-based authentication.issue_and_track_rd_documentdiagnose_rd_api_error,validate_rd_request_payloadmax_status_checksandstatus_check_interval_ms).Expected outcome: issue and track e-invoices from Python with a clean API like: