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scaleway-ops-mcp-server

by gkrost

Create a Scaleway Audit Trail export job

scaleway_audit_create_export_job

Create an Audit Trail export job to ship audit events to an existing Object Storage bucket. Requires confirm=true; triggers immediate backfill of past events. Specify bucket, prefix, and region to start delivery.

Instructions

Create an export job shipping Audit Trail events to an Object Storage bucket (S3 destination). Requires confirm=true. The bucket must already exist and be writable - create it first (e.g. scaleway_s3_create_bucket). Live-verified 2026-08-18: creation triggers an IMMEDIATE backfill, not just a future cadence - a fresh job wrote ~6 days of past daily log objects (one JSON file per day, e.g. '2026/07/12/logs_*.json') into the bucket within seconds of creation. scaleway_audit_delete_export_job does not delete these - if you created a bucket just to test this, you'll need to empty it (object-level operations are out of scope for this server) before scaleway_s3_delete_bucket will succeed. Check last_run_at / last_status via scaleway_audit_list_export_jobs afterwards for the ongoing cadence. Needs more than AuditTrailReadOnly on THIS server's own credential (read-only covers just the query tools) - if the call fails with permissions_denied, grant the Audit Trail write permission set via scaleway_iam_set_policy_rules.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesName of the export job.
tagsNoTags for the export job.
bucketYesObject Storage bucket the audit events are shipped to. It must already exist - create it first (e.g. scaleway_s3_create_bucket).
prefixNoKey prefix inside the bucket to write under, e.g. 'audit-trail/'.
regionNoDefaults to the server's configured region (fr-par).
confirmYesMust be explicitly true. Creation triggers an immediate backfill of real audit events into the destination bucket; delete does not remove those objects.
project_idNoProject owning the destination bucket. Defaults to the server's configured Project.
bucket_regionNoRegion of the destination bucket. Defaults to the server's configured region (fr-par).
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description goes far beyond annotations by revealing immediate backfill behavior, non-deletion of objects by delete_export_job, and the need for bucket cleanup. It also includes a live-verified date and troubleshooting for permissions_denied, providing strong operational context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Six sentences, each carrying distinct, high-value information including purpose, prerequisites, side effects, and permissions. Slightly long but every sentence is necessary; front-loaded with the core action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with 8 parameters and no output schema, the description comprehensively covers preconditions, side effects, monitoring, and permission requirements. It also references related tools for bucket creation and job deletion, giving a complete operational picture.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema covers 100% of parameters with descriptions; the description mostly reiterates bucket and confirm semantics already present in the schema. It adds no new parameter-level details beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool creates an export job for Audit Trail events to an S3-compatible Object Storage bucket. The verb 'create' and resource 'export job' are specific, and it differentiates from sibling delete/list export job tools by describing the shipping destination.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit prerequisites (bucket must exist and be writable), a required confirm=true, and post-creation monitoring via scaleway_audit_list_export_jobs. It also mentions the permission boundary (read-only covers only query tools) and a remediation step, making it clear when this tool is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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