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cloudflare-mcp

by pocc

get_audit_logs

Get Cloudflare account audit logs for user actions, API calls, and configuration changes. Filter by dates, IP, zone, actor, or action type to investigate activity.

Instructions

Get audit logs for a Cloudflare account. Returns recent activity including user actions, API calls, and configuration changes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number
sinceNoStart date in ISO 8601 format (e.g., 2024-01-01T00:00:00Z)
beforeNoEnd date in ISO 8601 format
actor_ipNoFilter by actor IP address
per_pageNoResults per page (max 1000)
zone_nameNoFilter by zone name
account_idYesThe account ID
action_typeNoFilter by action type (e.g., 'add', 'delete', 'edit')
actor_emailNoFilter by actor email address

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It states that the tool returns recent activity and enumerates the kinds of activities included, which is useful. However, it does not clarify pagination behavior, default time ranges, data volume expectations, or the lack of side effects beyond what the 'get' name implies.

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?

The description is a single front-loaded sentence with no filler. It communicates the resource scope and return contents efficiently, though it repeats the tool's name somewhat and could have used the space to add constraints or distinctions.

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

Completeness2/5

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

The tool has 9 parameters, no output schema, and no annotations, so the description needs to provide more context. It explains what kind of activity is returned but not the response structure, pagination semantics, default behavior when date filters are omitted, or operational caveats. An agent would still need to infer several important calling details.

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?

Schema description coverage is 100%, so the baseline is 3. The description adds no parameter-specific meaning beyond the schema, such as how 'since' and 'before' interact, default pagination values, or ordering of results, but the schema already documents each parameter adequately.

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

Purpose4/5

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

The description clearly identifies the operation as retrieving audit logs for a Cloudflare account and specifies the content categories: user actions, API calls, and configuration changes. It is distinguishable from nearby siblings like get_access_logs, but it does not explicitly name or contrast itself with those alternatives.

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

Usage Guidelines2/5

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

The description implies use when account-level audit logs are needed, but it provides no explicit guidance on when to use this tool versus alternatives, no exclusions, and no context about limitations such as retention windows or when filters should be applied.

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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