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cf-mcp

by wojtekkura
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

cf_build_dashboard_url

Construct a deep link to the Cloudflare dashboard for a specified view type, account, and optional zone and filters. Use this to navigate directly to security events, WAF rules, analytics, or other Cloudflare services.

Instructions

Construct a deep link into the Cloudflare dashboard for a given view.

Args:
    view_type: one of:
        security_events, waf_custom_rules, rate_limiting_rules,
        bot_management, analytics_traffic, logpush,
        access_apps, gateway_rules.
    account_id: Cloudflare account ID. Required for all views. Falls back
        to CF_ACCOUNT_ID env var when not supplied.
    zone: zone name or zone ID for zone-scoped views (e.g. "example.com").
    filters: optional `?key=value` query-string overrides (e.g.
        `{"action": "block"}` on security_events).

Returns: envelope with `data = {url, view_type, account_id, zone}`.

Errors:
    validation when view_type is unknown, account_id is missing, or a
    zone-scoped view was called without a zone.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
view_typeYes
account_idNo
zoneNo
filtersNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Tool Definition Quality

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries full burden. It reveals that the tool constructs a URL, falls back to an environment variable for account_id, validates view_type, returns an envelope, and errors on validation. No destructive actions are implied.

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 well-structured with bullet points and clear separation of args, returns, and errors. It is somewhat lengthy but every sentence adds value; could be slightly more concise but still effective.

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?

Given 4 parameters, no annotations, and no structured output schema, the description is complete. It covers all parameters, return envelope, error conditions, and usage details. An agent can correctly invoke this tool without additional information.

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

Parameters5/5

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

Schema description coverage is 0%, so the description fully compensates. It explains each parameter: view_type with a list of valid values, account_id with env fallback, zone for zone-scoped views, and filters with an example. This adds essential meaning beyond the schema.

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?

The description clearly states the verb 'Construct' and the resource 'deep link into the Cloudflare dashboard for a given view.' It distinguishes this utility tool from sibling query/manage tools, which are all about retrieving or modifying data.

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?

The description explains the purpose and parameter usage, guiding when to use this tool (to build a dashboard URL). It does not explicitly state when not to use or provide alternatives, but the context from sibling tools makes it clear. The instructions on required vs optional parameters are helpful.

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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