content_evergreen_score_analyzer
Evaluates content evergreen potential for CMOs by analyzing historical traffic patterns and backlink authority. Takes a content URL and optional time range, returns an evergreen score (0-100), traffic trend analysis, and backlink profile. Ideal for content strategy planning, SEO optimization, and...
This record as markdown: /tools/io-github-getgapup-mcp-knowledge/content-evergreen-score-analyzer.md
What content_evergreen_score_analyzer does on Mcp Knowledge
AI agents call content_evergreen_score_analyzer to retrieve information from Mcp Knowledge without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
url | string | Yes | Content URL to analyze |
async | boolean | — | If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client ti |
toDate | string | — | End date for historical analysis (YYYY-MM-DD) |
fromDate | string | — | Start date for historical analysis (YYYY-MM-DD) |
Parameters from the server's own tool schema.
Why content_evergreen_score_analyzer is rated Low
This tool purely retrieves and analyzes publicly available data (historical traffic patterns, backlink profiles) from public APIs (Wayback Machine, Common Crawl). It reads and scores content without modifying, executing, or deleting anything. Misuse potential is minimal as it only queries external public data sources.
From the tool's definition Evaluates content evergreen potential...analyzing historical traffic patterns and backlink authority...returns an evergreen score (0-100), traffic trend analysis, and backlink profile. Uses Wayback Machine and Common Crawl public APIs.
Risk signalsAccepts URL/endpoint input (url)
Attacks that exploit this kind of access
The rule that runs content_evergreen_score_analyzer safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mcp Knowledge, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For content_evergreen_score_analyzer, this is the rule to start with:
content_evergreen_score_analyzer is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Mcp Knowledge, apply this rule, and every content_evergreen_score_analyzer call is checked against it from then on.
Questions about content_evergreen_score_analyzer
Evaluates content evergreen potential for CMOs by analyzing historical traffic patterns and backlink authority. Takes a content URL and optional time range, returns an evergreen score (0-100), traffic trend analysis, and backlink profile. Ideal for content strategy planning, SEO optimization, and identifying high-value evergreen assets. Uses Wayback Machine and Common Crawl public APIs. It is categorised as a Read tool in the Mcp Knowledge MCP Server, which means it retrieves data without modifying state.
content_evergreen_score_analyzer accepts 4 parameters: url, async, toDate, fromDate. Required: url. The full parameter table on this page comes from the server's own tool schema.
Register the Mcp Knowledge MCP server in PolicyLayer and add a rule for content_evergreen_score_analyzer: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Mcp Knowledge. Nothing to install.
content_evergreen_score_analyzer is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the content_evergreen_score_analyzer rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for content_evergreen_score_analyzer. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
content_evergreen_score_analyzer is provided by the Mcp Knowledge MCP server (https://mcp.gapup.io). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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