social_engagement_velocity_tracker
Tracks hourly social engagement velocity (likes, shares, comments) across Twitter, LinkedIn, and Reddit for CMOs. Inputs include platform handles/subreddits and time range. Outputs engagement metrics, velocity trends, and platform-specific insights. Ideal for real-time marketing performance monit...
This record as markdown: /tools/io-github-getgapup-mcp-knowledge/social-engagement-velocity-tracker.md
What social_engagement_velocity_tracker does on Mcp Knowledge
AI agents call social_engagement_velocity_tracker 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 |
|---|---|---|---|
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 |
hours | number | — | |
platforms | array | Yes |
Parameters from the server's own tool schema.
Why social_engagement_velocity_tracker is rated Low
This tool retrieves and aggregates social media metrics from Twitter, LinkedIn, and Reddit. It is purely a read/query operation that fetches engagement data and presents analytics. No data is created, modified, deleted, or any external operations triggered. Severity is low as it only reads publicly available social engagement data.
From the tool's definition Tracks hourly social engagement velocity (likes, shares, comments)... Outputs engagement metrics, velocity trends, and platform-specific insights
Attacks that exploit this kind of access
The rule that runs social_engagement_velocity_tracker 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 social_engagement_velocity_tracker, this is the rule to start with:
social_engagement_velocity_tracker 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 social_engagement_velocity_tracker call is checked against it from then on.
Questions about social_engagement_velocity_tracker
Tracks hourly social engagement velocity (likes, shares, comments) across Twitter, LinkedIn, and Reddit for CMOs. Inputs include platform handles/subreddits and time range. Outputs engagement metrics, velocity trends, and platform-specific insights. Ideal for real-time marketing performance monitoring and competitive benchmarking. Keywords: social media analytics, engagement tracking, marketing KPIs, CMO dashboard. It is categorised as a Read tool in the Mcp Knowledge MCP Server, which means it retrieves data without modifying state.
social_engagement_velocity_tracker accepts 3 parameters: async, hours, platforms. Required: platforms. 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 social_engagement_velocity_tracker: 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.
social_engagement_velocity_tracker 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 social_engagement_velocity_tracker 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 social_engagement_velocity_tracker. 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.
social_engagement_velocity_tracker 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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