save_plays

Plans de sauvetage clients — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Kyriba — Plan sauvetage 30j · ARR €11.988 · Champion parti · Script 6 actions · 3 concessions. Inputs are validated server-side — send the documented case fields.

SERVERMcp Knowledge SOURCEhttps://mcp.gapup.io
Medium RISK CLASS
Category Write
Parameters 43 required
Recommended Rate-limitedsee the rule below
Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-getgapup-mcp-knowledge/save-plays.md

What save_plays does on Mcp Knowledge

AI agents use save_plays to create or update resources in Mcp Knowledge, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Mcp Knowledge environment.

ParameterTypeRequiredDescription
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
account object Yes
company object Yes
product object Yes

Parameters from the server's own tool schema.

Why save_plays is rated Medium

This tool creates and structures customer retention/rescue plans with documented deliverables and action scripts. The reference case shows it produces audited outputs that influence business decisions (champion selection, concession terms, 30-day timelines). This is a Write operation because it generates and modifies reversible business artifacts (plans, scripts, case documentation).

From the tool's definition 'Plans de sauvetage clients' (customer rescue plans); 'Returns a structured, audited deliverable'; 'Script 6 actions'; 'send the documented case fields' — indicates creation and modification of structured business plans and action scripts tied to customer…

Risk signalsHigh parameter count (13 properties)

Questions about save_plays

What does the save_plays tool do? +

Plans de sauvetage clients — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Kyriba — Plan sauvetage 30j · ARR €11.988 · Champion parti · Script 6 actions · 3 concessions. Inputs are validated server-side — send the documented case fields. It is categorised as a Write tool in the Mcp Knowledge MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

What parameters does save_plays accept? +

save_plays accepts 4 parameters: async, account, company, product. Required: account, company, product. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on save_plays? +

Register the Mcp Knowledge MCP server in PolicyLayer and add a rule for save_plays: 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.

What risk level is save_plays? +

save_plays is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit save_plays? +

Yes. Add a rate_limit block to the save_plays 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.

How do I block save_plays completely? +

Set action: deny in the PolicyLayer policy for save_plays. 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.

What MCP server provides save_plays? +

save_plays 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.

More on Mcp Knowledge, and thousands of servers like it.

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