action_plan_esg
Plan d'action ESG — Gapup agent-payable C-suite expertise (SUSTAINABILITY). Returns a structured, audited deliverable. Reference case: TechCorp SAS — Plan ESG 36 mois (500 FTE, €60M CA, score 54→76/100). Inputs are validated server-side — send the documented case fields.
This record as markdown: /tools/io-github-getgapup-mcp-knowledge/action-plan-esg.md
What action_plan_esg does on Mcp Knowledge
AI agents use action_plan_esg 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.
| 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 |
focus | string | — | |
company | object | Yes | |
horizon | string | Yes | |
ambitions | object | Yes | |
targetLabels | array | — | |
currentScores | object | — | |
availableResources | object | Yes |
Parameters from the server's own tool schema.
Why action_plan_esg is rated Medium
This tool produces a structured ESG action plan (a document or report artifact). It creates/generates a deliverable based on input case fields. There is no indication of financial transactions, destructive operations, or code execution. It writes/creates an output artifact (an action plan), making 'Write' the most appropriate category.
From the tool's definition 'Plan d'action ESG' and 'Returns a structured, audited deliverable' — generates a structured ESG action plan document/deliverable
Risk signalsHigh parameter count (23 properties)
Attacks that exploit this kind of access
The rule that runs action_plan_esg 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 action_plan_esg, this is the rule to start with:
action_plan_esg stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. 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 action_plan_esg call is checked against it from then on.
Questions about action_plan_esg
Plan d'action ESG — Gapup agent-payable C-suite expertise (SUSTAINABILITY). Returns a structured, audited deliverable. Reference case: TechCorp SAS — Plan ESG 36 mois (500 FTE, €60M CA, score 54→76/100). 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.
action_plan_esg accepts 8 parameters: async, focus, company, horizon, ambitions, targetLabels, currentScores, availableResources. Required: company, horizon, ambitions, availableResources. 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 action_plan_esg: 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.
action_plan_esg is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the action_plan_esg 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 action_plan_esg. 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.
action_plan_esg 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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