working_capital
Optimiseur du BFR — Gapup agent-payable C-suite expertise (CFO). Returns a structured, audited deliverable. Reference case: Agicap — BFR optimisation · DSO 52→38j · Cash libéré +€2.8M · 3 quick wins immédiats. Inputs are validated server-side — send the documented case fields.
This record as markdown: /tools/io-github-getgapup-gapup-mcp/working-capital.md
What working_capital does on Gapup Mcp
AI agents use working_capital to create or update resources in Gapup Mcp, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Gapup Mcp 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 |
company | object | Yes | |
industry | string | — | |
challenges | array | Yes | |
financials | object | Yes | |
topCustomers | array | — | |
topSuppliers | array | — |
Parameters from the server's own tool schema.
Why working_capital is rated Medium
While the tool does not directly move money (Financial category), it optimizes and modifies working capital structures and generates audited financial deliverables that directly impact cash management and DSO metrics. This is a Write action—it creates/modifies financial planning and operational data reversibly.
From the tool's definition Tool description states it 'Returns a structured, audited deliverable' with reference to cash liberation (+€2.8M) and optimization of working capital metrics (DSO reduction).
Risk signalsHigh parameter count (18 properties)
Attacks that exploit this kind of access
The rule that runs working_capital safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Gapup Mcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For working_capital, this is the rule to start with:
working_capital 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 Gapup Mcp, apply this rule, and every working_capital call is checked against it from then on.
Questions about working_capital
Optimiseur du BFR — Gapup agent-payable C-suite expertise (CFO). Returns a structured, audited deliverable. Reference case: Agicap — BFR optimisation · DSO 52→38j · Cash libéré +€2.8M · 3 quick wins immédiats. Inputs are validated server-side — send the documented case fields. It is categorised as a Write tool in the Gapup Mcp MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
working_capital accepts 7 parameters: async, company, industry, challenges, financials, topCustomers, topSuppliers. Required: company, challenges, financials. The full parameter table on this page comes from the server's own tool schema.
Register the Gapup MCP server in PolicyLayer and add a rule for working_capital: 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 Gapup Mcp. Nothing to install.
working_capital 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 working_capital 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 working_capital. 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.
working_capital is provided by the Gapup MCP server (https://mcp.gapup.io/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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