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.

SERVERMcp Knowledge SOURCEhttps://mcp.gapup.io
Low RISK CLASS
Category Read
Parameters 73 required
Recommended Allowedsee the rule below
Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-getgapup-mcp-knowledge/working-capital.md

What working_capital does on Mcp Knowledge

AI agents call working_capital 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.

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
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 Low

The tool appears to analyze working capital (BFR - Besoin en Fonds de Roulement) and return structured financial analysis/recommendations. The description emphasizes 'Returns a structured, audited deliverable' and references optimization metrics (DSO reduction, cash freed), suggesting it reads/analyzes financial data and produces advisory output rather than executing transactions or moving money.

From the tool's definition Optimiseur du BFR — Gapup agent-payable C-suite expertise (CFO). Returns a structured, audited deliverable.

Risk signalsHigh parameter count (18 properties)

Questions about working_capital

What does the working_capital tool do? +

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 Read tool in the Mcp Knowledge MCP Server, which means it retrieves data without modifying state.

What parameters does working_capital accept? +

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.

How do I enforce a policy on working_capital? +

Register the Mcp Knowledge 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 Mcp Knowledge. Nothing to install.

What risk level is working_capital? +

working_capital is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit working_capital? +

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.

How do I block working_capital completely? +

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.

What MCP server provides working_capital? +

working_capital 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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