HR tech intelligence for CHROs, recruiters, VC teams, comp & benefits leads and workforce planners. Four modes powered by ESCO, O*NET, BLS OES and crowd-sourced salary data: • salary_benchmark — cash-only salary medians (p25/median/p75) for 54+ roles across US/EU/Asia. Covers tech, finance, compl...
Part of the Mcp Knowledge server.
Free to start. No card required.
AI agents use talent_intelligence to create or modify resources in Mcp Knowledge. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.
Without a policy, an AI agent could call talent_intelligence repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Mcp Knowledge.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"talent_intelligence": {
"limits": [
{
"counter": "talent_intelligence_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full Mcp Knowledge policy for all 271 tools.
These attack patterns abuse exactly the kind of access talent_intelligence gives an agent. Each links to the full case and the policy that stops it:
Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
HR tech intelligence for CHROs, recruiters, VC teams, comp & benefits leads and workforce planners. Four modes powered by ESCO, O*NET, BLS OES and crowd-sourced salary data: • salary_benchmark — cash-only salary medians (p25/median/p75) for 54+ roles across US/EU/Asia. Covers tech, finance, compliance, healthcare, marketing, ops and C-suite. Data from BLS OES, Levels.fyi and StackOverflow Developer Survey 2024. • skills_taxonomy — maps a skill to its ESCO URI, O*NET codes, skill type (hard/soft/knowledge/cert), 8 related skills with similarity scores and typical roles. • job_market_trends — YoY growth %, open positions estimate, top employers and leading skills per job category × country. Static 2024 data with BLS baseline fallback. • adjacent_roles — up to 6 roles adjacent to a source role with ESCO taxonomy adjacency: similarity score, salary delta % and skills overlap %. All salary data is cash-only (excludes equity/RSU/bonus). Cache TTL: 24h (stable labour market data). Optional env ONET_API_KEY for authenticated O*NET lookups (free registration at onetcenter.org).. 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.
Register the Mcp Knowledge MCP server in PolicyLayer and add a rule for talent_intelligence: 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.
talent_intelligence 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 talent_intelligence 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 talent_intelligence. 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.
talent_intelligence 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.
Deterministic rules across all 271 Mcp Knowledge tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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