The PolicyLayer MCP Registry: live risk records for 32,000 servers
Every MCP server, continuously watched: identity, tool surface, auth posture and a change feed you can subscribe to. Search it or license the data.
35 posts
Every MCP server, continuously watched: identity, tool surface, auth posture and a change feed you can subscribe to. Search it or license the data.
Robinhood's MCP lets an AI agent place real trades with no broker-side cap. A few simple rules at the gateway stop a rogue or hijacked agent draining the account.
AWS built AgentCore Policy on Cedar: deterministic authorisation at the MCP gateway, outside the LLM loop. The architecture PolicyLayer ships.
The NSA published 17 pages on MCP security. We map every recommendation to where enforcement actually happens: the call path between agent and tool.
MCP ships no auth model of its own. Here is how MCP authentication actually works, where it breaks across a fleet, and how to fix it at the gateway.
Authentication proves who is calling. MCP authorization decides what they can do. Here is how to add per-tool, per-argument limits to AI agents.
MCP's OAuth flow lets agents reach protected servers without static keys. Here is how MCP OAuth works, where it gets messy across a fleet, and how to manage it.
Anthropic showed model defences can't stand alone: Claude leaked secrets 24 of 25 times under injection. Why AI agent containment belongs at the environment layer.
Branch-level Deny if rules and protected-repo allowlists for the GitHub MCP server. Stop autonomous agents force-pushing to main or deleting your repos.
Stop autonomous agents POSTing your data to attacker domains. PolicyLayer's URL allowlists turn MCP fetch and HTTP tools into deterministic one-way readers.
Stop autonomous agents from burning through your inference budget. PolicyLayer's cost-scaled limits cap LLM tokens, not just tool calls, on every MCP server.
Lock your AI agent's kubectl access to dev and staging namespaces. PolicyLayer adds a second wall on top of Kubernetes RBAC and audits every blocked call.
Stop chasing 30 developers to update MCP configs on every key rotation. Centralised credentials behind the gateway, labelled Grant tokens, one update.
Stop your agent running rm -rf through a third-party shell-exec MCP server. PolicyLayer Require and Deny if rules give you a two-layer command allowlist.
Lock your Slack MCP server to specific channels and strip destructive tools from the MCP handshake. Practical Require, Deny if, and Hide policy walkthrough.
A concrete walkthrough of indirect prompt injection delivered via MCP tool responses. The attack, the model's reasoning, and the policy that stops it.
Discover why system prompts fail as a security boundary for AI agents, and how transport-level MCP proxies provide deterministic guardrails.
Learn how to use PolicyLayer's hosted proxy gateway to secure Claude Code tool usage, inspect JSON-RPC arguments, and set up policy boundaries on upstream MCP servers.
Anthropic published the production playbook for MCP: 300M SDK downloads, thin tools over 2,500 endpoints, OAuth vaults. The playbook stops at the tool call. Argument-level policy is what comes next.
Cloudflare's enterprise MCP launch solves discovery, access, and shadow-MCP prevention. That's the baseline. The harder question — what agents are allowed to do once they're inside — needs a different primitive.
Microsoft's open-source toolkit: nine packages for agent policy, identity, and compliance. Review of what works — and the MCP-shaped hole teams must bridge themselves.
A 10-point checklist for deploying AI agents that call APIs, move money, and modify databases. Covers deny-by-default, spend limits, rate limiting, and approval workflows.
MCP policy enforcement intercepts every AI agent tool call and evaluates it against deterministic rules before execution. Here's how it works and how to set it up.
System prompts can't enforce spending limits or prevent destructive operations. Here's why prompt guardrails fail for tool-calling AI agents and what works instead.
X released an official MCP server with 131 tools — including posting, DMs, follows, and deletes. Here's why that's a problem and how to enforce policies on it.
Cloudflare, Stripe, Supabase, Sentry, Firebase — we ran PolicyLayer's scan against real .mcp.json files from well-known repos. Most expose destructive tools with zero policy enforcement.
Security researchers filed 30+ CVEs against MCP servers in early 2026. Patching individual servers doesn't fix the structural gap. The real fix is a policy layer that works across all of them.
A new research paper argues that LLMs cannot self-enforce security constraints. PolicyLayer implements every recommendation you can deploy today.
The filesystem MCP server gives AI agents unrestricted read and write access. Here's how to rate limit file operations and prevent destructive mistakes.
The GitHub MCP server exposes 83 tools — including file deletion, repo creation, and PR merges. Here's how to enforce policies before your agent ships something it shouldn't.
Prompt guardrails for MCP agents are bypassable and unauditable. Why deterministic policy enforcement at the transport layer is the real security primitive.
LLMs can't reliably self-enforce safety rules. Deterministic policy enforcement outside the model catches what prompts miss — here's the architecture.
What happens when your AI agent goes rogue? Six failure modes — runaway loops, spending spirals, destructive ops — and the deterministic policies that stop them.
An agent that knows its spending limit treats it as a budget to burn. Enforce quotas at the MCP gateway, where the agent never sees the rule.
As AI agents improve, will they become reliable enough to handle money without guardrails? We argue that deterministic policy layers will always be necessary—and that's a feature, not a bug.