PolicyLayer Intercept — open-source policy enforcement proxy for MCP

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We built Intercept, a transparent proxy that enforces YAML policies on every MCP tool call before it reaches the upstream server.

The problem: when you connect an agent to an MCP server, it gets access to every tool with no granular controls. There's no protocol-level way to say "read-only," "max 5 calls per hour," or "block deletions."

Intercept sits between the agent and the server. You write a YAML policy file, and every tool call is evaluated before it's forwarded. If the policy says no, the call never reaches upstream.

What it supports:

• Unconditional blocks (deny specific tools entirely)
• Rate limits (sliding window counters)
• Argument validation (regex, allowlists, numeric bounds)
• Spend caps (stateful daily/hourly counters)
• Full audit logging

Example policy:

delete_repository:
  rules:
    - name: "block repo deletion"
      action: "deny"
      on_deny: "Repo deletion not permitted via AI agents"

create_issue:
  rules:
    - name: "hourly issue limit"
      rate_limit: 5/hour
      on_deny: "Hourly limit of 5 new issues reached"

Run it:

intercept -c policy.yaml -- npx -y @modelcontextprotocol/server-github

Enforcement is at the transport layer — below the model, invisible to the agent. No agent or server code changes needed. Works with any MCP server. Apache 2.0 licensed.

The main challenge was designing the policy language to be expressive enough for real use cases without becoming a nightmare to configure. We landed on YAML with a "first match wins" rule evaluation — same mental model as firewall rules.

Would love feedback from the MCP community on what policy primitives matter most as agents get more autonomous.

Relevant Links

GitHub repository: https://github.com/policylayer/intercept
Site: https://intercept.policylayer.com/
Policy reference: https://github.com/policylayer/intercept/blob/main/POLICY.md
Usage guide: https://github.com/policylayer/intercept/blob/main/USAGE.md