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Intercept and block MCP tool calls with YAML policies for safer AI agents.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mcp-runtime-guard" yet — see the docs or source repo.
Create a YAML policy for my MCP runtime guard that blocks AI agents from deleting files, executing shell commands, and accessing production database tools, and returns clear reasons for blocked requests.
A ready-to-use YAML security policy defining blocked tool types, matching rules, and denial messages.
Design an environment-based MCP policy: allow file reads and test commands in development but block network access; in production, allow only read-only tool calls. Output the YAML example.
A YAML policy example separating development and production rules with clear allow and deny scopes.
An MCP tool call was blocked by the runtime guard. Based on this policy and call log, identify which rule matched, why it was blocked, and suggest a safer way to allow it.
An analysis of the matched rule, the blocking reason, and safer policy adjustment recommendations.
Manage, proxy, and secure MCP servers with centralized access control.
Gate MCP agent actions through compliance policies before execution.
Secure MCP servers with policy checks, redaction, access control, and audit logs
Manage notes securely with policy controls, approvals, and prompt injection detection.
Run a local-first MCP proxy with secure discovery and major token savings.
Securely create isolated test branches for AI agents without exposing production secrets.