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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.
Enforce permissions, approvals, sanitization, and audit for AI agent MCP calls.
Add security scanning, risk gating, and safe execution to MCP tool calls.
Enforce policy checks on AI tool calls without exposing system credentials.
Secure LLM and MCP tool interactions with zero-trust controls and policy enforcement.
Protect MCP-connected agents with PII redaction, rate limits, and policy enforcement.
Gate MCP agent actions through compliance policies before execution.