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Policies are evaluated in-process against tool schemas, arguments, and execution context, allowing fine-grained control over which tools can be called, with what parameters, and under what conditions.","intents":["I need to prevent an LLM from calling certain dangerous tools in production","I want to enforce argument constraints on tool calls (e.g., max file size, allowed domains)","I need to audit and log all tool invocations before they execute","I want to apply different policies based on user role or execution context"],"best_for":["teams building LLM agents with MCP integrations who need security guardrails","enterprises deploying AI systems with compliance requirements","developers implementing multi-tenant LLM applications with per-user tool restrictions"],"limitations":["Policy evaluation happens synchronously in-process, adding latency to each tool call (exact overhead depends on policy complexity)","No built-in distributed policy caching — policies must be loaded into each process instance","Limited to MCP protocol; does not intercept direct API calls or non-MCP tool invocations","Policy language and syntax not documented in package metadata — requires reading source or examples"],"requires":["Node.js 16+ (typical for MCP implementations)","Active MCP server and client setup","Policy definitions in supported format (format unspecified in metadata)"],"input_types":["MCP tool call requests (JSON-RPC format)","Policy rule definitions (format TBD)","Tool schema metadata"],"output_types":["Allowed/denied decision with reason","Audit logs of tool invocations","Modified tool call (if policy rewrites arguments)"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-policylayerintercept__cap_1","uri":"capability://safety.moderation.declarative.policy.rule.evaluation.engine","name":"declarative policy rule evaluation engine","description":"Evaluates tool call requests against a set of declarative policy rules using pattern matching and conditional logic, supporting rule composition and context-aware decision making. 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Uses a middleware chain pattern to apply policies, logging, and transformations in sequence, with support for request/response modification and early termination based on policy decisions.","intents":["I want to add policy enforcement to an existing MCP setup without modifying client or server code","I need to inspect and log all tool calls passing through my MCP infrastructure","I want to modify tool call arguments before they reach the server (e.g., sanitize paths)","I need to inject additional context or metadata into tool calls"],"best_for":["platform teams operating shared MCP infrastructure","developers adding security layers to existing MCP deployments","teams needing centralized observability for tool usage"],"limitations":["Proxy adds network hop and processing latency to every tool call (exact overhead depends on policy complexity and logging verbosity)","Requires separate proxy process or sidecar deployment, adding operational complexity","No built-in load balancing or failover — single proxy instance is a potential bottleneck","Transparent proxying may complicate debugging if errors occur in policy evaluation vs. tool execution"],"requires":["Node.js 16+ runtime","MCP client and server already deployed","Network connectivity between client, proxy, and server"],"input_types":["MCP JSON-RPC requests (tool calls)","MCP JSON-RPC responses (tool results)"],"output_types":["Modified or unmodified MCP requests/responses","Policy decision signals","Audit logs"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-policylayerintercept__cap_3","uri":"capability://safety.moderation.tool.call.argument.validation.and.sanitization","name":"tool call argument validation and sanitization","description":"Validates and optionally sanitizes tool call arguments against policy rules and schema constraints before execution, supporting pattern matching, type checking, and value range enforcement. Can reject calls with invalid arguments, modify arguments to meet policy requirements (e.g., enforce path prefixes), or flag suspicious patterns for logging without blocking execution.","intents":["I want to prevent path traversal attacks by validating file paths against a whitelist","I need to enforce maximum request sizes or rate limits on tool arguments","I want to sanitize user-provided input before passing it to tools","I need to reject tool calls with arguments outside safe ranges (e.g., max file size)"],"best_for":["security teams hardening LLM tool integrations against injection attacks","developers building multi-tenant systems with per-user argument constraints","teams implementing input validation as a defense-in-depth layer"],"limitations":["Validation rules must be defined per tool or per argument — no automatic schema inference from tool definitions","Sanitization is policy-driven and may not cover all attack vectors (e.g., SQL injection requires tool-specific knowledge)","No built-in support for complex validation logic (e.g., cross-argument dependencies) — would require custom rule syntax","Performance impact scales with number of validation rules and argument complexity"],"requires":["Policy rules defining validation constraints for each tool","Tool schema metadata with argument types and constraints","Clear specification of what 'sanitization' means (format unspecified)"],"input_types":["Tool call arguments (any JSON-serializable type)","Validation rule definitions","Tool schema metadata"],"output_types":["Validation pass/fail decision","Modified arguments (if sanitization applied)","Validation error details"],"categories":["safety-moderation","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-policylayerintercept__cap_4","uri":"capability://safety.moderation.audit.logging.and.compliance.reporting.for.tool.invocations","name":"audit logging and compliance reporting for tool invocations","description":"Automatically logs all tool invocations with full context (tool name, arguments, caller, decision, timestamp) to support compliance auditing and forensic analysis. Logs include policy decisions, argument values, and execution outcomes, enabling post-hoc analysis of tool usage patterns and policy violations without requiring custom logging code.","intents":["I need to maintain an audit trail of all tool calls for compliance (SOC 2, HIPAA, etc.)","I want to investigate which tools were called by which users and when","I need to detect and alert on suspicious tool usage patterns","I want to generate compliance reports showing policy enforcement in action"],"best_for":["regulated industries (finance, healthcare, government) with audit requirements","security teams monitoring LLM tool usage for anomalies","compliance officers generating audit reports"],"limitations":["Logs are generated in-process; no built-in log aggregation or centralized storage — requires integration with external logging system (e.g., ELK, Datadog)","Log format and structure not documented — unclear if structured JSON, plain text, or other format","No built-in log retention or rotation policies — requires external log management","Sensitive data in arguments (e.g., API keys, PII) may be logged unless explicitly redacted by policy"],"requires":["Logging infrastructure to capture and store audit logs","Policy definitions specifying what to log and what to redact","Sufficient disk/network capacity for high-volume tool call logging"],"input_types":["Tool call requests with full context","Policy decisions and reasons","Execution outcomes"],"output_types":["Structured audit logs (format TBD)","Compliance reports (format TBD)"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-policylayerintercept__cap_5","uri":"capability://safety.moderation.context.aware.policy.decision.making.with.user.and.environment.data","name":"context-aware policy decision making with user and environment data","description":"Evaluates policies against execution context including user identity, role, environment (dev/staging/prod), and request metadata, enabling context-dependent tool access decisions. 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