mcp-audit-log
MCP ServerFreeStructured audit logger for MCP tool calls
Capabilities6 decomposed
structured mcp tool call logging with schema validation
Medium confidenceIntercepts and logs MCP tool invocations with structured JSON output, capturing tool name, arguments, return values, and execution metadata. Implements schema-based validation to ensure logged data conforms to predefined audit formats, enabling downstream parsing and compliance verification without custom parsing logic.
Implements MCP-native audit logging with schema validation at the protocol level, intercepting tool calls before execution rather than post-hoc logging, enabling preventive compliance checks and structured event capture aligned with MCP's resource-based architecture
Purpose-built for MCP's tool-calling semantics unlike generic logging libraries, providing schema-aware validation and MCP-specific metadata capture without requiring custom middleware
tool call argument capture and serialization
Medium confidenceCaptures and serializes tool invocation arguments into structured audit records, handling complex nested objects, arrays, and non-JSON-serializable types (Buffers, Dates, custom objects). Uses a configurable serialization strategy to represent these types in audit logs while preserving semantic meaning for later reconstruction or analysis.
Implements MCP-aware argument serialization with configurable type handlers and optional field masking, preserving non-JSON types as annotated metadata rather than lossy string conversion, enabling faithful reconstruction of tool invocations
More sophisticated than generic JSON.stringify logging because it handles MCP-specific types and supports field-level redaction, whereas standard logging libraries lose type information or fail on non-serializable objects
tool execution timing and performance metrics collection
Medium confidenceMeasures and logs execution duration, latency percentiles, and performance metrics for each tool call, capturing wall-clock time from invocation to completion. Aggregates metrics across multiple calls to enable performance profiling and bottleneck identification without requiring external APM tools.
Integrates timing collection directly into MCP tool call interception, capturing execution metrics at the protocol level without requiring instrumentation of individual tool implementations, enabling zero-overhead profiling for tool orchestration workflows
Simpler than deploying full APM solutions for MCP-specific performance monitoring, providing tool-level metrics without the overhead of distributed tracing infrastructure
tool call result capture and error logging
Medium confidenceCaptures tool return values and error states, logging successful results alongside error objects, stack traces, and failure context. Distinguishes between tool-level errors (returned error objects) and execution errors (exceptions), enabling comprehensive failure analysis and debugging without manual error handling in tool implementations.
Implements dual-path error capture at the MCP protocol level, distinguishing between tool-returned errors and execution exceptions, with automatic stack trace collection and error context preservation without requiring try-catch instrumentation in tool code
More comprehensive than generic error logging because it captures both tool-level and execution-level failures with MCP-specific context, whereas standard logging requires manual error handling in each tool implementation
audit log event emission and streaming
Medium confidenceEmits audit log entries as structured events that can be consumed by external systems via event listeners or streams, enabling real-time log processing without blocking tool execution. Implements a non-blocking event emitter pattern that decouples logging from tool execution, allowing subscribers to handle logs asynchronously.
Implements non-blocking event emission for audit logs using Node.js EventEmitter pattern, enabling asynchronous log processing without impacting tool execution latency, with support for multiple concurrent subscribers
Enables real-time log streaming without requiring external message queues or log aggregation setup, whereas traditional logging requires separate infrastructure for log collection and processing
mcp resource context and metadata capture
Medium confidenceCaptures MCP-specific context metadata alongside tool calls, including resource URIs, request IDs, user/session identifiers, and server state information. Enriches audit logs with MCP protocol context to enable correlation of tool calls across distributed systems and multi-step workflows.
Integrates MCP protocol context capture directly into audit logging, preserving resource URIs and request metadata without requiring manual context threading, enabling native correlation of tool calls within MCP's resource-based architecture
Purpose-built for MCP's context model unlike generic correlation ID systems, automatically capturing MCP-specific metadata without requiring application-level context propagation
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
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Best For
- ✓MCP server developers building production agents with compliance requirements
- ✓teams implementing audit trails for regulated environments (finance, healthcare, legal)
- ✓developers debugging multi-step tool orchestration workflows
- ✓developers building secure MCP servers that handle sensitive data
- ✓teams implementing detailed execution traces for complex tool chains
- ✓compliance officers requiring complete audit records of tool invocations
- ✓MCP server operators optimizing agent performance
- ✓teams implementing SLO monitoring for tool-based workflows
Known Limitations
- ⚠No built-in persistence layer — logs are emitted as events and require external storage (file system, database, log aggregation service)
- ⚠Schema validation adds latency per tool call; no async validation option documented
- ⚠Limited to MCP protocol tool calls; cannot audit non-MCP function invocations or external API calls
- ⚠Serialization strategy must be pre-configured; no automatic detection of sensitive fields
- ⚠Large argument payloads (>1MB) may impact logging performance; no built-in truncation or sampling
- ⚠Circular references in arguments may cause serialization failures without custom handlers
Requirements
Input / Output
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Structured audit logger for MCP tool calls
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