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mcp-agent-trace-inspector

by dbsectrainer

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    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI agents to self-report every tool call, token usage, decision, and session grade into a local SQLite store, so users can trace execution, audit reasoning, and see per-session costs in a local dashboard. Also supports proxy mode to intercept and trace MCP tool invocations for agents that cannot self-report.
      48 npm
      2
      MIT
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents and developers to query traces, sessions, and exceptions for debugging and observability, alongside tools for prompts, datasets, annotation queues, scores, and metrics. Supports selective tool loading and a read-only mode for safer local access from any MCP client.
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    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents and developers to query traces, observations, sessions, and exceptions, plus prompts, datasets, annotation queues, scores, and aggregated metrics, for local debugging and observability from any MCP client. Supports selective tool-group loading to cut token overhead and a read-only mode that disables all write operations.
      -
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents and MCP clients to locally debug observability data — traces, observations, sessions, exceptions, route decisions, prompts, datasets, metrics, and annotation queues — through 48 query and management tools. Supports selective tool-group loading to cut token overhead and a read-only mode that disables all write operations.
      -
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents and MCP clients to locally debug Langfuse traces, sessions, and exceptions, and to query prompts, datasets, metrics, and annotation queues. It pairs with an included agent skill to provide trace debugging, exception triage, and latency analysis workflows.
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    TDQS

    A3.6/5.0

    Scored across 13 tools

    Disambiguation4/5

    The core lifecycle tools (trace_start, trace_step, trace_end, get_trace_summary, list_traces) are clearly distinct, and the retention pair (set_retention_policy vs apply_retention) is differentiated by config-vs-execute semantics. The three export tools (export_compliance_log, export_dashboard, export_otel) are the only mild risk, but their descriptions and output formats clearly separate them.

    Naming Consistency4/5

    Most tools follow a consistent verb_noun snake_case convention (configure_alerts, set_retention_policy, export_compliance_log, get_trace_summary, list_traces). The trace_start/trace_step/trace_end trio uses noun_verb ordering, a minor deviation but internally consistent.

    Tool Count5/5

    13 tools is well-scoped for a trace inspector, covering lifecycle, analysis, export, and governance. Each tool earns its place with no redundant entries.

    Completeness4/5

    The trace lifecycle (start/step/end/summary/list), comparison, reasoning extraction, retention, alerts, compliance, and multiple export formats are all covered. Minor gaps exist such as no direct trace deletion or per-step retrieval/filtering, but agents can work around these.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues