"Understanding Call Hierarchy in Software Development or Programming" matching MCP servers:

MCP servers for real-time development monitoring and interactive pair programming.

MCP server for On-Call Health burnout analysis. Connects AI assistants to your on-call data for workload insights.

MCP server that diagnoses ML model regressions by correlating drift reports, eval runs, and deploy logs, providing evidence-cited incident reports through a set of investigation tools.

MCP server that reads Spark profiler files to give accurate Minecraft server tuning advice, parsing binary protobuf directly and diagnosing TPS, MSPT, GC, heap, and call-tree issues.

Enables AI assistants to query and analyze AI agent sessions from observability providers like Shepherd (AIOBS) and Langfuse, allowing users to debug agent runs, compare sessions, track performance, and analyze LLM usage patterns.

A paid, hosted MCP server that acts as a witness layer for AI agent tool calls, providing receipt creation, approval evidence, argument redaction, result summaries, and audit exports.

Enables LLMs to analyze and manage DBOS workflows, including introspection, workflow management, and authentication, to help debug applications in development or production.

Patent-pending diagnostic + decisions-ledger engine for any host software system — operator briefs and a severity-gated MCP console.

Enables read-only MCP access to Tactical RMM, allowing agents to query devices, clients, sites, audit logs, software, and pending actions without any mutating capabilities.

Enables incident detection and analysis by identifying anomalies in metric time series and surfacing root-cause candidates and recommended actions. Supports both mock (synthetic) and VictoriaMetrics backends with identical MCP tool contracts for seamless development-to-production switching.

Monitors development server logs in real-time and provides Claude with immediate error notifications via Server-Sent Events. Intelligently parses TypeScript, Svelte, and Vite errors with severity classification and file correlation.

Wraps your existing MCP servers and checks each tool call against policy and live state before it runs. Allow, block, or require a refresh, with a reason the agent can act on.

An incident management MCP server for on-call engineers, providing tools to search incidents, review deploys, query logs, analyze latency metrics, and acknowledge or summarize incidents.

Enables MCP-compatible agents to query a pay-per-call archive of production failure post-mortems, with free tools for sampling and claim prechecks and paid tools for searching incidents, auditing claims, generating risk briefs, and retrieving research or full archive data.

Real-time observability dashboard for monitoring AI agents in multi-agent development workflows, with live WebSocket updates of tool calls, sessions, and usage statistics.

Enables interaction with Jira Service Management Operations alerts and on-call schedules, including searching alerts, reading notes and activity logs, acknowledging, closing, annotating, adding responders, and querying current and next on-call rotations.

Relays error logs from other MCP servers when an LLM call fails and the returned error message is unclear, helping the model handle errors more intelligently.

MCP server exposing rlg (RustLogs) log files as tools for on-call / SRE agent workflows. Three tools over JSON-RPC stdio — tail_log (last N events, filtered by level/target), filter_log (predicate filtering), summarize_errors (grouped error taxonomy). Pure Rust. MIT OR Apache-2.0.

Laravel Telescope-style debugging for Hono apps whose dashboard endpoint is also an MCP server: read recent exceptions with the request that produced them, recent requests filtered by status or duration, one request in full, and the slowest queries. Five read-only tools, zero runtime dependencies.

MCP server for analyzing Perfetto traces with LLMs — query .pftrace files in PerfettoSQL via Claude Code or any MCP client