"Step-by-step guide to breaking down a request into parts" matching MCP servers:

MCP server that transforms raw log query results into structured incident reports (Markdown, JSON, HTML) with correlation to git commits and tickets.

Enables read-only interaction with official Embrace MCP tools while preserving full structured response data, including session aggregates and detailed logs, crashes, network, and spans, through a local stdio server.

Streams browser DevTools console, network, storage, and performance data to your IDE's AI agent for real-time debugging and analysis.

An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.

Fetches Langfuse observability traces directly into a VS Code coding agent's context, enabling querying and viewing trace data through natural language.

Enables AI agents to monitor Docker containers, system resources, ports, and logs in real-time.

Enables assistants to securely work on a Chest via personal access token: reading tool logs, builds, and databases, editing rows and variables, and installing or linking tools, with every write requiring a dry run and human confirmation.

Provides MCP tools to create and query SigNoz trace funnels, enabling agents to measure their own step conversion rates from within the agent loop.

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 that exposes Avangenio's service status by fetching and parsing status.avangenio.com/data.txt into normalized JSON.

A read-only MCP server for Proxmox VE that provides AI assistants with structured visibility into cluster nodes, guests, storage, and Docker workloads. It is designed to prevent any mutating operations by construction.

Enables AI agents to query Oracle WebLogic Server runtime state, health, and JVM metrics through the REST management API, and to start, shut down, or force-shut-down servers via Node Manager, all under a least-privilege account with allowlisting, read-only mode, and JSON audit logging for every call.

Ranks log patterns by volume and cost on Splunk, Datadog, Elasticsearch, CloudWatch and ClickHouse, and plans compact, tier down or offload for the excess over each cap. Runs locally over stdio; no log data reaches log10x. Read-only against a public demo dataset without an API key.

Enables debugging of distributed transactions by continuously ingesting Docker container logs, indexing them by trace/request ID, and exposing MCP tools to search, tail, and correlate logs across services.

Enables AI agents to analyze ROS2 log files across multiple nodes by merging them into a unified timeline and providing smart query tools, without requiring ROS2 installation.

Enables AI assistants to monitor, analyze, and configure OWASP ModSecurity CRS via Docker, with tools for overview, drill-down, and rule/IP management.

MCP server that stream-parses NDJSON log files without loading them into memory — filter by pattern, detect error spikes via Z-score analysis, summarize severity timelines by time window.

Local-first dashboard + MCP server that parses Claude Code and Codex JSONL files into a SQLite cost / token tracker. Per-MCP and per-tool breakdown, session drill-down, dedup by request_id; never talks to vendor APIs

Enables agents to score, inspect, and gate tool calls before they execute, resolving shell commands the way a shell would in order to block destructive actions and detect multi-step attack sequences. It also redacts credentials and PII in either direction, requires signed single-use approval tokens for high-impact actions, and keeps a tamper-evident audit trail.

Finds problems in your MCP servers before your users do. Scans your Claude config, checks every server's capabilities, actually calls tools to make sure they work, and catches breaking changes between versions.

A Claude Code MCP server that connects to Laravel Clockwork to provide insights into application performance, database queries, errors, and request flow.

Enables developers to investigate request failures by querying Prometheus metrics, Loki logs, and Tempo traces without opening Grafana, while supporting read-only access and optional Grafana annotations.

Enables AI assistants to manage Zabbix enterprise monitoring through 100 Portuguese-language tools covering controlled network discovery, staged device onboarding, PDF/XLSX/CSV/JSON/Markdown reporting, and governance with RBAC modes, two-step approval, secret redaction, and audit logging. Supports Zabbix 6.0 through 7.4 with stdio, SSE, and Docker deployment.

A debugging gateway for distributed systems that provides 17 tools for interacting with AWS CloudWatch, Step Functions, LangSmith, and Jira. It enables efficient log analysis, workflow tracing, and ticket management while significantly reducing token usage through a single-interface discovery pattern.

A flight recorder for Claude Code that captures tool calls and observations into a SQLite database, then classifies them into a distilled timeline for incident troubleshooting.

Enables MCP clients to call a hello tool and access observability features, including metrics and request traces, through a Streamable HTTP transport with SQLite-backed storage.

Read-only MCP server for TrueNAS Scale debugging, providing k3s tools for kubectl operations and whitelisted midclt calls for system info, apps, and pools.

Enables AI agents to query an MSP's network monitoring data — tenants, discovered devices, networks, interfaces, configuration backups, alerts, performance statistics and billing usage — through multi-tenant, stateless Streamable HTTP with credentials supplied per request. Read-only by default, with optional alert dismissal and raw API access for changes.

Find the step that caused an AI agent’s failure. Ask your assistant why a run failed, see the evidence, and check whether a suggested fix works.

Enables AI agents to read incidents, alerts, on-call schedules, teams, severities and API user info, and — on explicit request — declare, update and resolve incidents, manage alerts, and create or update teams through the Rootly REST API. It is stateless and multi-tenant, taking the API token as a per-request HTTP header that is never stored.