"Using Latest Modern C++ Features in Programming" matching MCP servers:

MCP server for Healthchecks: inspect, create and adjust cron and uptime checks, and read why one failed

Lets an assistant read recorded production AI agent runs — steps, model and tool calls with arguments, and outcomes — along with the findings of comparison runs that checked a prompt or model change against those recordings, and verify a signed evidence bundle offline with no account or network. It is strictly read-only: no tool starts a replay or comparison, so nothing can spend money or act without a person deciding.

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.

Enables LLM agents to triage network incidents by fetching device telemetry, inspecting syslogs, and executing traffic reroutes through MCP tools.

Provides read-only, stdio-based MCP tools for inspecting locally captured C/C++ fault artifacts, grouping processes and sessions, querying the evidence store, and resolving explicitly supported RPC/IPC relationships. Access is restricted to a configured artifact root, with observed, static-candidate, and unresolved evidence kept strictly separate.

Monitors MCP protocol traffic across legacy and modern lanes, records usage evidence in a durable SQLite ledger, and recommends when the legacy fallback can safely be removed.

Enables AI assistants to analyze Windows WPR/ETW traces (.etl files) using natural language queries, with features like auto-summary, CPU sampling, DPC/ISR analysis, and symbol resolution.

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

C#/.NET patterns and helpers for MCP tools that unreliable agents cannot misuse: result envelopes, corrective errors, safe defaults, truncation transparency, audit hooks. Builds on the official C# SDK and ships a runnable sample server.

Provides read-only production observability through a small set of tools for health, job status, latest data, approved logs, and deployment metadata, enabling AI planning and review without a production write path.

An advanced system monitoring solution that uses unsupervised machine learning algorithms to detect abnormal resource usage patterns in real-time, with features including anomaly detection, process analysis, and Discord integration.

MCP-native agent evaluation and observability server. Log traces, evaluate output quality with 12 built-in rules (PII detection, prompt injection, cost thresholds), and track agent costs. Real-time dashboard, OTel-compatible spans. Self-hosted, MIT licensed.

Tells an agent what went wrong with its own Ollama calls, in sentences with the fix: lost prompt cache and where the prompt stopped matching, context overflow, a model running partly on CPU, tool schemas crowding the prompt. Also the last turn in numbers and which local models fit in video memory. Local, read-only, nothing leaves the machine.

MCP server that diagnoses Apache Spark job failures and optimizes performance using stack-trace analysis and LLM providers, supporting EMR and local sources.

Production-grade MCP Gateway in Go featuring dynamic OpenAPI tool registration, RBAC governance, in-flight PII/DLP redaction, and structured JSON audit logging.

Enables agents to interact with the Logflare API by writing JavaScript functions that run in a Vercel Sandbox, using three tools: search, execute_read, and execute_write.

Enables AI assistants to search, summarize, and inspect Kibana/OpenSearch Dashboards logs through the user's logged-in browser session, eliminating the need for API keys or service accounts.

An MCP server that exposes a dbt project's run state as tools, enabling AI assistants to answer questions like 'is the warehouse healthy?' or 'what broke and why?' via plain English, using read-only access to dbt artifacts and warehouse data.

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