"Enhancing Prompt Engineering with MCP" matching MCP servers:

Enables AI clients to investigate data engineering workflows by exposing tools for job status, logs, schema lookup, read-only SQL, and searching documentation/incidents, along with resources and prompts for ETL failure analysis.

A Model Context Protocol server that provides AI assistants access to AWS CloudWatch Logs, enabling browsing, searching, summarizing, and correlating logs across multiple AWS services.

Enables LLMs to query real job data and summarize backend job failures using MCP tools backed by a SQLite database.

Enables inference engines to match longest common prompt token prefixes via a radix trie, so cached KV-cache blocks are reused instead of re-prefilled. This eliminates redundant prefill computation and lowers time-to-first-token, alongside paged attention allocation, speculative decoding verification, INT8 quantization, and latency telemetry.

A safe, read-only MCP server that gives Codex structured access to engineering operations evidence, with validated queries, secret redaction, and audit logging. Provides a search_logs tool for filtering logs by service, environment, severity, and time range.

Enables real-time data streaming through Server-Sent Events with timestamp broadcasting and server monitoring capabilities. Optimized for deployment on Render.com with health checks and status endpoints.

Provides AI agents with real-time access to live Azure infrastructure, including AKS cluster health, resource management, policy validation, and Terraform analysis through a Model Context Protocol interface.

MCP server for IBM Concert Operate that exposes the full v2 REST API as callable tools, enabling AI assistants to manage alerts, incidents, policies, runbooks, and more.

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 triage SOC alerts while enforcing a trust firewall across retrieval, memory, and privileged actions. It exposes tools for alerts, logs, memory, and alert actions, with defenses that refuse risky operations in the presence of attacker-controllable content.

Provides tools for obtaining system CPU and memory statistics through FastAPI endpoints exposed via MCP.

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.

Enables AI assistants to review workflow status in n8n instances, including active/inactive counts and workflows with recent errors.

Unified MCP safety server that detects prompt injection (75 patterns), scans LLM outputs for leaked secrets/PII, enforces API cost budgets, and creates signed audit trails. Zero ML dependencies, pure Python.

Enables interaction with AWS Fault Injection Service to create, manage, and execute chaos engineering experiments. Operates in read-only mode by default for security, with optional write operations for starting/stopping experiments and managing templates.

Self-hosted Google Search Console MCP server with 20 read-only tools for Google Search Console. Maintained source relocated to get-mcp-ads/google-search-console-mcp-server; npm package remains @getmcpads/google-search-console-mcp-server.

Generates and deploys Cloudera Data Engineering (CDE) Airflow jobs from ODCS data contracts, validating live table data in CDW against schema and data-quality rules without WAP staging.

A Roblox MCP bridge that connects Codex and other MCP clients to a live Roblox client, enabling live inspection, control, and authorized reverse engineering.

A Model Context Protocol server that retrieves and analyzes Sentry.io issues, allowing users to inspect error reports, stacktraces, and debugging information from their Sentry account.

Enables automated access to LoadRunner Cloud APIs for retrieving performance test data, managing projects, and collecting test results. Supports integration with AI clients for building performance engineering workflows and dashboards.