"Enhancing Prompt Engineering with MCP" matching MCP servers:

Provides a local MCP interface to query captured, PII-scrubbed prompt telemetry from coding agents and browser chats, enabling time summaries, prompt search, and activity analysis without data leaving the machine.

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.

An MCP server that enables conversational interaction with Wazuh SIEM, allowing users to investigate alerts, hunt threats, tune false positives, edit rules, and run security actions via natural language.

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.

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.

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.

Provides an MCP-native operational interface for diagnostics, explainability, regression checks, and operational memory on data-system internals like PostgreSQL and Databricks toy engines.

Enables natural language analysis of network packet captures, including protocol detection, flow analysis, and security threat identification, integrated with AI assistants.

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.

The policy enforcement plane for MCP: deterministic admission and egress policy, attributable audit, and SIEM export for your MCP server fleet. Self-hosted and MIT licensed.

Enables AI agents to interact with Freeplay, an ops platform for AI engineering teams, to analyze production logs, identify quality issues, iterate on prompts and agents using real data, and run experiments before deploying.

An MCP server that enables AI agents to safely operate multi-cluster Kubernetes fleets through an Open Cluster Management hub, with policy enforcement, human approval, and audit tracing.

Estimates the environmental footprint of your AI use — energy (kWh), miles driven, water used for cooling, and CO₂ — plus a prompt-efficiency score, working with any AI client by measuring token usage.

Enables LLM clients to access DevSecOps tooling such as CI/CD pipeline status, vulnerability triage, log search, and dependency scanning through MCP, turning AI copilots into security-aware engineering partners.

Enables chaos engineering on Kubernetes clusters by providing tools to inject faults like network delays, pod kills, and HTTP delays, along with cluster inspection and chaos lifecycle management.

Connect engineering metrics, DORA performance, deploy risk scoring, and PR health to any AI assistant. Score PRs for deployment risk using a 36-signal model, query team health, incidents, coverage, and more.

Enables transparent security for any MCP server by intercepting tool calls, blocking prompt injection attempts, masking PII in responses, and writing immutable audit logs.

Enables interaction with Sentry's error tracking and monitoring tools through a unified API, allowing natural language access to Sentry services.

Enables Windows event log forensics by wrapping Hayabusa, offering EVTX scanning, Sigma rule exploration, ATT&CK coverage analysis, and detection engineering resources.