"How to fix SonarQube findings" matching MCP servers:

Radar is an open-source Kubernetes observability and diagnostics MCP server. It exposes cluster health, workload diagnosis, logs, events, topology, audit findings, and remediation actions to AI agents through the Model Context Protocol.

MCP server for AI-assisted trading operations, enabling agents to diagnose and resolve FIX, OMS, and venue incidents through controlled tools and human approval.

A specialized diagnostic framework that enables AI models to self-diagnose and fix MCP-related issues by analyzing logs, validating configurations, testing connections, and implementing solutions.

Seamlessly bring real-time production context—logs, metrics, and traces—into your local environment to auto-fix code faster.

Retrieves captured bug context and evidence for coding agents, enabling progressive disclosure of sessions, manifests, and window correlations to diagnose and fix issues.

Analyzes DevOps findings to automatically recommend and generate AWS Fault Injection Simulator (FIS) experiment templates. It helps teams validate system resilience by mapping reported issues to specific chaos engineering actions across AWS services.

Analyzes how search engines and AI systems discover, crawl, cite, and convert traffic via CLI and MCP tools.

Provides tools for DeepTempo AI SOC including findings and case management, investigation workflow orchestration, action approval workflows, and MITRE ATT&CK layer generation.

Drop-in MCP server that lets Claude inspect, debug, and hot-fix your running Bun process through conversation.

Enables AI agents to query runtime debugging facts (stack traces, logs, function arguments) captured by Syncause, allowing them to fix root causes with evidence instead of guessing.

Enables monitoring and analysis of agent goal achievement and failures across sessions, repos, and tools, with detailed views and tracing.

Enables coding agents to read performance findings from sixty, get detailed evidence for each finding, and close or resolve them with descriptions, while also checking service telemetry and providing installation instructions.

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

Provides read-only access to OpenFolio data, enabling catalog, holdings, grid, and log queries without placing orders.

MCP server for AWS infrastructure analysis. Connects to DynamoDB, Lambda, SQS, SNS, Secrets Manager, EventBridge, RDS, PostgreSQL, MongoDB, and CloudWatch — surfaces missing indexes, queue DLQs, Lambda config issues, IaC drift, and security findings for Claude Code and Cursor.

MCP server for Drumbeats monitoring. Enables creating monitors, triaging incidents, and running HTTP/SSL/DNS checks using natural language from any AI client.

Read-only PostgreSQL performance auditing via MCP. Collects metrics from PostgreSQL system views, applies deterministic checks for index, query, vacuum, configuration, and connection issues, and returns structured findings for MCP clients.

An MCP server exposing 72 tools across 26 homelab services, enabling LLMs to monitor and manage infrastructure, media, storage, and networking with a single endpoint.

iOS leak hunting and performance investigation. Reads .memgraph and .trace files, classifies retain cycles against a 34-pattern catalog with Swift fix templates, bridges to source via SourceKit-LSP. 28 MCP tools, 34 catalog resources, 5 investigation prompts.

eBPF-based GPU causal observability agent with MCP server. Traces CUDA Runtime and Driver APIs via kernel uprobes and host events via tracepoints to build causal chains explaining GPU latency. 7 tools: get_check, get_trace_stats, get_causal_chains, get_stacks, run_demo, get_test_report, run_sql. Telegraphic compression reduces token usage ~60%. Supports stdio and HTTPS (TLS 1.3) transport.