"MCP Full Stack MVP Development Resources" matching MCP servers:

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

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

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 agents to autonomously investigate deployment health by inspecting Kubernetes resources, comparing live cluster state against Git, and correlating findings with Dynatrace problems.

MCP server for semantic log ingestion, hybrid retrieval, and cleanup, enabling natural-language querying of log files with dense+BM25 retrieval and full provenance.

An instrumented MCP server for debugging lost tool calls in Claude Desktop, using ping, echo, sized_echo, and slow_echo tools to record and analyze the full protocol flow.

MCP server that exposes OSSEC HIDS security monitoring capabilities as tools, resources, and prompts for AI assistants.

Cross-cloud observability for AI agents. Discover resources, correlate logs, and diagnose infrastructure issues across AWS, GCP, Vercel, and Cloudflare — without leaving your editor.

Enables LLMs to analyze and manage DBOS workflows, including introspection, workflow management, and authentication, to help debug applications in development or production.

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.

MCP server for the beacon log analytics platform, exposing beacon's REST API as MCP tools and resources for AI agents to query and analyse AI-assistant usage data.

Gives AI assistants read-only access to a Kubernetes cluster's observability stack — Loki, Prometheus, Tempo, the Kubernetes API — plus AWS telemetry from CloudTrail, Config, ECR, and RDS. 23 tools for querying logs, metrics, traces, Kubernetes events, deployments, and audit history in plain language.

Enables AI assistants to access full Datadog observability, including log search, APM trace filtering, smart sampling, and cross-correlation between logs, traces, and metrics.

An MCP server with bearer token authentication implementing tools, resources, and prompts for a mock developer platform API, supporting both stdio and Streamable HTTP transports.

An MCP server that gives AI agents full visibility and control over your Dagster instance, enabling autonomous monitoring, diagnosis, and remediation of data pipelines.

Enables coding agents to locally investigate and manage error tracking issues, including Laravel error summaries, paginated stack traces, triage, comments, and deletion.

MCP server for integrating self-hosted Sentry with AI assistants, enabling project and issue listing, issue details with stack traces, and event retrieval.

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

Provides AI coding agents with real-time visibility into local development runtime state, enabling them to tail application logs, inspect ports, monitor process metrics, and diagnose network errors.

An MCP server for interacting with Prefect resources, enabling AI assistants to monitor, manage, and debug workflows.