"Retrieving Markdown Files from a Database" matching MCP servers:

MCP server for multiple databases (PostgreSQL, MySQL, MariaDB, SQLite, MongoDB, Redis) with tools for schema inspection, querying, performance diagnostics, and safe write operations, featuring access modes, PII masking, and audit logging.

An MCP server that analyzes SQL schemas, generates realistic test data, benchmarks queries, and provides optimization recommendations to improve database performance.

An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.

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

Enables LLMs to query and analyze logs from SEQ structured logging server with capabilities for searching events, retrieving event details, analyzing log patterns, and accessing saved searches.

A log analysis MCP server that enables tailing, searching, filtering, and summarizing logs from local files and Docker containers.

Enables querying and formatting Loki logs from Grafana via the Model Context Protocol. It supports LogQL queries, label retrieval, and provides results in text, JSON, or markdown formats.

Read-only MCP server for TrueNAS Scale debugging, providing k3s tools for kubectl operations and whitelisted midclt calls for system info, apps, and pools.

Enables AI agents to interact with the Honeybadger error monitoring service to list, filter, and analyze fault data. It provides tools for fetching error lists and retrieving detailed fault information from Honeybadger projects.

Enables LLMs to analyze logs by extracting patterns, redacting secrets, and providing token-efficient summaries from files, Docker containers, or journald.

Exposes configured log files as MCP tools, enabling agents to list, query, and follow logs from local and SSH sources.

Enables on-call database diagnostics: it classifies load pressure, traces root causes with hypothesis-evidence-confidence, detects blocking and lock chains, scores health across a dimension tree, and renders deliverable incident reports. Works from symptom text alone with no database connection or history required (Tier0), escalating to snapshot-based and trend-based analysis as observations accumulate.

A template for deploying MCP servers as Cloudflare Workers with integrated LogPush and R2 storage for detailed execution logging. It enables remote tool execution and provides utilities for retrieving logs directly from Cloudflare R2 buckets.

Enables read-only access to JavaMelody monitoring data from one or more Java web applications, covering HTTP/SQL/Spring counters, JVM and thread snapshots, and database reports. Users can query several configured microservices from a single server process and inspect what is slow or failing without opening the JavaMelody dashboard.

Enables AI agents to query Microsoft Copilot Studio telemetry and governance data in plain English, pulling from multiple Azure and M365 APIs into a local SQLite database.

Enables AI assistants to query and fetch error and performance monitoring data from AppSignal through the Model Context Protocol. Supports searching and retrieving detailed information about application errors and performance samples with flexible filtering options.

Enables AI agents to autonomously investigate simulated production incidents by checking live service health, logs, deployments, and database status while retrieving relevant historical postmortems and runbooks to propose evidence-backed root causes.

Enables AI agents to query and diagnose IP-MPLS network operations by retrieving tickets, device configs, topology, and logs from PostgreSQL, Neo4j, and OpenSearch via MCP.

An MCP server for retrieving and filtering logs from Mezmo with a quota-conscious design and intelligent defaults. It enables users to discover and query logs by application, level, and custom time ranges to streamline debugging while minimizing API usage.

Enables querying and analyzing Falco security events from Falcosidekick UI through MCP tools. Supports filtering events by time windows and retrieving full event details for security monitoring and incident investigation.

Read-only MCP server for querying AI usage metrics (exact tokens, cost, latency, errors, productivity) from a local SQLite database, enabling charts and analysis in Claude Code and Cursor.

MCP server to start, monitor, search, and detect errors in logs from any project, even those without log files.

A Python-based MCP server that analyzes PostgreSQL query plans, suggests indexes, and checks pagination safety to help optimize database performance.

An MCP server for querying Grafana Loki directly with a discovery-first workflow — labels, values, series, and LogQL queries without requiring Grafana.

Enables querying logs and metrics with plain SQL from any MCP client via pooml's read-only query API.

An MCP server that records agent execution metrics and exposes a Context Window Explorer to visualize exactly what entered the model's context window across sessions, tokens, and tool calls.

Provides cryptographically signed, tamper-evident compute usage receipts via a Model Context Protocol server, exposing tools to record usage, verify receipts, list the ledger, and verify ledger integrity without requiring any account, API key, or single cloud provider.

Enables classification of GPU workloads as training, inference, or idle from telemetry data, with tools for one-shot classification, benchmarking, and audit log verification.

Provides MCP tools to create and query SigNoz trace funnels, enabling agents to measure their own step conversion rates from within the agent loop.

Model Context Protocol (MCP) server for debugging, analyzing, and diagnosing Kubernetes clusters directly from AI agents.