"How to Build a Knowledge Base" matching MCP servers:

Enables diagnosing web hosting and server issues by running live HTTP, SSL, DNS, and security-header checks alongside a searchable troubleshooting knowledge base.

Enables AI agents to build, test, debug, and interact with Kotlin Multiplatform Mobile (Android/iOS) applications through automated build pipelines, UI automation, crash analysis, and app state inspection.

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

Enables AI agents to perform observability analysis across Prometheus-compatible metrics and logs without prior vendor knowledge, including signal discovery, entity topology resolution, root-cause analysis, correlation, and capacity forecasting through natural-language anchors.

Ships only the MCP server, not the recorder. Recording works by wrapping a process on the host — a local proxy, a PATH shim, a shadow git index. None of that survives a container boundary, so orca record inside here would watch an empty namespace. What does travel is the read side: the six MCP tools serve runs that already exist on disk, so a client mounts its .orca directory and r

Enables AI assistants to monitor and analyze industrial process data from DCS/SCADA systems via MCP protocol, with domain expert knowledge for anomaly detection and recommendations.

Enables grading a website's security headers with per-gap fixes and a README badge, and analyzing logs, code, configs or suspicious messages to determine what happened, how severe it is, and what to fix first. Requests are masked for sensitive data and automatically retried across multiple AI providers when one refuses, subject to a defensive-use-only policy.

An MCP-native enterprise operations platform that unifies team management, product catalog, order processing, knowledge base, location intelligence, analytics, and DevOps monitoring into a single server accessible from any MCP-compatible AI agent.

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

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

A modular Retrieval-Augmented Generation (RAG) framework that provides hybrid search and knowledge retrieval capabilities via the Model Context Protocol. It enables users to integrate document-based knowledge into LLM workflows with support for dense/sparse retrieval, reranking, and observability.

A local MCP server that gives LLMs long-term memory by indexing code, infrastructure, logs, and docs into a queryable graph. It enables semantic and structural search, evidence-backed reasoning, and tracked plans that persist across sessions and teams.

Enables read-only querying and analysis of Kibana logs through a logged-in sid Cookie, including keyword/time/index searches, traceId lookups, surrounding log context, and aggregations by service, level, or host. It also validates Kibana connection status and redacts sensitive fields such as cookies, tokens, and passwords.

Enables AI agents to query and analyze Graylog logs through MCP tools for search, aggregation, stream listing, and saved queries, with optional OpenAI-powered natural language orchestration and audit logging.

Enables autonomous infrastructure health management by exposing tools for retrieving system logs, querying a knowledge base, executing SQL analytics, and simulating system commands, all integrated into an AI-driven incident response workflow.

Enables MCP-compatible clients to inspect the local machine's CPU, memory, and disk information through tools, a structured resource, and an upgrade-assessment prompt.

Enables querying and managing AI logs through tools like listing logs, retrieving jobs, and performing AI-powered chat queries. Also provides access to gateway security reports and guardrail testing.

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

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.