"Retrieving information from document directory with search and memory capabilities" matching MCP servers:

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

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.

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

Enables ingestion and full-text search of Windows application logs via MCP tools. Supports dual-backend indexing with Elasticsearch and SQLite for fast retrieval.

MCP server for read-only investigation of Aliyun SLS logs fixed to cn-beijing/taient-rpa/node-rpa. Exposes search_logs, get_context_logs, and check_connection tools with a guided investigation skill.

A production-oriented reliability, benchmarking, and evaluation system that layers multi-version protocol negotiation, adaptive streaming, connection pooling, and resilience onto an MCP agent runtime.

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

Read-only MCP server for searching and aggregating logs from VMware Aria Operations for Logs (formerly vRealize Log Insight). Enables querying log events, aggregating with spike detection, and retrieving alert information.

A Linux system monitoring MCP server that provides real-time information on CPU, memory, disk, network, processes, Docker, security, and more via MCP tools.

Provides system hardware information (CPU, memory, storage, etc.) and system status (OS, network, resource usage) via MCP tools.

A lightweight server that provides real-time system information including CPU, memory, disk, and GPU statistics for monitoring and diagnostic purposes.

A Model Context Protocol server that enables retrieving and analyzing Sentry issues, including stacktraces and debugging information.

A JVM monitoring and control platform server based on Arthas that provides a Python interface for monitoring and analyzing Java processes with capabilities for thread analysis, memory monitoring, and performance diagnostics.

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.

Enables read-only observability of Windows systems, exposing CPU, memory, storage, service, and health information through Model Context Protocol tools.

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 AI assistants to retrieve and analyze Sentry issues, including error reports, stacktraces, and debugging information from Sentry.io.

Enables troubleshooting of LDAP directory services through natural language queries, providing health diagnostics, replication status, performance metrics, log analysis, and configuration comparisons across multiple servers.

Enables log analysis through MCP tools for searching logs, retrieving error contexts, and summarizing incidents with self-verified root-cause hypotheses.

Securely integrates Wazuh security data with LLMs (such as Claude Desktop) by retrieving alerts from Elasticsearch indices and transforming them into MCP-compliant format, enabling real-time security context in LLM applications.