"Database Query and Information Retrieval" matching MCP servers:

Enables AI agents to read and optionally write to PostgreSQL databases through a multi-project setup with schema inspection, query execution, and performance analysis tools.

MCP server for querying and analyzing TensorBoard event files, enabling AI agents to extract scalar data, statistics, and correlations without a running TensorBoard server.

Enables post-hoc auditing of an agent's retrieval supply chain by recording digest-only provenance from source through chunk, transformation, context and decision, then reporting influence rankings with an honest unexplained residual, lineage traces, advisory source trust and retirement recommendations, and retrieval schema drift. It never performs retrieval, ranks documents at query time, or blocks decisions.

HandaaS的MCP服务器，提供全域资讯搜索、企业新闻、行业资讯、主题跟踪和企业动态监控能力，帮助用户开展行业研究和舆情分析。

Enables read-only querying of Azure Log Analytics and Azure Resource Graph through MCP, supporting KQL queries, workspace discovery, and resource inventory exploration with Azure RBAC authentication.

Enables AI clients to safely query PostgreSQL or SQLite databases read-only through AST-validated guardrails, schema introspection, and statistical table profiling. It returns results as Markdown tables, JSON audit reports, and database health checks.

MCP server for unified SQL database access, supporting multiple databases with schema discovery, caching, and safety controls.

Provides comprehensive system diagnostics and hardware analysis through 10 specialized tools for troubleshooting and environment monitoring. Offers targeted information gathering for CPU, memory, network, storage, processes, and security analysis across Windows, macOS, and Linux platforms.

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 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.

Exposes a metrics query API to AI assistants, allowing them to issue queries and interact with the server's tools such as ping.

Provides tools to monitor host system health including CPU load, disk usage, and network status while enabling file system management tasks like searching and moving files. It includes built-in safety guards to prevent operations on critical system directories.

Enables named, authenticated callers to run read-only introspection of a Google Cloud project and to read and write per-tenant notes that stay isolated between callers. Every request is scope-checked against a reviewed policy, rate-limited per caller, and audited without ever logging argument values.

A FastAPI-based server that enables executing SQL queries, managing database connections, and retrieving analytics reports through MCP-integrated endpoints. It allows users to interact with database schemas, performance metrics, and access logs using structured queries.

Enables querying and searching logs from Kibana (ELK stack) via MCP, with support for project-based data views, trace ID correlation, and log expansion.

Logs LLM interactions to local CSV or Markdown files with automatic categorization for detailed tracking. It provides an interactive HTML dashboard to visualize query volume, model usage, and category distribution.

Exposes a synthetic issue tracker and pipeline warehouse as callable tools so an agent can answer operational questions about tickets, pipeline health, runs, incidents, and governed metrics with every claim cited to the exact tool call it came from. All writes are proposal-only, requiring human approval through a gated apply path that logs each step for audit.

Enables users to generate and execute InfluxDB queries using natural language commands in Korean. Supports querying metrics like CPU usage, memory status, and system monitoring data through conversational interface.

A comprehensive MCP server providing advanced Redmine project analytics, web automation via Playwright, and iTunes music integration. It enables detailed tracking of sprint metrics, bug counts, and team performance through a token-optimized tool architecture.

Enables AI agents and users to manage workspace files, monitor system metrics, take persistent notes, and retrieve weather data via MCP tools and resources.