"How to work with a vector 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.

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.

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.

Fetches Langfuse observability traces directly into a VS Code coding agent's context, enabling querying and viewing trace data through natural language.

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

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

A Claude Code MCP server that connects to Laravel Clockwork to provide insights into application performance, database queries, errors, and request flow.

MCP server for safely exposing SQL Server database capabilities to LLM clients, with read-only mode, security features, and observability.

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

Enables AI agents to query a private MySQL database through a self-maintained SSH tunnel while enforcing read-only SQL by default, with optional opt-in server and Docker operations.

A Model Context Protocol server that provides access to Observe API functionality, enabling LLMs to execute OPAL queries, manage datasets/monitors, and leverage vector search for documentation and troubleshooting runbooks.

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

A production-ready MCP server for SQL Server monitoring, diagnostics, and database operations, with native connectivity, session management, deadlock and blocking analysis, and health checks.

Enables assistants to securely work on a Chest via personal access token: reading tool logs, builds, and databases, editing rows and variables, and installing or linking tools, with every write requiring a dry run and human confirmation.

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.