"Databases or database systems written in Python, like Postgres" matching MCP servers:

A Postgres MCP server with index tuning, explain plans, health checks, and safe sql execution.

Enables AI agents to interact with PostgreSQL databases through schema intelligence, query execution, and DBA tooling including index analysis and health monitoring. Features configurable access levels and audit logging for secure database operations.

Governed PostgreSQL DBA operations — slow-query, bloat, and blocking-lock RCA, index management, vacuum/analyze, and replication lag, with unbypassable audit logging (MCP + CLI), budget/runaway guards, dry-run, and undo/rollback.

Enables AI agents to analyze, optimize, and safely interact with PostgreSQL databases, including health checks, index recommendations, query planning, and SQL execution with read-only and production protection modes.

A Postgres MCP server with index tuning, explain plans, health checks, and safe SQL execution.

MCP server for PostgreSQL that enables schema exploration, safe SQL execution, EXPLAIN analysis, health checks, and index recommendations across multiple databases.

A Model Context Protocol server that provides secure database access to PostgreSQL through Kysely ORM, enabling natural language interaction with PostgreSQL databases. It offers 40+ MCP tools for querying, schema inspection, diagnostics, and Java backend monitoring.

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

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.

Enables AI assistants to manage, monitor, and optimize PostgreSQL databases with over 200 specialized tools for operations, security, performance tuning, and diagnostics.

An open-source MCP server for PostgreSQL that provides database health analysis, index tuning, query plan optimization, and safe SQL execution, suitable for both development and production environments.

A Model Context Protocol (MCP) server for comprehensive monitoring and observability of systems using Langfuse.

Enables natural language queries for device support, including resolving device references, retrieving device details, historical metrics, and checking provisioning status. Maintains conversation context for multi-turn interactions.

An MCP server for Microsoft SQL Server integration that enables users to query, monitor, and analyze databases directly through Claude. It supports schema exploration, performance analysis, and optional write operations via natural language commands.

Enables real-time system monitoring and automation through MCP protocol with SSE transport, integrating with n8n workflows to check system health, query logs, and retrieve metrics from ABC system APIs. Supports natural language queries in Vietnamese and English for seamless system administration.

Enables AI assistants to query and analyze AI agent sessions from observability providers like Shepherd (AIOBS) and Langfuse, allowing users to debug agent runs, compare sessions, track performance, and analyze LLM usage patterns.

Enables analysis of AI agent traces to detect and fix failures using heuristic detectors, with no LLM calls required.

Fast and minimal Sentry MCP server written in Rust

An MCP server that emits OpenTelemetry traces, metrics, and logs to OTLP endpoints in various formats. It includes tool-mimicry profiles to generate realistic traffic resembling common tools like nginx, postgres, and AWS Lambda for testing and demonstration purposes.

Transparent MCP proxy with OpenTelemetry tracing. Wrap any MCP server, persist traces to SQLite · Postgres · MySQL. No code changes needed.