"Setting up an MCP server in Kubernetes" matching MCP servers:

A modular monolith MCP server connecting multiple providers (Redash, PostgreSQL, GitHub) with unified permission, security, and auditing, enabling secure data access and tool execution.

An unofficial MCP server for Percona Everest that enables AI-powered interaction with database clusters, including listing, retrieving details, credentials, and components.

LLM-assisted, safety-gated Postgres migrations exposed as an MCP server, using a deterministic rule engine over Postgres's own parser AST for safety enforcement, with two-phase approval and append-only audit ledger.

Enables MCP-capable agents to operate PostgreSQL and PgBouncer clusters on Kubernetes—covering discovery, pooling, tuning, backups/PITR, DR, and lifecycle—with safe-by-default read-only mode and granular opt-in security controls.

Enables CRUD operations on Supabase structured data through PostgREST tools without exposing arbitrary SQL. Access can be constrained to specific tables via an allowed-tables setting.

Provides MCP tools for setting up and managing Hephaestus development environment with Docker containers, including starting/stopping services, initializing databases, and troubleshooting.

Enables AI agents to consult and update CRM contacts, look up customers by phone, CPF, or installation code in an analytical base, and publish HTML reports and presentations to stable public links. It provides typed contracts, Bearer auth, rate limiting, and an offline demo mode behind a single MCP endpoint.

Exposes a small in-memory directory of ten people over streamable HTTP, letting an AI agent list every entry or look someone up by name or email.

Enables LLMs to manage PostgreSQL clusters in Kubernetes using the CloudNativePG operator. Supports creating, scaling, monitoring clusters and retrieving detailed status information through natural language commands.

Enables an event-driven operations agent to query internal SQL, GitHub, Slack, Jira, documentation, and Kubernetes telemetry through 28 RBAC-gated MCP tools, with shared memory for playbook retrieval and incident workflows.

A FastMCP server for querying, searching, and analyzing Kubernetes resources archived off-cluster with KubeArchive.

Enables AI agents to query and act on SAP CAP travel domain data (travels, bookings, customers, agencies) via MCP tools, including unbound actions and security-aware access.

Provides read-only access to Velero backup and schedule resources in Kubernetes clusters, enabling AI agents to inspect backups, schedules, and generate Velero YAML manifests safely without write permissions.

Enables integration with financial transaction data through REST APIs, PostgreSQL databases, and document storage systems. Demonstrates agentic AI capabilities by connecting to Alpha Vantage API and managing financial data through natural language interactions.

Enables natural-language sales queries against a SQLite database, generating and executing read-only SQL through a secure MCP server with table listing, schema description, and query execution.

An MCP server that provides targeted PostgreSQL schema access to AI agents, retrieving only relevant tables for a question and enforcing read-only access through multiple layers.

An MCP server that provides a USDA-accurate food database with deterministic macro math, enabling tools like list_foods, get_food, calculate_macros, filter_by_diet, build_meal, and list_available_tags. It allows Claude to look up nutrition facts and solve for exact macro targets offline, without AI or network.

SchemaBrain is an MCP server that sits between AI agents (Claude, Cursor, Windsurf) and your SQL database as a read-only trust + intelligence layer. The agent never writes SQL — 12 tools compile it from definitions you control, PII and secret categories are refused before the query runs, and every call lands in a tamper-evident (SHA-256-chained) audit log. Postgres today.

Give your AI agent the entire China A-share market: 55 datasets of prices, financials, capital flows, corporate events and futures/options, stored locally and queryable with read-only SQL. Built point-in-time with delisted stocks kept, so backtests don't lie — no account, no API key.

Enables AI agents to safely explore and query a SQLite database in read-only mode, allowing them to inspect schema and run analytical SQL queries without risking data modification.

A Model Context Protocol server that gives AI agents real-time access to Excel workbooks in OneDrive, answering natural-language questions with live data. It caches only sheet structure, never cell values, and fetches current ranges via Microsoft Graph for each query.

An MCP server that gives models semantic context about a data warehouse, including table meaning, units, lineage, and health, to reduce guessing.

Enables AI agents to answer analytical questions about an online store's SQLite database through specialized read-only tools, without any risk of modifying the underlying data.

Lets an agent query JSON files too large for its context: JSONPath with aggregation pipes, schema, field profiles, samples, identity-keyed diff, CSV and spreadsheet export, and checks that gate a file. Int64 IDs and decimals keep their exact digits, and zstd, Base64-Zstd and PostgreSQL bytea payloads open directly.

Self-hosted governance layer between an AI assistant and your data: allow/deny policy, deterministic PII masking, row caps, and a hash-chained audit log with an Ed25519-signed receipt for every access, verifiable offline.

Read-only MCP server that exposes your local Notion backups to AI agents — query databases, read pages, search a backed-up workspace. Offline by default: no LLM calls, no telemetry, no cloud.

Lets AI agents estimate the cost and result size of BigQuery and Snowflake queries before they run, then execute them only within per-call byte, row, and dollar bounds. Estimates are labeled with an accuracy tier so agents never over-trust an approximate figure.

An MCP server that gives AI agents access to configured databases (PostgreSQL, MySQL, Redshift, SQL Server) with SSH/AWS SSM tunnels, pluggable secret providers, and strict per-instance isolation.

Enables natural-language querying and analysis of an e-commerce SQLite database via MCP, with read-only SQL execution, table inspection, and AI-generated answers.

Provides local MCP tools to query your own Xiaomi Mi Fitness health data (sleep, workouts, heart rate, etc.) stored in a local SQLite database, enabling AI assistants to access personal health records without exposing credentials.