"Kyverno policy examples and documentation" matching MCP servers:

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 preprocess, analyze, and visualize CSV data through comprehensive tools for data manipulation, statistical analysis, and graph generation.

This server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.

Exposes local DuckDB pizza sales data as MCP tools for querying store-level and total sales metrics via natural language, enabling local LLMs to perform real-time analytical queries.

Enables AI to interact with Microsoft Access (.mdb, .accdb) and SQLite 3 databases, including read-only support for Access 97 databases. Supports executing SQL queries, importing/export data from CSV and Excel files, and storing notes about database files.

Provides stock market data and computes technical indicators like EMA, MACD, and RSI across multiple timeframes using the LongPort API and TA-Lib. It enables users to perform detailed financial analysis and multi-timeframe market reviews through standard MCP tools.

Enables schema-aware exploration of JSON data by uploading samples, flattening nested structures, and using heuristic search with token overlap and fuzzy matching to find field paths for target names, accelerating ETL and API onboarding workflows.

Provides AI assistants with access to Vega-Lite documentation, visualization examples, and specification validation tools. Enables searching docs, retrieving examples by category, validating JSON specs, and accessing schema information for creating data visualizations.

Ripplecheck is a counterfactual schema migration compiler powered by the DataHub MCP Server. Paste breaking warehouse DDL and it projects the metadata graph, proves a bounded release policy, routes an executable migration DAG to owners, writes a hash-sealed decision capsule back to DataHub, and generates a merge-ready PR evidence pack.

Enables policy-bound, one-way synchronization of course content between Moodle sites, with capability-based provider selection, explicit approval workflows, and durable job state.

Provides a secure, policy-driven read-only gateway that exposes multiple databases to AI tools via MCP, with governed select, search, and aggregate operations and no free-form SQL.

Enables agents to perform deterministic data intake pipelines for FOIA and public comments, with medallion warehouse, PII policy enforcement, and verified insights.

Enables AI agents and MCP hosts to query Trino while carrying each end user's verified OIDC identity, so row filters, column masks, and catalog scope are enforced by the existing policy engine rather than a shared service account. Queries are read-only by construction, with quotas, revocation, and audit logging.

Provides deterministic tools for understanding, transforming, and verifying structured data via MCP, enabling rule inference from examples and verification of transformed records.

A governance proxy for the DataHub MCP Server that enforces catalog metadata as policy, providing allow, redact, review, and deny outcomes for agent tool calls, and writing agent actions back into DataHub.

Enables AI assistants to interact with Eclipse Dataspace Components (EDC) connectors for dataspace operations including asset, policy, contract, catalog, negotiation, and data transfer management.

Generates complete PyAirbyte data pipeline code and setup instructions for moving data between 600+ Airbyte source and destination connectors or to Pandas DataFrames, using AI-powered context-aware guidance based on connector documentation.

Generates CanvasXpress data visualization JSON configurations from natural language descriptions using RAG with 132 few-shot examples, achieving 93% exact match accuracy for creating charts and plots.

Exposes nine governed analytics tools — attrition, headcount, tenure, salary, promotion, and more — plus a restricted read-only SQL execution path, so an HR analyst's plain-English question resolves to a versioned, reproducible method instead of free-form LLM-written SQL. Tool selection is driven by the LLM, while role-based access control, PII screening, SQL guards, result validation, and audit logging keep every answer within policy.

Enables users to query and manage Cloudera Lakehouse Optimizer resources, including Iceberg table statistics, policies, namespaces, and optimization tasks, with guarded write tools for policy creation, table association, and maintenance operations.