"Unreal Engine" matching MCP servers:

Enables AI assistants to query and manage a local Engine DJ library on macOS, including searching tracks by BPM, key, genre, or comments, auditing duplicates and missing files, reading cues and beatgrids, and building playlists or fixing tags when write access is enabled.

A provably read-only SQL layer for AI agents (MCP) and weekly reports — over the database behind an ERP (Logo Tiger, Netsis, Mikro). Statement-checking guard, measured against 28 attacks.

Enables AI agents to safely operate on PostgreSQL data through typed MCP tools with per-identity RBAC, guardrails, and immutable audit logging.

Enables natural-language-driven analytics over CSV/Parquet or built-in data by decomposing questions into analytical tasks, running them via deterministic DuckDB and SciPy tools, and publishing only claims verified against the underlying rows.

Enables unified access to SQL, semantic vector search, and columnar analytics through a single MCP interface.

Generates cryptographically secure, compliant UUIDs (v4, v5, v7) to prevent AI-hallucinated identifiers that would cause database collisions.

An MCP server that exposes personal financial data — transaction ledger, portfolio holdings, live/historical market prices, and quantitative risk metrics — as standardized tools, resources, and prompts, enabling natural language reasoning over real computed numbers.

Enables local AI-powered retail location intelligence by exposing database schema and spatial query tools to LLMs. It supports executing validated SQL, retrieving example spatial analyses, and generating strategic business insights from retail siting data.

Enables agents to perform controlled enterprise data queries through semantic intent, with runtime validation of statistics, filters, granularity, permissions, and physical bindings. Exposes tools like semantic_query for safe, fail-closed access to data horizons and capabilities.

Lets an LLM explore a cryptic legacy ERP schema in plain language through a semantic layer (table listing, column descriptions, published dictionary) and run single read-only SELECT queries that return capped results. Enforces safety at the database engine level: only reads are authorized, sensitive columns are masked to NULL, queries are aborted after a few seconds, and every call is written to an append-only audit log.

A read-only MCP server that provides tools to read, list, and inspect secrets from HashiCorp Vault's KV secrets engine (versions 1 and 2) using a Vault token.

An MCP server for chDB, the in-process SQL OLAP engine powered by ClickHouse. Lets agents query Parquet, CSV, JSON, and pandas DataFrames with one tool — no separate server, no Docker.

Natural language to SQL engine with multi-connector support (PostgreSQL, MySQL, Snowflake, BigQuery, DuckDB), document QA, semantic caching, and self-hosted MCP server.

Enables AI agents to inspect real databases through MCP with tools for listing tables, describing schemas, sampling rows, running queries, and explaining execution plans, all with engine-enforced read-only access to SQLite and MySQL.

Data-first MCP server for reading and writing spreadsheets (.xlsx, .csv, .ods) - cell-level ops + DuckDB SQL engine.

A standalone API built on Model Context Protocol that enables AI agents to directly and securely communicate with the ZomPP legal engine for managing reports and diagnosing orchestration.

Enables LLM assistants such as Claude Desktop and Cursor to discover database schemas and run strictly read-only SELECT/EXPLAIN queries against local database files. Includes parser- and engine-level blocking of mutations, result truncation to prevent context overflow, and structured error responses that help models self-correct.

A Model Context Protocol server that enables large language models to access database metadata and perform cross-engine data querying across diverse database ecosystems.

A minimal MCP server that provides a persistent DuckDB SQL engine to AI assistants, enabling natural-language querying of CSVs, Parquet, and cloud data with 12 tools and optional read-only mode.

Enables AI assistants to query Apache Iceberg tables on S3 via AWS Glue Data Catalog using DuckDB as the embedded query engine, supporting columnar Arrow reads with no data movement.