"Blender Scene Generation and Importing into Unreal Engine" matching MCP servers:

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

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.

Search the fastest-growing US horse boarding directory: 6,000 facilities and 3,800 trainers across 48 states, plus boarding price data by state.

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 AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

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 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.

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.

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 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.

An MCP server that gives LLM clients access to a SQL Server database and the local filesystem, including file operations and image handling.

Enables AI interaction with Microsoft Access and SQLite databases to perform SQL queries, updates, and data management. It supports importing and exporting data via CSV and Excel files and includes tools for managing human-readable notes about database files.

MCP server that enables AI agents to interact with Spica servers, managing databases, serverless functions, storage, authentication, auditing, debugging, and version control.

Provides read-only access to Microsoft SQL Server databases using Windows Authentication, enabling AI assistants to safely explore schemas and query data with built-in security controls.

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 assistants to perform complete CRUD operations on Airtable bases, tables, records, fields, and comments, with batch processing and file attachment support, plus enterprise-grade reliability features.

Enables querying sales data, identifying out-of-stock products, viewing top sellers, and receiving restock suggestions through natural language.

A FastMCP-based server designed for the banking and fintech domains, providing tools for database queries, Git operations, and deployment management. It features a modular architecture with reusable prompt templates and integrated security practices for sensitive data handling.