"Answer Engine Optimization (AEO) Audit Guide" matching MCP servers:

Enables AI assistants to evaluate business processes for automation by collecting discovery answers, calculating labor costs, scoring automation potential, and saving completed audits to a local SQLite database.

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

Enables AI tools to understand a database, inspect schema, and run safe SELECT queries with SQL guardrails, plus optional codebase reading.

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 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.

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.

A comprehensive Model Context Protocol server that analyzes AWS costs and provides optimization recommendations by integrating with services like Cost Explorer, Cost Optimization Hub, and Trusted Advisor.

Enables AI chatbots to look up standardized Korean food composition data, retrieve nutrient values, and check or grade nutrition answers against the National Standard Food Composition DB 10.4 with source attribution.

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

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 conversational spatial SQL queries in plain English, turning natural language questions into validated PostGIS operations and rendering results as GeoJSON on an interactive map.

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.

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.

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.

DBeast MCP is a robust, security-first Model Context Protocol server designed to empower AI coding assistants (like Claude Desktop) with deep PostgreSQL database insights. Instead of just running basic SQL queries, DBeast equips your AI agent with tools to inspect active locks, audit slow queries, analyze table schemas, and safely generate index recommendations in real-time. Built specifically for

An MCP server that exposes a dbt project's run state as tools, enabling AI assistants to answer questions like 'is the warehouse healthy?' or 'what broke and why?' via plain English, using read-only access to dbt artifacts and warehouse data.