"Semantic layer for SQL query execution with dimensions and measures" matching MCP servers:

A local MCP server for secure database querying from Claude Code, with Apple Keychain credential storage, permission-based access control, and audit logging.

Implements a secure MCP server with API Key and JWT authentication, providing tools like echo, login, secure_action, and admin_action. Includes MCP Inspector integration for testing and debugging.

MCP server that scans PyPI packages and GitHub repos for security vulnerabilities, dangerous patterns, and prompt injection vectors, providing trust scores (0-10) and side-by-side comparisons.

Provides cryptographic governance receipts for AI agents, enabling pre-execution evaluation and signed verdicts (EXECUTE/BLOCK/REVIEW/SHADOW) with offline-verifiable audit trails.

Local MCP server for private, consent-based speaker identification and attribution, with per-language voiceprints and calibrated match thresholds. It lets AI assistants know who is speaking in a room or transcript without cloud services.

MCP server for connecting to SQL Server in readonly mode. Allows any MCP client to explore the schema and run SELECT queries against a SQL Server database.

An MCP server that lets Claude query a mock business SQL database in plain language through read-only tools, with server-side guardrails that enforce SELECT-only queries and block access to sensitive payment data.

Enables secure database operations on SQL Server instances through a three-tier safety system, supporting schema exploration, query execution, performance analysis, and data export with configurable security levels from read-only to full development access.

A governed SQL gateway for untrusted AI agents, providing controlled access to PostgreSQL, MySQL, and OceanBase with RBAC, field ACLs, row policies, and cost controls.

Enables assistants to inspect schemas and run bounded, read-only SQL queries over synthetic retail data with database-enforced guardrails, resource limits, and blocked write attempts.

Enables LLMs to propose UPDATE/DELETE SQL that is run in a transaction, measured, and rolled back, requiring human approval before applying to prevent unauthorized changes.

Validates SQL queries via AST parsing, ensuring they are single read-only SELECTs on allowed tables with enforced LIMITs, and masks PII columns based on user roles. Provides a tamper-evident audit log and runs fully offline.

C# SQL Agent MCP server featuring raw SQL input, strict AST validation, and an embedded Admin UI. Eliminates LLM hallucinations and security risks across 6 major databases.

A wrapper for mcp-remote that provides secure authentication for protected MCP servers using Adobe IMS or Okta OAuth flows. It features automated token management, validation, and background refreshing for seamless access to remote resources.

Enables AI agents to safely query and explore SQLite databases through read-only, guard-protected tools that block writes, sensitive table access, and runaway queries.

Enables AI assistants to safely run read-only SQL against SQLite databases through whitelist-validated queries, capped result sets, and confined file paths. It also exposes schema inspection so models can discover tables and columns before querying.

Enables read-only querying and diagnostics for dual SQL Server 2019 instances with rate limiting and security controls, accessible via MCP tools over HTTP.

Enables AI agents to safely query SQL databases through read-only tools for describing entities, reading records, and aggregating records, with view-based access and fail-closed per-user row-level security.

A local DLP middleware that redacts sensitive information from prompts using local models before they reach external LLMs. It provides tools to sanitize queries, restore placeholders in responses, and manage a ledger of redactions to maintain data privacy.

Security-focused MCP adapter that combines read-only DataHub metadata with a reviewed OKF-derived policy IR to execute closed, typed SQL queries against synthetic PostgreSQL data.