"Retrieving Markdown Files from a Database" matching MCP servers:

Enables read-only listing and reading of files in an Azure Files SMB share, enforcing each user's NTFS permissions per request.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Enables LLM agents to access Global Database's company intelligence, including company profiles, financials, ownership, people search, prospecting, and KYB/compliance lookups against official registries.

A small MCP server that lets an LLM query PostgreSQL, MySQL, MariaDB, SQL Server, or SQLite databases safely — read-only, role-restricted, and with sensitive data blacked out.

Enables LLM clients to safely inspect database schemas and run only approved read-only queries and stored procedures, with auditing.

Enables AI clients to safely query PostgreSQL or SQLite databases read-only through AST-validated guardrails, schema introspection, and statistical table profiling. It returns results as Markdown tables, JSON audit reports, and database health checks.

This MCP server provides secure access to databases for AI agents, enforcing authentication, authorization, human approval, logging, and notifications to prevent dangerous actions.

Enables AES-256-CBC encryption and decryption of messages with passphrase-derived keys, exposing tools, resources, and prompts for MCP clients like VS Code Copilot Chat.

Provides agent certification and trust verification tools for AI agents, enabling certification checks, trust score calculations, audit ticket issuance, and emergency kill switch activation through the A-SOC trust network.

Enables AI agents to interact with a user management REST API, providing list, get, and create operations while preventing destructive actions like update/delete through an explicit access registry.

Enables AI agents to manage VPN infrastructure through provisioning, lifecycle control, traffic routing, and health monitoring.

Enables chatting with PostgreSQL databases through secure GitHub OAuth authentication, supporting read operations for all users and write operations for privileged users. Deployable as a production-ready remote MCP server on Cloudflare Workers with automatic schema discovery and SQL injection protection.

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 securely use real secrets (API keys, database passwords) by requiring human approval for each release, ensuring secrets never enter the model's context.

An MCP server that enables AI agents to securely add secrets to .env files by prompting the user to input the value through a local masked dialog, ensuring the agent never sees the secret.

A secure MCP server for querying a subscription business database with AST-based SQL guarding, PII masking, audited two-step write actions, and a seeded demo dataset.

An MCP server that exposes tools for issuing scoped agent credentials, delegating narrower child credentials, handling approvals, revoking task trees, and retrieving audit trails and evidence packets.

A secure PostgreSQL Model Context Protocol server that provides read-only database access through tools like schema listing, object inspection, query execution, and EXPLAIN analysis, with database-enforced access control via read-only transactions and a minimal role rather than SQL text parsing.

Anonymizes documents via the Stript desktop app locally, ensuring personal data never enters the conversation. Provides tools to anonymize files and clipboard content, fetch results, and restore original values to local files.

An MCP server that lets an AI agent probe a live URL and confirm whether sensitive files (e.g., .git, .env, source maps) are genuinely served by fetching and validating the content, avoiding false positives.