"Maintaining Consistent Behavior in System Prompts" matching MCP servers:

A modular monolith MCP server connecting multiple providers (Redash, PostgreSQL, GitHub) with unified permission, security, and auditing, enabling secure data access and tool execution.

Enables users to manage company departments, employees, expenses, and performance ratings through a natural language interface in Claude Desktop. It features 12 specialized tools for comprehensive CRUD operations and AI-powered organizational analysis using Google Gemini.

MCP server for snowflake that doesn't allow write operations under any circumstances, and includes a system prompt.

A comprehensive system that helps organizations track, manage, and respond to security vulnerabilities effectively through features like vulnerability tracking, user management, support tickets, API key management, and SSL certificate management.

A production-grade MCP server that enables AI assistants to securely manage healthcare data through clinical tools for patient vitals, lab results, and medication ordering. It prioritizes security and compliance with features like HIPAA-ready audit logging, PII redaction, and role-based access control.

Enables integration with financial transaction data through REST APIs, PostgreSQL databases, and document storage systems. Demonstrates agentic AI capabilities by connecting to Alpha Vantage API and managing financial data through natural language interactions.

A dual-server MCP system with PostgreSQL integration that provides financial tools (stock prices, portfolio calculation, financial news) on one server and utility tools (weather, time, data processing, text analysis) on another server.

Enables intelligent analysis of regression test failures and automatic discovery of solutions in JIRA. Analyzes test logs using AI-driven algorithms and matches errors with relevant JIRA issues through natural language interactions.

An unofficial MCP server for Percona Everest that enables AI-powered interaction with database clusters, including listing, retrieving details, credentials, and components.

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 read-only SQL analytics and ALS collaborative filtering recommendations on a Postgres e-commerce database.

A full-stack AI application implementing a Model Context Protocol server for retail operations. It enables users to query inventory, analyze pricing elasticity, and get demand forecasts through a conversational interface connected to Firebase Firestore.

Enables querying a Neo4j knowledge graph about Wroclaw University of Science and Technology using natural language. Converts user questions into Cypher queries and retrieves contextual information through an intelligent RAG pipeline with LLM-powered query routing.

Enables intelligent data analysis and querying of Snowflake databases through specialized AI agents. Features 20+ tools for data operations, lineage tracing, usage analysis, and performance optimization with multi-agent architecture.

Enables natural language interaction with heterogeneous databases (MySQL and PostgreSQL) for CRUD operations across customer, product, and sales data with intelligent query routing and visualization capabilities.

A Model Context Protocol (MCP) server that converts natural language queries into SQL statements, allowing users to query MySQL databases using conversational language instead of writing SQL code.

A comprehensive Model Context Protocol (MCP) server for product inventory management with PostgreSQL database backend, enabling natural language queries for product information across multiple AI platforms.

Enables AI assistants to manage todo lists through natural language by creating, listing, updating, completing, and deleting tasks stored in Firebase Firestore. Supports custom system prompts for personalized task management workflows.

An MCP server that turns an AI lead management system into a conversational tool any MCP-compatible AI client can control directly, with tools, resources, and prompts for lead classification, tracking, and weekly reviews.

A comprehensive Model Context Protocol server implementation that enables AI assistants to interact with file systems, databases, GitHub repositories, web resources, and system tools while maintaining security and control.