Database
| Server | Language | Stars | Downloads |
|---|---|---|---|
| SQLite Explorer Explore, query, and inspect SQLite databases with ease. List tables, preview results, and view detailed schema metadata to understand structure quickly. Verify connectivity and readiness with a quick health check. | — | — | — |
| sqlite-explorer-fastmcp-mcp-server An MCP server that provides safe, read-only access to SQLite databases through Model Context Protocol (MCP). This server is built with the FastMCP framework, which enables LLMs to explore and query SQLite databases with built-in safety features and query validation. | Python | 105 | — |
| sqlite-literature-management-fastmcp-mcp-server A flexible system for managing various types of sources (papers, books, webpages, etc.) and integrating them with knowledge graphs. | Python | 18 | — |
| sqlite-mcp-server Universal SQLite DB MCP Server | Python | — | — |
| sqlite-mcp-server2 | — | — | — |
| sqlite-mcp-server3 | — | — | — |
| sqlite-mcp-server4 | — | — | — |
| sqlite-mcp-server5 | — | — | — |
| sqlite-mcp-server6 | — | — | — |
| sqlite-mcp-server7 | — | — | — |
| sqlite-mcp-server-enhanced A SQLite MCP server with JSONB support, database administration tools, and advanced database operations | Python | — | — |
| sqlmap-skynet SQLMap with Autonomous AI, phased workflows, RAG memory, and MCP Agent Tools | Python | 92 | — |
| sql-mcp-server MCP server that connects Claude to a Microsoft SQL Server database | Python | — | — |
| sql-migration | — | — | — |
| SQL Sentinel MCP Server SQL Server monitoring and diagnostics for AI agents using Extended Events. No ODBC drivers required. | — | — | — |
| SQL Server Integrates with SQL Server databases to execute queries, manage schemas, run stored procedures, and perform data operations across single-database and server-wide contexts with support for both on-premises and Azure SQL Database environments. | — | 3 | — |
| sqlserver-mcp-server A comprehensive Model Context Protocol (MCP) server for interacting with SQL Server databases | Python | — | — |
| SQL Server MCP (Windows) SQL Server MCP with RAG capabilities for Windows (native ODBC support) | TypeScript | — | — |
| ssd-ai AI development assistant that implements the **Model Context Protocol (MCP)** standard. It provides 36 specialized tools through natural language keyword recognition, helping developers perform complex tasks intuitively. ### Core Values - **Natural Language**: Execute tools automatically through Korean/English keywords - **Intelligent Memory**: Context management and compression using SQLite - **Multi-Language Support**: TypeScript, JavaScript, Python code analysis - **Performance Optimization**: Project caching system - **Enterprise Quality**: 100% test coverage and strict type system - **Long-Running Support**: Task management for asynchronous operations - **Large-Scale Data**: Cursor-based pagination --- ## Key Features ### 1. Memory Management System 10 tools for maintaining context across sessions: - **Intelligent Storage**: Information classification and priority management by category - **Context Compression**: Priority-based context compression system - **Session Restoration**: Perfect recreation of previous work states - **SQLite-Based**: Concurrent control, indexing, transaction support **Key Tools**: - `save_memory` - Store information in long-term memory - `recall_memory` - Search stored information - `auto_save_context` - Automatic context saving - `restore_session_context` - Session restoration - `prioritize_memory` - Memory priority management ### 2. Semantic Code Analysis AST-based code analysis and navigation tools: - **Symbol Search**: Locate function, class, variable positions across projects - **Reference Tracking**: Track all usages of specific symbols - **Multi-Language**: TypeScript, JavaScript, Python support - **Project Caching**: Performance optimization through LRU cache **Key Tools**: - `find_symbol` - Search for symbol definitions - `find_references` - Find symbol references ### 3. Code Quality Analysis Comprehensive code metrics and quality evaluation: - **Complexity Analysis**: Cyclomatic, Cognitive, Halstead metrics - **Coupling/Cohesion**: Structural soundness evaluation - **Quality Scores**: A-F grade system - **Improvement Suggestions**: Actionable refactoring recommendations **Key Tools**: - `analyze_complexity` - Complexity metric analysis - `validate_code_quality` - Code quality evaluation - `check_coupling_cohesion` - Coupling/cohesion analysis - `suggest_improvements` - Improvement suggestions - `apply_quality_rules` - Quality rule application - `get_coding_guide` - Coding guide lookup ### 4. Project Planning Tools Systematic requirements analysis and roadmap generation: - **PRD Generation**: Automatic product requirements document creation - **User Stories**: Story writing including acceptance criteria - **MoSCoW Analysis**: Requirements prioritization - **Roadmap Creation**: Step-by-step development schedule planning **Key Tools**: - `generate_prd` - Product requirements document generation - `create_user_stories` - User story creation - `analyze_requirements` - Requirements analysis - `feature_roadmap` - Feature roadmap creation ### 5. Sequential Thinking Tools Structured problem solving and decision making support: - **Problem Decomposition**: Break down complex problems step by step - **Thinking Chains**: Sequential reasoning process generation - **Multiple Perspectives**: Analytical/Creative/Systematic/Critical thinking - **Execution Plans**: Convert tasks into executable plans **Key Tools**: - `create_thinking_chain` - Thinking chain creation - `analyze_problem` - Problem analysis - `step_by_step_analysis` - Step-by-step analysis - `break_down_problem` - Problem decomposition - `think_aloud_process` - Thinking process expression - `format_as_plan` - Plan formatting ### 6. Prompt Engineering Prompt quality improvement and optimization: - **Automatic Enhancement**: Convert vague requests to specific ones - **Quality Evaluation**: Score clarity, specificity, contextuality - **Structuring**: Goal, background, requirements, quality criteria **Key Tools**: - `enhance_prompt` - Prompt enhancement - `analyze_prompt` - Prompt quality analysis ### 7. Browser Automation Web-based debugging and testing: - **Console Monitoring**: Browser console log capture - **Network Analysis**: HTTP request/response tracking - **Cross-Platform**: Chrome, Edge, Brave support **Key Tools**: - `monitor_console_logs` - Console log monitoring - `inspect_network_requests` - Network request analysis ### 8. UI Preview Pre-coding UI layout visualization: - **ASCII Art**: Support for 6 layout types - **Responsive Preview**: Desktop/mobile views - **Pre-Approval**: Confirm structure before coding **Key Tools**: - `preview_ui_ascii` - ASCII UI preview ### 9. Time Utilities Various format time queries: **Key Tools**: - `get_current_time` - Current time query (ISO, UTC, timezones, etc.) | — | — | — |
| Stash Persistent agent memory with 8-stage knowledge consolidation using PostgreSQL and pgvector. | — | 619 | — |
| steampipe-mcp-server A Python MCP server interacting with PostgreSQL, intended for use with Steampipe. | Python | — | — |
| STRING Database Integrates with STRING protein interaction database to enable protein network analysis, functional enrichment, GO/KEGG pathway analysis, cross-species homolog identification, and detailed annotation retrieval across over 5000 organisms for systems biology research. | — | 4 | — |
| structr ATTENTION: This repository is a clone of https://gitlab.structr.com/structr/structr. All development/issue tracking has moved there. | Structr is an integrated open-source low-code development and runtime environment that uses a graph database (Neo4j). | Java | 823 | — |
| Sudar An AI powered platform for empowering teachers in a multigrade classrooms | TypeScript | 1 | — |
| sugar Persistent memory for AI coding agents. Cross-session context, global knowledge, and autonomous task execution. | Python | 72 | — |