An MCP server designed for SQL analysis that demonstrates sampling capabilities by interacting with SQL files in a local directory. It provides a framework for testing client-side sampling while managing SQL-based contexts.
Provides secure, read-only access to Microsoft SQL Server with multi-layer protection, enabling safe query execution, schema discovery, and SQL script analysis through natural language.
Provides tools to prepare and validate ABAP Open SQL statements for SAP's ADT data-preview console, automatically fixing dialect issues like parenthesis spacing and 255-character limits.
An MCP server that performs code reviews by comparing local source code against design documents stored in Confluence. It integrates with Atlassian MCP servers to analyze documentation and provide suggestions for quality improvement based on design specifications.
Provides AI agents with a live architecture model of a codebase, enabling queries for root cause analysis, blast radius, and dependency traversal through MCP tools.
A metadata-guided, read-only SQL analysis MCP server for DataHub that helps agents perform safe analytical queries using DataHub schema, lineage, ownership, and tags, with a deterministic planner and strict SQL safety layer against local synthetic SQLite, guaranteeing zero write or mutation operations.
Enables interaction with Microsoft SQL Server databases through a virtual filesystem interface, comprehensive stored procedure management with draft-test-deploy workflows, safe write operations with transaction control, and performance analysis capabilities.
A Model Context Protocol server that provides Angular project analysis and refactoring capabilities, enabling LLMs to analyze component usage patterns, dependency structures, and perform safe refactoring with breaking change detection.
Extract domain knowledge from codebases to reduce LLM token consumption by 20x and time in agentic search by 10x — gathers and makes concepts, naming conventions, and vocabulary queryable via MCP.
Provides educational tools for developers to learn programming concepts, review code, get best practices, compare approaches, generate learning paths, debug, explain code, and quiz themselves.
Analyzes codebases to suggest relevant learning projects and generate interactive slides with direct links to the Marble platform. It enables developers to create tailored learning experiences based on their specific technologies, patterns, and code context.
Generates DeepWiki-style documentation for private code repositories with RAG-based Q\&A capabilities, semantic code search, and multi-language AST parsing. Supports local LLMs (Ollama) or cloud providers for privacy-focused codebase analysis.
Enforces AST-based architectural guardrails on AI-generated code, blocking writes that violate maintainability, security, or complexity rules and prompting immediate refactoring.