"ANA" matching MCP servers:

Enables AI to analyze Java classes from Maven project dependencies, with support for decompilation strategies and configurable groupId mappings.

A Model Context Protocol (MCP) server that gives AI assistants deep visibility into databases, inspecting schemas, detecting index problems, analyzing table bloat, and explaining query plans across PostgreSQL, MySQL, and SQLite.

Provides access to real-time LLM pricing, speed metrics, and performance benchmarks for over 300 models from Artificial Analysis. It enables users to list, filter, and compare models based on costs, tokens per second, and intelligence indices.

Enables loading and statistical analysis of .xlsx and .csv files with visualization capabilities using matplotlib and plotly to generate various graphs and charts.

The server facilitates natural language interactions for exploring and understanding codebases, providing insights into data models and system architecture using a cost-effective, simple setup with support for existing Claude Pro subscriptions.

MCP server for TypeScript type resolution and dependency graph analysis using ts-morph and madge.

A Python-based MCP server that enables AI-assisted log file analysis with features for filtering, parsing, and interpreting log outputs, plus executing and analyzing test runs with varying verbosity levels.

Enables AI assistants to analyze and query SQL Server databases, including schema discovery, health checks, and data retrieval.

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Tableau CRM Analytics (beta): https://www.cdata.com/download/download.aspx?sku=FSZK-V&type=beta

Exposes conda environment management tools to MCP-enabled AI coding assistants, enabling them to create, modify, and delete environments and packages on your machine.

Analyzes frontend project code (React, Vue, Angular) and converts it into AI-understandable flow diagrams and object structures. Provides tools for code analysis, variable/function/component inspection, and project structure insights.

Bridges AI models with WinDbg to analyze Windows crash dumps and perform remote debugging through natural language queries, enabling execution of debugger commands and automated crash analysis.

Provides deep source code analysis for Unreal Engine codebases, allowing AI assistants to understand C++ class structures, search code, and analyze subsystems.

A FastMCP-based server that provides data analysis tools for processing, analyzing, and visualizing data with an intuitive Streamlit web interface.

Self-hosted MCP server using Ollama for local AI-powered code analysis, refactoring, and optimization. Integrates with VS Code via Continue or Roo.

A Docker-managed MCP server for analyzing React codebases and generating component documentation from mounted workspaces. It enables users to scan projects, analyze JSX/TSX strings directly, and generate Markdown docs while ensuring safe path handling.

Enables AI agents to read-only query a SQLite database, inspect schema and table summaries, and execute SELECT queries with pagination through MCP.

Enables automated analysis of Woodpecker CI pipeline failures with intelligent error detection and fix suggestions. Supports both direct pipeline analysis and IDE-integrated git-context analysis using repository names, PR numbers, or branch information.

Tracks and analyzes AI agent tool calls with event logging, dashboard, per-tool and per-agent analytics, and error monitoring.

Universal Database MCP Server enabling AI assistants to connect and query multiple databases including Databricks, BigQuery, PostgreSQL, MySQL, SQL Server, SQLite, and MariaDB through a unified interface.