"Understanding Proxies or Proxy Servers" matching MCP servers:

An MCP server that analyzes local or remote GitHub repositories, providing intelligent code context and structure to AI coding assistants.

MCP server providing AI assistants with tools for advanced EVM smart contract analysis, including proxy detection, implementation resolution, and security analysis.

A FastMCP-based proxy server that seamlessly integrates any MCP client with the Devin MCP API, enabling AI-powered repository analysis and question answering.

A proxy server that forwards MCP requests to a JetBrains IDE server, with support for path conversion between WSL, Git Bash, and Windows.

A collection of MCP servers providing structured tools for ARM specification, verification, assembly analysis, and performance checks. They enable LLM agents and engineers to perform formal verification, analyze assembly code, and evaluate performance constraints.

40 regulation-and-deadline linters (CRA/CSAF, PCI DSS 6.4.3, WCAG 2.1 AA, DORA, NIS2, EU AI Act, KSeF, NF-e) that AI agents call over MCP. Free checks on the open file; licence key unlocks workspace scan and CI exit code.

MCP server for high-fidelity code audits, refactoring, and architectural analysis using specialized Proxy Experts.

Exposes Cursor IDE's MCP tools (codebase search, file operations) as an HTTP API for integration with Open WebUI, n8n, and other automation tools.

Provides AI coding agents with five intelligence layers (dependency graph, git history, documentation, architectural decisions, code health) via nine MCP tools, enabling deep codebase understanding and reducing exploration cost.

An MCP server that helps AI agents comprehend a codebase by providing tools for navigating, searching, and understanding code structure and history.

A self-contained, in-memory graph database for AI Agents. Provides semantic code understanding through the Model Context Protocol (MCP).

A research proxy that lets Claude, Cursor, and other MCP clients utilize Gemini's generous free tier for deep codebase analysis without burning your main model's quota!

Local MCP tool for understanding JSON Schema files while planning tests, summarizing types, required fields, constraints, and generating placeholder paths without copying data.

An MCP server that enables coding agents to autonomously test, evaluate, and tune other MCP servers by acting as a proxy and providing linting, trace recording, evaluation, comparison, and reporting tools.

Stop pasting your file tree into Claude. Give any AI assistant real architectural understanding of a codebase — local, private, zero‑config.

Integrates Google Gemini 3.1 with Claude Code to provide web search, large codebase analysis, multimodal image understanding, and creative brainstorming, leveraging Gemini's 1M token context and Google Search grounding.

Enables AI-assisted FlutterFlow development by reading, exploring, and understanding FlutterFlow projects through Claude and other MCP-compatible clients.

High-performance code understanding toolkit that enables batch reading of multiple files with dependency context, structural outline extraction with Java annotation awareness, and precise location of classes/methods across large codebases.

Enables agents and CI pipelines to audit MCP servers and agent tool-chains by statically scanning repositories, local checkouts, tools/list exports, or live endpoints for risks such as destructive actions without confirmation, mismatched safety annotations, injection surfaces, credential or PII exposure, and unguarded command, path, or URL sinks. All checks are read-only and never execute the scanned code or call tools/call.

Provides structural, queryable understanding of a Python codebase via MCP tools, enabling direct lookups for callers, dependencies, and class hierarchies without repeated grep/read cycles.