"MCP tools for monitoring application memory and CPU usage" matching MCP servers:

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.

MCP server providing npm registry search, package details, dependency auditing, bundle size estimation, and package comparison tools for AI agents.

An MCP server that provides a persistent sandbox for AI coding agents to explore codebases server-side, returning only compact summaries to reduce context consumption.

MCP server for semantic code indexing using vector embeddings, enabling AI agents to maintain persistent memory of codebases through natural language queries and intelligent chunking.

A stateless MCP server that gives coding agents a curated entry point to shared memory, orchestrating Hindsight (facts) and LightRAG (corpora) for automatic routing, URL ingestion, and consistency tooling.

MCP server providing dependency and package management tools for AI agents. Analyze licenses, find outdated packages, visualize dependency trees, estimate bundle sizes, and audit security vulnerabilities.

A Python framework that exposes developer tools through MCP, REST API, and CLI from a single shared registry, enabling AI assistants, HTTP clients, and terminal users to access the same tools.

Provides a memory server for coding agents over MCP, capturing and retrieving the meaning and rationale behind code decisions down to the function level. It enables agents to search product memory, get task context, and propose new memories to avoid re-deriving or re-breaking past decisions.

Provides AI-callable tools for modernizing legacy applications, including stack detection, API contract extraction, SQL to Flyway conversion, and migration effort estimation.

Provides AI coding agents with a hybrid cognitive memory engine that reduces token usage, prevents amnesia, detects repetitive error loops, and retrieves relevant code context through MCP.

A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.

An MCP server that enables persistent memory, structured thinking sessions, and project-based knowledge management for Claude. It includes specialized coding tools for package discovery and reinvention prevention by validating code against existing libraries and APIs.

Exposes Language Server Protocol (LSP) tools such as diagnostics, goto definition, find references, symbols, and rename as a stdio MCP server.

MCP server providing parser-backed validation, parsing, documentation, and editor assistance for AI agents working with _hyperscript.

Provides documentation generation and analysis tools for AI agents, including JSDoc generation, README analysis, changelog generation, API documentation, and code comment analysis.

Enables file reading with pagination and regex-based code search across a codebase using grep.

A Docker-based MCP server providing codebase memory and search tools. It enables storing/retrieving memories, regex search of code, and file summarization for AI assistants.

Local MCP servers that give Claude Code access to other tools mid-session.

Architecture-index MCP tools for kernelee apps that combine static analysis and runtime wiring into a JSON index, enabling coding agents to query control flow and dependencies via the Model Context Protocol.