"How to find and troubleshoot a memory leak in software" matching MCP servers:

A minimal MCP server with get_weather and create_ticket tools, used for testing MCP servers across protocol, unit, eval, transport, and auth layers.

Enables AI assistants to diagnose Kubernetes clusters through read-only MCP tools, such as inspecting pod status, logs, events, nodes, deployments, and HPA metrics via natural language queries.

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

MCP server for detecting publisher telemetry pipeline leaks in binary artifacts by scanning for sensitive strings like Sentry DSNs, Slack tokens, and AWS keys.

Enables MCP clients to search locally indexed text files, PDFs, and images using natural-language descriptions, and to index folders and inspect index statistics.

Offline Python MCP server that audits Zapier, Make and n8n lead pipelines and lists where inbound leads are silently dropped.

Enables converting software development requirements into traceable estimates, WBS breakdowns, PERT calculations, risk registers, roadmaps, quotations, and professional PDF proposals or action plans. It supports reviewing assumptions, exclusions, scope gaps, and commercial documentation before sending deliverables to clients.

Enables AI agents to maintain persistent, searchable two-layer memory with 37 tools, hybrid search, knowledge graphs, and enterprise features like authentication and backups.

A discovery tool for AI agents to search, evaluate, and install MCP servers from multiple registries.

Turns Cursor into a full software factory with 10 specialist agents (PM, Architect, Backend, Frontend, etc.) as a local MCP server, keeping code on your machine.

A Windows-local MCP server that connects natural-language engineering tasks to COMSOL, Autodesk Fusion, and LabVIEW through their official software interfaces. It lets users submit, track, and verify parametric simulation, CAD modeling, and measurement jobs as configurable tools.

Enables LLMs to list, open, and close installed software on Windows, macOS, and Linux through natural language.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Enables MCP clients like Claude to query Chinese A-share market data, including K-line charts with forward/backward adjustment, limit-up and limit-down pools, per-stock fund flows, index quotes, and stock news, with automatic symbol normalization and retry handling for throttled data sources.

Provides A-share (Chinese stock market) quantitative analysis through tools for stock screening, northbound capital flow tracking, dragon-tiger list analysis, margin trading, sector analysis, technical indicators, IPO info, and limit-up/down statistics using akshare data.

Enables users to describe their LLM fine-tuning job once and get the cheapest, fastest, and most balanced GPU options across a dozen cloud providers in seconds.

Provides Claude Co-work with MCP tools to search and record organizational memory, including search, read, query, ingest, remember, sync, and status operations.

MCP server providing durable Substrate organizational memory tools, including search, read, query, ingest, remember, and sync. It integrates with Codex to automatically capture completed turns and session boundaries for persistent memory.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

提供A股实时行情、历史K线、财务报表、技术指标等全方位数据查询的MCP服务器，支持盘中即时更新及批量查询。