"Advanced Engineering Fundamentals: Structural, Materials, Dynamics, and Thermodynamics" matching MCP servers:

An MCP server that provides governed metric definitions and provenance-labeled memory for materials test labs, enforcing quality system discipline on agent interactions.

Enables local engineering workflow management by consolidating tickets, QA evidence, time tracking, root cause investigation, knowledge, and reporting into a single SQLite database, allowing generation of complete ticket packages for handoffs, dailies, or career evidence.

An MCP server that enhances sequential thinking with meta-cognitive capabilities including confidence tracking, hypothesis testing, and organized memory storage through graph-based libraries and structured JSON documents.

Enables querying a local health knowledge base with hybrid RAG (vector + FTS5) and exploring backlinks between notes.

Provides persistent memory and semantic code understanding for AI assistants using MongoDB Atlas Vector Search. Enables intelligent code search, memory management, and pattern detection across codebases with complete semantic context preservation.

A unified MCP Gateway for enterprise knowledge, code, and memory tools, featuring admin management for documents, accounts, and MCP keys, with local network deployment support.

Provides AI assistants with structured access to an organization's engineering standards, practices, and processes through searchable knowledge base with CRUD operations and multi-dimensional organization.

Provides a stdio MCP bridge for coding agents to query and record engineering knowledge locally, preserving debugging history, failed attempts, and verified solutions.

Enables AI assistants to index, search, and retrieve engineering documentation, architecture, standards, and knowledge from the OpenHaus Engineering System via the Model Context Protocol.

Enables complex problem-solving through multi-modal reasoning, dynamic knowledge graphs, meta-cognitive reflection, and collaborative AI personas.

Provides personalized Data Engineering learning updates by fetching recent news about DE concepts, patterns, and technologies, while tracking user knowledge to present only new information relevant to their learning journey.

Enables to run structured QuReDec decision briefs from inside MCP-compatible clients, submitting questions and receiving evidence-backed recommendations with citations.

Provides engineering leadership benchmarks, developer value calculation, and mentoring playbooks based on real 1:1 sessions with 300+ engineering leaders.

Enables offloading large tool outputs from LLM context and recalling them on demand to save tokens.

Provides structured local memory for Claude Desktop, reducing token usage by over 95% through intelligent retrieval and layered storage.

Enables AI agents to store and retrieve project context, bugs, decisions, and session logs by reading and appending markdown files in a local Obsidian vault, without requiring any cloud services.

A Model Context Protocol server that enables AI agents to query a Graphiti knowledge graph and pgvector document store for evidence-backed responses via hybrid search and RAG.

Enables Claude and ChatGPT to share a single study-progress database for interview prep, coursework, and spaced repetition, with per-user data isolation and server-side SM-2 scheduling for due reviews and study plans.

An MCP tool enabling structured thinking and analysis across multiple AI platforms through branch management, semantic analysis, and cognitive enhancement.

TheWeave is a markdown-native memory architecture for Claude and any MCP-aware agent. Your agent's memory lives as plain .md files you own: a 5-verb MCP core over the vault, query-driven PageRank retrieval, bi-temporal facts (valid_from / valid_until), and a persona-as-vault model. No database and no embeddings server. The files are the memory, inspectable in your editor and versionable in git.