"Understanding Temporal Memory in Neuroscience and AI" matching MCP servers:

A local MCP server that accumulates the business-domain knowledge of a software project — flows, integrations, decisions, nuances — and makes it available to any MCP-compatible agent (Claude Code, Cursor, Copilot, Gemini, OpenCode). The goal is to capture the why behind the code: the stuff a new developer would need six months from now to understand why a thing is built the way it is. The what is

This MCP server provides a deterministic index of the First Principles Framework (FPF) spec, enabling agents to query patterns, routes, and relations without vector databases.

Make it easy for agents to build their context about your projects over time The server provides a set of tools to help agents accumulate knowledge about a project over time in a structured way.

Provides a structured documentation system for context preservation in AI assistant environments, helping users create and manage memory banks for their projects.

Enables natural-language Q&A over multi-source documents (PDF/Markdown/web) with a self-reflective retrieval-augmented agent that cites sources, retries on poor retrieval or grounding, and supports multi-turn memory.

Gives Claude Code and other MCP clients cited answers from a local, code-aware hybrid index of a repository's documentation and source, returning path:line sections linked to the code symbols they name. It also stores session handoff notes and doc/code conflict decisions in a git-backed memory, all running offline with no API calls or data leaving the machine.

A server for managing project documentation and context across Claude AI sessions through global and branch-specific memory banks, enabling consistent knowledge management with structured JSON document storage.

Enables semantic search over a software project's Markdown and text documentation by indexing document chunks in Qdrant and exposing retrieval through MCP tools.

Enables MCP clients to search and read the free AI School curriculum, including 550+ tracks on AI engineering, governance, security, and applied AI by profession.

A read-only MCP server that exposes Tiramisu AI's product information, pricing, and official links to MCP-compatible AI clients.

Readme Generator AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Enables AI agents to programmatically engage Agrus.ai by listing services and verticals, querying compliance positions, retrieving NDA-protected case studies, and drafting Discovery Sprint scopes for regulated industries.

An MCP server that provides indexed, searchable access to Anthropic Claude and Google Gemini documentation, with full-text search, page fetching, and section listing capabilities.

A smart documentation system that helps AI assistants understand and follow your project's conventions by automatically discovering, routing, and managing AI_README.md guide files.

Enables AI assistants to check whether a quote from the EU AI Act matches the right version on a given date, compare provisions across the 2024 and 2026 texts, and emit evidence records that anyone can recompute in a browser against signed corpus releases.

Lets AI assistants classify an AI system under the EU AI Act, returning risk tier, obligations, and deadlines based on a plain-English description of the product.

Provides a compressed knowledge graph of the NVIDIA AI developer stack for deterministic traversal, enabling agents to answer questions about dependencies and prerequisites with minimal tokens.

MCP server that generates ISO/IEC/IEEE 29119-3 compliant test plan drafts from project information, providing a structured resource for the standard's test plan outline and a tool for draft creation.

API Docs Generator AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Provides AI-powered search and documentation tools using Google Vertex AI or Gemini API with real-time web search grounding, enabling technical queries, code analysis, documentation retrieval, and architecture recommendations to overcome LLM knowledge gaps.