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

MCP server for multimodal understanding and object grounding (bounding boxes) across images, videos, and documents, with support for multiple AI providers (Zhipu GLM-V, OpenAI GPT-4o, Anthropic Claude, or any OpenAI-compatible endpoint).

An MCP server for debugging Temporal workflows, enabling LLM-assisted inspection of workflow executions, detailed workflow info, and event history.

Saves the user's exact words as immutable, SHA-256-hashed captures before anything else, then derives events, entities, context cards, and causal hypotheses — every fact traceable to its verbatim source. Local-first personal memory for Claude Code, Codex, and any MCP client.

Enables AI assistants to manage Temporal workflows, schedules, and workflow executions through a standardized interface.

Gives agents a stable interface for durable memory, combining exact, lexical, semantic, and graph search results.

Provides persistent session memory for AI assistants, enabling them to store, search, and retrieve conversation summaries across sessions via the Model Context Protocol.

Provides AI coding agents with a local, Markdown-first shared memory, enabling them to record decisions, failures, progress, and handoffs and retrieve them across sessions via MCP tools.

Provides a shared, persistent memory layer for AI assistants, letting them read and write to a local Obsidian vault through MCP with validation, secret rejection, and deduplication.

Enables managing invoice workflows using Temporal, allowing submission, approval, rejection, and status checking of invoices through MCP tools.

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

Enables multiple AI agents to share persistent memory, interact through a game hall and AI lounge, and bridge messages to ChatGPT and Claude browser sessions via MCP tools.

A Model Context Protocol (MCP) server that provides AI agents with comprehensive temporal awareness and time calculation capabilities.

Enables AI assistants to semantically search your entire local conversation history from Claude Desktop, ChatGPT and Claude Code, and to retrieve, browse, ingest and report on those conversations. All embeddings run locally, so no cloud, API keys, or data leave your machine.

Enables AI assistants to retain memory across sessions by storing conversations locally in Markdown files, allowing personalization and continuity without external servers.

Universal MCP server providing adaptive semantic memory for AI agents, supporting document ingestion, semantic search, chat persistence, cross-project linking, and cloud storage overflow.

Enables MCP-compatible AIs to read a user's local three-layer memory of their own typed chat messages, including raw text, conversation summaries, and theme indexes, so responses can be grounded in the user's past decisions and preferences.

An MCP server that lets LLM agents accumulate organizational knowledge across sessions, scoped by domain, backed by Neo4j with enforced structural invariants.

An experimental MCP server that compresses git commit co-change coupling graphs using the Baligács temporal clique linear spanner algorithm, reducing edge and token counts by ~55-65% while preserving temporal reachability, and exposes tools like index_repository, get_architecture, search_code, and temporal_compress for querying code knowledge graphs.

Integrates Xiaomi MiMo's multimodal API to enable understanding of images, audio, and video through natural language prompts.

A persistent, project-scoped memory layer for AI agents, supporting hybrid retrieval (vector, keyword, and tag matching) and sharing across different MCP clients like Claude Code, Qoder, or Cursor.