记忆核心（Memory Eternal）：自研的 DeepSeek Harness 记忆插件，不移植任何既有记忆框架——对话结束后自动沉淀知识卡到本地 Markdown Vault（自研去重、自研 CJK 检索、可 git 管理），设置页提供图形化知识库（统计 / 搜索 / 知识图谱 + 侧边栏一键弹窗），Agent 通过 memory_recall 工具按需召回历史上下文。零人工干预。

Persistent session memory for AI coding agents that never leaves your machine — including the on-device model that reasons over it. Restores your prior decisions, open TODOs, and changed files across sessions; adds associative recall of related past work,

Local-first cross-session long-term memory for DeepSeek Harness: dual-scope SQLite stores, hybrid FTS5 + local-vector retrieval with RRF, an evidence gate, provenance audit and SM-2 spaced repetition. 23 narrow tools, zero external services, zero API keys

MCP server that gives Claude, ChatGPT and other MCP clients access to a Zotero library: search, citations, adding items, safe writes, semantic search, PDF passages and page images.

AI4Scholar for DeepSeek Harness (dsh): 38 native academic tools — Semantic Scholar, PubMed, Google Scholar, arXiv, bioRxiv/medRxiv, DOI resolution, PDF full text, auto-cite, scientific figures, credit balance — with an API-key card in the Web UI settings.

The open-source context layer for AI agents. PipesHub turns your company's knowledge (Slack, Drive, Jira, GitHub, Microsoft 365 and 40+ connectors) into a permission-aware workspace that agents can search, grep, navigate and cite. MCP, SDKs and built-in agents. Self-hosted.

🧠 RepoBrain (formerly Antigravity) — Give your repo a brain. ChatGPT for your codebase: works in Claude Code, Cursor, Codex, Windsurf & more.

Git-native persistent memory for AI coding agents. Implements Google OKF v0.2 with sub-300µs in-memory BM25 search, embedded MCP server, and progressive disclosure. Slashes token bloat by 80% with zero external databases or dependencies. Built in pure Go.

MCP server giving AI agents (Claude Code, Claude Desktop, Cursor, ChatGPT, Codex, OpenClaw) persistent long-term memory backed by your local Obsidian markdown vault. Hybrid retrieval (BM25 + ML embeddings + BGE reranker, RRF-fused), HNSW + int8 quantizati

The open-source memory and observability layer for AI agents — persistent memory, loop detection, hash-chained audit trails, and a live dashboard, automatic on pip install.

CoexistAI is a modular, developer-friendly research assistant framework . It enables you to build, search, summarize, and automate research workflows using LLMs, web search, Reddit, YouTube, and mapping tools—all with simple MCP tool calls or API calls or Python functions.

Self-learning vector memory for AI agents — single-file .rvf cognitive container with HNSW search, episodic Reflexion memory, causal graph + Cypher, 9 RL algorithms, Thompson Sampling bandit, 41 MCP tools, hybrid (BM25 + dense) retrieval, GNN attention. 1

Token architecture, component specifications, and slide generation. Three-layer tokens (primitive→semantic→component), CSS variables, spacing/typography scales, component specs, strategic slide creation. Use for design tokens, systematic design, brand-compliant presentations.

Source-linked CodeGraph exploration, ranked search, and static navigation for coding agents.

Local deterministic memory and safety kernel for AI agents. Replaces vector RAG with STRATA, a cryptographically signed, append-only ledger, so every agent state carries proof. Uses causal_walk engine to trace execution failures back to their root cause, and Operator Lite to block destructive terminal terminal commands before they ever run

Enables MCP clients to reverse-engineer binary files — hex viewing, disassembly, function/call-graph recovery, syscall and RTTI naming, string/xref search, and symbol export for Ghidra and IDA — across Switch NSO/NRO/NSP and many other formats. Tool output is persisted as annotations so analysis carries across sessions.

Enables AI assistants to search a catalog of framed public-domain masterworks and NASA photography, look up available sizes, frames and prices, and quote orders before tax and shipping. It can also generate a secure Stripe Checkout link so the buyer pays directly, and report order and shipping status without exposing card data.

Visual search for memes, infographics and charts — by meaning, OCR text, or image similarity.

MindQL queries, hybrid search, and a thought graph - read/write memory for AI agents.

EPO/USPTO search, citations, OCR, plus PATSTAT Portfolio Analytics, guarded SQL and Graph Analytics.

Give an AI a research direction: it runs literature synthesis, gap validation, hypothesis formation and experiment design itself. 267 markdown skills form a research graph: 51 operations built from 216 atomic steps, any order, explicit backtracking; the plan is approved before it runs and interrupted runs resume. npx install, no runtime, no API key

Search, extend, and act on your team's Naumu knowledge graph: notes, threads, and nodes.

Semantic Intelligence for Large-Scale Engineering. Context+ is an MCP server designed for developers who demand 99% accuracy. By combining RAG, Tree-sitter AST, Spectral Clustering, and Obsidian-style linking, Context+ turns a massive codebase into a searchable, hierarchical feature graph.

A lightweight, rollbackable, and visual Long-Term Memory Server for MCP Agents. Say goodbye to Vector RAG and amnesia. Empower your AI with persistent, graph-like structured memory across any model, session, or tool. Drop-in replacement for OpenClaw.