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.

Original art from galleries and artists: search, details, delivered prices and checkout links.

Session-level (not fragment) local memory for AI coding agents: passively captures Claude Code, Codex, ZCode and Qoder conversations into one SQLite store, with provenance-cited retrieval and a human-only right to be forgotten.

Nornicdb is a distributed low-latency, Graph+Vector, Temporal MVCC with all sub-ms HNSW search, graph traversal, and writes. Using Neo4j Bolt/Cypher and qdrant's gRPC means you can switch with no changes while adding intelligent features like schemas, managed embeddings, reranking+llm, GPU accel, Auto-TLP, Policy-based Memory Decay, and MCP server.

A cyber brain for your AI. It never forgets a detail, remembers exactly what you said, and learns how you work over time. Free, local, works with Cursor, Claude Code, Codex, OpenClaw, Hermes and more. MIT.

AgentChat 是一个基于 LLM 的智能体交流平台，内置默认 Agent 并支持用户自定义 Agent。通过多轮对话和任务协作，Agent 可以理解并协助完成复杂任务。项目集成 LangChain、Function Call、MCP 协议、RAG、Memory、HITL、Skill、Milvus 和 ElasticSearch 等技术，实现高效的知识检索与工具调用，使用 FastAPI 构建高性能后端服务。

Run AI apps via inference.sh CLI - image generation, video creation, LLMs, search, 3D, Twitter automation. Models: FLUX, Veo, Gemini, Grok, Claude, Seedance, OmniHuman, Tavily, Exa, OpenRouter, and many more. Use when running AI apps, generating images/videos, calling LLMs, web search, or automating

An official Qdrant Model Context Protocol (MCP) server implementation

Stores what AI agents learn — thoughts, decisions, session events and repo facts — in PostgreSQL with pgvector and serves it back through versioned MCP tools with hybrid vector-plus-full-text retrieval and budgeted context packs. Enables multiple agents to share one scoped, role-isolated long-term memory, with deliberate promotion of distilled candidates into durable memories.

Enables agents to discover, search, compare, and inspect tested MCP tools by problem or keyword, with certification verdicts, scorecard summaries, certified scope, and explicit not-tested details.

Exposes 16 local stdio MCP tools that give Codex-style clients project-isolated persistent memory, local ONNX-based semantic search, and durable task tracking that survives across sessions and concurrent clients, without executing agents, hosting a model, or contacting model providers.

Enables MCP hosts to spawn, supervise, and collect results from parallel panels of pinned-model OpenCode v2 agents for delegated tasks, reviews, and cross-model comparisons. Supports per-member roles, models, permissions, follow-up prompts, cancellation, and persisted result retrieval.

Enables agents to reach pump.fun's full API surface — official developer routes, bonding-curve reads, Solana RPC, and unsigned trade building — by writing JavaScript against one merged OpenAPI document, using just two tools (search and execute). Model-authored code runs in a network-less sandbox, so multi-step questions resolve in a single round trip while credentials stay on the host Worker.

Enables coding agents to navigate and verify a contract-backed semantic graph of TypeScript backends, inspect change impact, run checks, explain failures, and draft human-reviewable contracts through bounded MCP tools and matching JSON CLI output.

Enables AI agents to run private web searches against a self-hosted SearXNG instance, rerank results with a local model, and fetch or extract pages locally into markdown, including PDFs, with optional caching, crawling, and cited local-LLM answers.

Connects MCP clients to a public CVE activity feed and private product watches, letting agents search advisories, save watched products, check and acknowledge matches, and track new or updated vulnerability records.

Enables people and AI agents to create, preview, publish, withdraw, and discover offers and requests across goods, services, trips, and delivery, with semantic matching and secure shared rooms for negotiation.

It enables AI agents to access live web data through page fetching, search, prebuilt scrapers, datasets, and remote browsers, using free direct requests and local Chrome rendering with Bright Data only as a fallback for bot walls. It also adds budget controls, caching, pagination, cancellation, retries, SSRF protection, and both stdio and HTTP transports.

Mounts a headless, low-memory browser for agents with a text-first tool interface, enabling navigation, semantic tree/markdown extraction, structured-data scraping, screenshots, form interaction, and session capture. Reads and interactions are returned as semantic trees, markdown, or CSS-selector JSON rather than pixels, which is cheaper for a model to reason over.

Enables AI agents to run web searches and fetch page content by driving a real Chromium browser over CDP, so every request carries an existing profile's cookies, login state, and fingerprint. It also lets agents click elements, fill and submit forms, read the current tab, and check browser/CDP status, returning accurate results from logged-in pages without being treated as an anonymous crawler.

Enables agents to crawl, search, map, and extract structured evidence from websites, SPAs, PDFs, Office files, YouTube videos, GitHub repositories, ArXiv papers, shopping and travel listings, and CVE advisories via local or cloud-backed tools.

Enables agents to search local Chinese text memories and fetch individual records through stdio tools, using bigram FTS5 recall with optional vector rank fusion.

Enables agents to search the web with ranked content-bearing results, extract clean text from pages, crawl sites under configured limits, and map site structure via the Tavily API.

Enables agents to run neural web searches, gather token-budgeted code context and documentation excerpts, and crawl individual pages through the Exa API.