@Moai-Team-LLC
基本信息
Auditable, self-improving knowledge & memory for AI agents, served over MCP. Citation-enforced answers (no source, no claim), a replayable why-trace per answer, and a judge-gated loop that promotes validated knowledge. Zero-key local embeddings (bge-m3), hybrid vector + BM25 retr
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"agenticmind": {
"url": "https://YOUR_HOST/mcp",
"headers": {
"Authorization": "Bearer YOUR_MCP_TOKEN"
}
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。
点击上方按钮,直接连接服务器端点实时获取工具列表。
AgenticMind is a self-hosted, auditable knowledge and memory layer for AI agents, served over the Model Context Protocol (MCP). It provides citation-enforced answers with a full why-trace, a self-improving corpus, and runs entirely on Postgres with pgvector—no additional vector stores or external dependencies required for embeddings.
Quickstart: run OPENAI_API_KEY=sk-... sh -c "$(curl -fsSL https://raw.githubusercontent.com/Moai-Team-LLC/AgenticMind/main/quickstart.sh)" to pull Docker images and bring up the server. From source, clone the repo, run ./setup.sh then npm run dev. Point any MCP client (Claude Code, Cursor, LangGraph) at http://localhost:3000/mcp with the auto-generated bearer token.
AgenticMind enforces citations, provides a full why-trace for every answer, and includes a self-improving corpus and relational verification via a knowledge graph—all on Postgres+pgvector, unlike most RAG solutions that offer only fuzzy recall.
Requires Node ≥22.18 or Bun ≥1.3, and PostgreSQL with pgvector. Embeddings run locally by default (bge-m3), so no cloud key is needed for retrieval; only a chat-model key (e.g., OpenAI API key) is required for answer synthesis.
Validated answers are promoted back into the corpus through a judge-gated compounding loop driven by programmatic signals—not human feedback. A `kl_signal` tool emits these signals on prior answers.
No. AgenticMind is headless; agents interact with it solely via MCP tools over streamable HTTP. The only consumers are agents.
The MCP endpoint uses per-token bearer authentication with scoped, least-privilege tokens. In the quickstart, a static bearer key (`MCP_API_KEY`) is auto-generated; from source, a JWT with `typ="mcp"` is accepted. Authorization is fail-closed.
Search published GPU deployment, rack integration and structured cabling resources; read canonical documents and Leviathan Systems company service scope. Anonymous, read-only Streamable HTTP MCP. No credentials required.
AI agents start every session with amnesia — you re-explain the project, repeat your preferences, and correct the same mistakes over and over. PLUR gives them a memory that persists. Your agent's corrections, preference
The Cloud is the AI-native workspace that gives every AI — Claude, ChatGPT, Gemini, and other Frontier & Free or Local models — shared memory and real agents. Not cloud computing: thecloud.so is one workspace where your
Exact, shared memory for AI agents: a hierarchical database where totals always add up, every write is attributed to the agent and person behind it, and any figure traces back to its source file. Agents create databases,
Orcha is a unified context layer for AI tools and agents. It stores and indexes and exposes organizational, team, or individual knowledge. Files, structured databases, and connected sources live in one workspace, and age
评论