Noesis MCP Server

Noesis MCP Server

Provides persistent, cross-session memory for AI agents using a wave-based scoring system that surfaces relevant knowledge across sessions.

Category
访问服务器

README

Noesis

They store. Noesis knows.

Every AI memory product on the market does the same thing: it stores what you said and retrieves it by keyword or vector similarity. Start a new session and your agent reads the database. Close the gap between what it finds and what you meant. Hope it surfaces the right thing.

Noesis is built differently.

Noesis is the public face of EME — the Epistemic Memory Engine — a wave-based reasoning substrate that scores every piece of knowledge across four axes: activation, concordance, durability, and utility. It doesn't retrieve. It surfaces. The right thing rises because the system has been paying attention to what matters, isolating noise through entropy rather than time, and accumulating concordance across every session you've ever run.

Your agent doesn't remember. It knows.


What's in this repo

noesis/
├── skills/
│   ├── noesis-recall/      — persistent cross-session memory. free.
│   ├── pitch-adversary/    — five-vector adversarial stress-testing. free.
│   └── strategy-guardian/  — trading strategy memory and rule enforcement. paid.
├── server/                 — @vanta-ide/noesis npm package (MCP server stub)
└── .github/workflows/      — auto-publish to npm on tag push

Skills are agent instructions packaged as SKILL.md files. Install them into Claude Code, Claude.ai, Codex, or any MCP-compatible agent. Each skill calls the Noesis MCP server — hosted at rreme.dev/noesis or self-hosted via the npm package.


Install a skill

# via skillfish CLI
npx skillfish add vanta-ide/noesis noesis-recall
npx skillfish add vanta-ide/noesis pitch-adversary

Or download the SKILL.md directly from any skill folder and drop it into your agent's skills directory.


Connect the Noesis MCP server

Hosted (zero setup):

{
  "mcpServers": {
    "noesis": {
      "command": "npx",
      "args": ["-y", "@vanta-ide/noesis"],
      "env": {
        "NOESIS_ENDPOINT": "https://rreme.dev/noesis"
      }
    }
  }
}

Self-hosted:

npm install -g @vanta-ide/noesis
noesis serve --port 3100

Point NOESIS_ENDPOINT at your instance. The wave field, scoring, and all persistence run locally. Nothing leaves your machine.


The difference

Every other memory tool Noesis
Mechanism Store → retrieve Score → surface
Retrieval Keyword or vector similarity Resonance across four axes
Session boundary Resets or requires manual sync Survives. Accumulates.
Noise handling Time-based decay Entropy-based isolation
Gets smarter No Yes — concordance increases with use
Works across agents Depends on config Native — one wave field, all agents

Skills

noesis-recall — free

Gives your agent persistent memory across every session, every machine, every agent. Recalls relevant context before every response. Stores key observations after every session. The agent doesn't ask you to repeat yourself.

pitch-adversary — free

Five simultaneous attack vectors on any pitch, thesis, plan, or argument. Severity-ranked. Calibrated to audience. Remembers which objections you've already addressed and hunts for what you haven't. Doesn't soften when you push back.

strategy-guardian — paid

Learns your trading rules from your journal, backtests, and stated strategy. Flags in real time when your current setup matches patterns that have historically failed your rules. The only skill that remembers your strategy across every session and enforces it against your own behaviour.


Architecture

Noesis is the public interface to EME (Epistemic Memory Engine), the reasoning substrate at the core of the RREME stack.

EME is not a database. It is a wave field — a continuous amplitude memory architecture where every piece of knowledge has a position in four-dimensional scoring space. Knowledge that is accessed rises. Knowledge that contradicts established patterns loses concordance. Knowledge that is never relevant decays through entropy, not time.

The proprietary engine — wave field implementation, scoring algorithms, concordance calculation, Memoria training platform — is closed source and runs on Vanta's infrastructure. The skills and the MCP server interface are open. The intelligence is not.

RREME stack: EME (memory) → CTR (execution) → Synapse (validation) → SOVEREIGN (orchestration)


License

MIT — skills and server interface.

The underlying Noesis engine, wave architecture, concordance scoring, and trained models are proprietary to Vanta IDE and are not covered by this license.


Links

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选