ClariLayer

Name: ClariLayer
Author: clarilayer

作者：clarilayer版本 0.31.0i★ 71i在云端运行

注册名称io.github.clarilayer/clarilayer

安装

概览

作者提供的说明（英文原文）

Individual-analyst context layer: recall, remember, and reconcile your data and engineering context.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数：意见、测量和人气是不同的东西。

用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
我们的基础检查i4 项中通过 4 项依据公开信息检查；尚未扫描代码
使用情况i起步阶段★ 71

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

连接方式: 在云端运行
传输方式: Streamable HTTP
分类: 其他
你需要填写：Authorization

安装

选择你使用的 AI 应用，然后复制设置。

安装之前

基础检查：4 项中通过 4 项
在作者的服务器上运行：你向它提出的内容会经过他们的服务器。
需要你自己填写： Authorization

标为机密的值是你账户的钥匙。千万不要分享给别人，也不要粘贴到聊天里。

你需要

在云端运行无需安装任何东西，通过互联网连接

你用的是哪个应用？

ClaudeClaude CodeCursorVS CodeChatGPT

在上方选择你的应用。我们会记住它，下次按钮会显示“安装到 …”。

这个地址需要在请求的 header 中放入密钥，而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。

在终端中运行这条命令

claude mcp add --transport http clarilayer https://clarilayer.com/api/mcp/mcp --header 'Authorization: your-value'

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json，或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "clarilayer": {
      "url": "https://clarilayer.com/api/mcp/mcp",
      "headers": {
        "Authorization": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "clarilayer": {
      "type": "http",
      "url": "https://clarilayer.com/api/mcp/mcp",
      "headers": {
        "Authorization": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

这个地址需要在请求的 header 中放入密钥，而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。

你的选择通过 Cookie 保存在这台设备上，无需账户。

需要你填写的值

Authorization 机密必填 HTTP header
Bearer cl_ — mint one at clarilayer.com via Connect your AI

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同，请以 README 为准。

哪些应用可以使用它

依据这个服务器的连接方式和各应用自己的文档，检查于 2026年11月10日。

通过互联网连接，适用于

Claude ChatGPT Goose LM Studio Msty Studio Cherry Studio Cursor VS Code + GitHub Copilot Visual Studio Windsurf (Devin Desktop)Zed Kiro Cline Continue JetBrains AI Assistant Claude Code Codex CLI Gemini CLI OpenCode nodecode Warp LibreChat Open WebUI Raycast

全部应用及其优缺点 →

它能做什么

服务器要求先登录，才会列出它的工具。

基础检查i

我们检查的是任何人都能看到的信息；我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月10日

✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 clarilayer 验证，该账户拥有此仓库
✓ 通过
仍在维护
代码最后更新于2个月前
… 尚未检查
有许可证
我们还没有从 GitHub 读取这个仓库
✓ 通过
端点有响应
在 1069 毫秒内响应（HTTP 401）
✓ 通过
使用 OAuth 登录
声明支持 OAuth 登录，你的 AI 应用可以带你去登录
… 尚未检查
工具描述中没有隐藏指令
尚未检查；我们会在检查端点时读取工具列表

与“其他”中的其他服务器比较i

星标数多于此分类中其他 19105 个服务器的 98%
发布到注册中心的时间比此分类中其他 19105 个服务器的 17% 更新
基础检查结果等于或优于此分类中其他 19105 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时，星标数才计入。

常见问题

ClariLayer 安全吗？

它在 4 项适用的基础检查中通过了 4 项。我们没有阅读代码。在添加密钥或令牌之前，请先看看这个服务器要求哪些权限，并使用只具备所需权限的密钥。

它需要哪些密钥或代码？

你需要填写：Authorization

它在我的电脑上运行还是在云端？

它在作者的云端运行。通过互联网连接，无需安装，但你发送的内容会经过作者的服务器。

它还在维护吗？

GitHub 仓库最后更新于2个月前，最新版本（0.31.0）于3个月前进入注册中心。

哪些应用可以使用它？

支持 MCP 的应用，例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接，所以接受远程 MCP 服务器的应用也可以使用，例如开启开发者模式的 ChatGPT。

有什么可以替代它？

同一分类中有：World Monitor, Claude Flow, Tldraw

替代选择

同一分类中其他作者的服务器，按星标数排序。

如何看卡片：↓ 每周下载量i★ GitHub 星标i三大支柱：评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

World Monitor

Real-time global intelligence on conflict, markets, energy, trade, shipping and cyber. 102 tools.

作者：koala73广泛使用★ 9万5天前更新

在云端运行✓ worldmonitor.app

安装

Claude Flow

AI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.

作者：ruvnet广泛使用↓ 1.4万/周★ 8.1万14个月前更新

在你的电脑上运行

安装

Tldraw

Draw and visually collaborate with your agents on tldraw's canvas.

作者：tldraw广泛使用★ 5.1万8个月前更新

在云端运行

安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

ClariLayer

Your AI should remember how you work.

Turn selected past conversations into memory your AI can use across projects and sessions.

Website · Docs · Connect your AI · Quickstart

ClariLayer keeps the facts, preferences, decisions, rules and lessons you choose to carry forward. Connect Claude Code, Cursor, Codex, claude.ai or another compatible remote MCP client. Your AI can recall relevant work context from the selected authorized space, with its source and applicability visible.

Start free. No credit card for the current personal offer.

One decision, carried into the next session

You settle a launch decision with your AI:

For the Launch project, show the product demo first. Technical detail belongs in docs. Remember this confirmed decision with its source and project applicability.

In a later session:

Recall the Launch project's saved decisions before drafting the launch page. Show which decision applies and where it came from.

The decision can travel across projects and sessions within the authorized space while retaining its original applicability. A rule for one customer or project stays bounded. If it changes, correct it; if it no longer belongs, use scoped forget or exclusion.

Recall depends on the AI client actually calling the tool. Connecting MCP does not guarantee every answer uses saved context.

Connect your AI

Use [Connect your AI](https://clarilayer.com/connect-ai) for guided setup. Select your client and space, give the setup request to that AI, and complete authentication in the client. Use OAuth when the selected route supports it, or store a context key locally as the fallback. Never paste a key into an AI conversation or a GitHub issue.

Already connected? Choose Update my AI setup on the same page, then run its request in the intended project. This updates one recognized ClariLayer instruction block while preserving your own instructions.

Client	Project instruction target
Claude Code	`CLAUDE.md`
Codex	`AGENTS.md`
Cursor	`.cursor/rules/clarilayer.mdc`
claude.ai / other remote clients	Follow the connection and runtime guidance supported by that client

The installed bootstrap obtains the current workflow from get_project_stanza with mode: "runtime" once at the first relevant use in each new AI session. A routine server guidance update then reaches the next session without copying another long workflow into every project.

Optional setup CLI

The npm CLI supports context-key connection setup and a local dbt check. CLI 0.3.0 replaces the embedded Analytics instructions with a request for your connected AI and adds instructions --agent .

Check which version is available before choosing a command:

npm view clarilayer version

With 0.3.0 or later available:

npx clarilayer@latest init

Already connected? Print only the instruction update request:

npx clarilayer@latest instructions --agent codex

If your registry still serves 0.2.1, use npx clarilayer@0.2.1 init --no-stanza to skip its older embedded instructions, then complete Update my AI setup through the guided setup above. The hosted path is available independently of npm publication.

See CLI.md for options and the source-checkout route, CHANGELOG.md for release history, and RELEASING.md for publication checks. Native instruction qualification records the tested client and its limits.

Full setup, manual connection examples and troubleshooting: [QUICKSTART.md](./QUICKSTART.md).

What your AI can do

Work	How it works
Recall	`recall_context` retrieves relevant saved context across the selected authorized space. Preserve source and applicability; project and purpose are relevance hints, not permissions. Fetch complete entries with `get_context_entry` when needed.
Remember or correct	`remember` with `work_context` saves confirmed durable facts, preferences, decisions, rules and lessons. Ambiguous changes and suggestions remain candidates for review.
Forget	Recall the target first, then use its returned entry ID for the requested forget operation. Do not guess names or delete related entries without a separate request.
Complete the context loop	`context_checkpoint` records the AI's bounded completion declaration. It does not prove the AI used the right context or completed an external task.
Report use	`report_context_use` optionally links bounded feedback to delivered context. A delivery receipt alone is not evidence of answer quality.

The hosted MCP service was checked on September 17, 2026: capability v64 · server 0.39.0 · 23 tools. Use the live capabilities tool for the current list and versions. Capability reference.

Bring over selected history

After connection, you can choose supported local history, a destination space and an extraction provider, then inspect the exact preview before accepting an initial import. Ongoing capture requires a separate setup and grant for the sources you choose. Connecting MCP alone does not read history or enable capture.

Source support and extraction-provider support are separate. The current qualified extraction path uses a version-specific Claude CLI profile; OpenAI and Cursor extraction providers are unavailable, and native Cursor history qualification is limited. Check the current history guide before choosing a source.

Selected source content is processed by the chosen extraction provider. ClariLayer stores the extracted context rather than a raw transcript archive. Provider processing may use your allowance or incur provider usage charges.

Optional semantic search has separate organization consent and provider disclosure in Settings. A new connection or history-import choice does not grant that consent. Lexical recall remains available without it.

Analytics when your work needs it

ClariLayer for Analytics retains its specialist tools:

get_analysis_context recalls definitions, schema notes, saved queries and related context. Recall previews can be truncated; use get_context_entry for full bodies, stored SQL and CRM contracts.
bootstrap imports supplied SQL, dbt models, notes, data dictionaries and semantic models. It does not read a repository or warehouse by itself.
reconcile compares a saved definition with supported warehouse or bounded, row-free HubSpot evidence supplied by your agent. Salesforce contracts can be stored and recalled; Salesforce reconcile is disabled.

General work and engineering context are not independently reconciled. Live trust statuses remain `asserted` / `caveat`; verified is not live.

Watch the Analytics reconcile example

A seeded Analytics demo. Your agent supplies the warehouse evidence; a mismatch becomes a caveat for later sessions. This illustrates the Analytics specialist path.

Check dbt documentation locally

cd your-dbt-project

dbt docs generate npx clarilayer dbt-check

The CLI compares local manifest.json and catalog.json files for phantom columns, missing catalog models, type-family mismatches and empty descriptions. No account or warehouse connection is needed for the local check. With an explicit --save, bounded findings are staged as proposals in your Context Inbox for review. --save --dry-run previews the payload without a network request.

See the CLI reference and Analytics recipes. The August 2026 dbt drift survey retains its method, evidence and limitations for the published 0.2.1 check.

Control and privacy

Saved context retains its source and applicability. Separate spaces do not merge automatically.
History import, ongoing capture and semantic processing each have their own setup or consent boundary.
In the personal MCP reconcile path, ClariLayer holds no warehouse or CRM credentials, executes no SQL and calls no HubSpot API. Your agent supplies the evidence. Warehouse evidence may include optional preview rows; CRM evidence is row-free.
Suggestions can be staged with propose / propose_batch for review. Pending proposals are not live recall context. Ad hoc conversation harvest requires an explicit request and sends distilled candidates, not the transcript.

Security · Privacy · Pricing

What is open source?

This repository's docs, examples, recipes and setup/dbt CLI are MIT licensed. The hosted ClariLayer service is proprietary. This repository is the public starting point for connecting to the service.

The Governed Context Edge is available through a hand-run private team pilot. Request early access.

For contributions and setup help, see CONTRIBUTING.md.

ClariLayer

概览

PopNx MCP 的三大支柱

它能帮你做什么

安装

安装之前

需要你填写的值

哪些应用可以使用它

它能做什么

基础检查i

作者与仓库一致

仍在维护

有许可证

端点有响应

使用 OAuth 登录

工具描述中没有隐藏指令

与“其他”中的其他服务器比较i

常见问题

替代选择

World Monitor

Claude Flow

Tldraw

作者的 README

One decision, carried into the next session

Connect your AI

Optional setup CLI

Already connected? Print only the instruction update request:

What your AI can do

Bring over selected history

Analytics when your work needs it

Check dbt documentation locally

Control and privacy

What is open source?