ClariLayer

io.github.clarilayer由 GitHub 帳號 clarilayer 發布v0.31.0更新於 Nov 2, 2026

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

已驗證Streamable HTTP可網頁執行知識與記憶開發者工具資料與分析

概覽

AI 產生的概覽

託管式上下文層,讓 AI 跨專案、跨工作階段回想、記住、修正與遺忘持久的工作上下文。

可以做什麼
  • 在已授權的空間內回想相關上下文,保留來源與適用範圍,並依需求取得完整條目
  • 儲存已確認的事實、偏好、決策、規則與經驗,或將不明確的變更暫存為待審提案
  • 在回想後依條目 ID 遺忘或排除指定內容,並記錄有界線的完成宣告與上下文使用回饋
  • 分析情境:回想定義、結構描述說明與已儲存查詢,匯入提供的 SQL、dbt 模型與資料字典,並以代理提供的證據核對已儲存定義
  • 在本機檢查 dbt 文件中的幽靈欄位、缺少的模型與型別不符,可選擇將發現暫存為提案
適用情境
適合希望助理把已定案的決策、規則與偏好從一個工作階段或專案帶到下一個工作階段或專案的場合,也適合需要讓分析定義與結構描述說明保持一致。亦適用於希望寫入先經審核、而非默默寫入記憶的團隊。
執行需求
透過 streamable HTTP 存取的遠端 MCP 端點,使用 OAuth 驗證;也可將上下文金鑰保存在本機作為備援,並透過 Authorization 標頭送出。需要 ClariLayer 帳號與已授權空間;選用的 npm CLI 需要 Node.js。本機 dbt 檢查不需要帳號或資料倉儲連線。
安裝前請注意
上下文金鑰屬於機密,請勿貼到 AI 對話或公開 issue。只有用戶端實際呼叫工具時才會回想,遞送回條或檢查點並不代表上下文被正確使用。歷史匯入與持續擷取需要另外設定與授權,所選內容會交由擷取服務商處理,可能產生費用。語意搜尋需另行同意。遺忘操作會刪除條目,應依回傳的條目 ID 精確指定。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 ClariLayer,將其新增到工作區。
  2. 連接 所需的 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
  3. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.clarilayer%2Fclarilayer/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。 客戶端會在首次連接時完成 OAuth 登入。

{
  "mcpServers": {
    "clarilayer": {
      "type": "http",
      "url": "https://clarilayer.com/api/mcp/mcp"
    }
  }
}

README

[MseeP.ai Security Assessment Badge]

[ClariLayer]

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 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.

ClientProject instruction target
Claude CodeCLAUDE.md
CodexAGENTS.md
Cursor.cursor/rules/clarilayer.mdc
claude.ai / other remote clientsFollow 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 <client>.

Check which version is available before choosing a command:

bash
npm view clarilayer version

With 0.3.0 or later available:

bash
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 [email protected] 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.

What your AI can do

WorkHow it works
Recallrecall_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 correctremember with work_context saves confirmed durable facts, preferences, decisions, rules and lessons. Ambiguous changes and suggestions remain candidates for review.
ForgetRecall 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 loopcontext_checkpoint records the AI's bounded completion declaration. It does not prove the AI used the right context or completed an external task.
Report usereport_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

[Analytics example: recall a net-revenue definition, compare it with warehouse evidence, then retain a mismatch as a caveat]

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

bash
cd your-dbt-projectdbt docs generatenpx 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.

來源:README.md,提交 87188b0

工具

0
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版本歷史

1
  1. v0.31.0最新Sep 16, 2026

評分

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