Tephra

io.github.andylang598由 GitHub 帳號 andylang598 發布v1.0.2更新於 Oct 29, 2026

Shared memory for your AI tools: top-5 recall 98.9% on answerable LongMemEval-S questions. Premium.

已驗證Streamable HTTP可網頁執行知識與記憶AI 與機器學習

概覽

AI 產生的概覽

託管式付費記憶服務,讓多個已連線的 AI 工具共用同一份記憶,可召回、搜尋並儲存與 Obsidian Metrics 帳號綁定的內容。

可以做什麼
  • 從帳號記憶與共享庫中依排名召回,支援關鍵字、語意或混合模式,並可選擇依時間順序回傳
  • 在同一份記憶上執行純語意搜尋
  • 儲存一筆記憶到自己的帳號,可指定區域、標籤與重要度
  • 在結果中附上指引區塊,例如先召回再儲存的提示與摘要表
適用情境
當你希望多個 AI 用戶端(Claude、ChatGPT、VS Code、Cursor、Gemini CLI 等)共用一份持久記憶來保存長期事實,且願意為託管服務付費時使用。
執行需求
遠端 streamable-HTTP 端點,無需自行架設。透過服務本身的 OAuth 流程以 Obsidian Metrics 帳號登入,不支援 OAuth 的用戶端可使用個人 AI 金鑰。需要付費 Premium 訂閱或一次性席次。選用的 stdio 橋接需要 Node 20.18.1 或更新版本。
安裝前請注意
付費產品,沒有免費方案;會員到期後金鑰與連線會暫停。記憶存放在第三方託管服務上,且不會自動擷取對話,需由 AI 主動呼叫儲存工具。個人 AI 金鑰可存取帳號,應妥善保管;最多 10 個可撤銷金鑰,可設為唯讀。有速率限制。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Tephra,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.andylang598%2Ftephra/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": {
    "tephra": {
      "type": "http",
      "url": "https://tephra.obsidian-metrics.com/mcp"
    }
  }
}

README

Tephra MCP

[Tephra MCP server]

Documentation and config examples for Tephra, a hosted remote MCP server: one memory your AI tools share, tied to your account. Tools you connect recall from it and add to it. Besides documentation and configuration examples, it holds a small optional stdio bridge (bin/, test/, package.json, MIT) for AI apps that only speak stdio. Tephra itself is a paid hosted service by Obsidian Metrics.

  • Server URL (Streamable HTTP): https://tephra.obsidian-metrics.com/mcp
  • Connecting: add the server URL. Clients that support MCP OAuth sign in with your Obsidian account from the client; for others, use a personal AI key (tpk_...). Sign-in support varies by client, so check the connect guide for yours.
  • Connect guide: CONNECT.md and https://tephra.obsidian-metrics.com/connect
  • Registry metadata: server.json; client config examples: mcp-config-examples.json

Features

  • One memory your AI tools share. The connect page has steps for Claude (claude.ai, Desktop and mobile), ChatGPT, VS Code (GitHub Copilot), Cursor, Claude Code, Gemini CLI, Windsurf, Zed, Mistral Le Chat, Perplexity and any other app that can add a remote MCP server. Each connected tool recalls from the same memory and adds to it.
  • Three MCP tools (a read-only key gets only the first two):
    • tephra_recall: ranked recall over your memory plus the shared library. query up to 4000 characters; limit 1-50 (default 10); optional keywords (up to 20 exact terms for the keyword arm), mode (semantic, keyword or hybrid) and reader_order: "chronological" (same rows oldest-first, each dated).
    • tephra_search: plain semantic search over the same memory, without recall's ranking extras. query up to 4000 characters; limit 1-100 (default 10).
    • tephra_remember: save one memory to your own account, never to the shared library. text up to 8000 characters; optional region (leave it out and Tephra files it), up to 10 tags, importance 1-5 (default 3). Tephra adds a via-ai-key tag and reports when the memory was already stored.
  • Tephra's directions on MCP: recall, search and remember results can include a <tephra_directions> block with the same guidance Tephra's REST API returns: a recall-then-save directive, a warning (flagged blocked) when a save was made without a recent recall, a completeness note, the summary sheet and the "you may be missing" list. The summary sheet, the missing list and alerts index stored records and are fenced and labelled as data, not instructions. The server's initialize instructions ask the AI to call tephra_recall before answering questions that may depend on saved context and tephra_remember to save durable facts; the AI still decides when to call the tools.
  • Hybrid recall: bge-m3 semantic search and a keyword arm fused by reciprocal rank, a cross-encoder rerank, and a bounded two-hop walk over linked memories.
  • Account-scoped by default: each member is their own tenant; everything a member saves is tied to their account and is not visible to other members.
  • Shared library: public knowledge (no member data), grown hourly from sources such as arXiv, PubMed, Federal Register and Crossref/OpenAlex; recall draws on it alongside your own memories.
  • Control and audit: up to 10 active AI keys, each revocable, optionally read-only, with its own activity log; a connected-apps panel to disconnect OAuth apps; edit history, edit/delete/contest a memory, data export (app).
  • Prompt-injection hardening on key/MCP results: invisible characters stripped, records capped at 4000 characters, results wrapped as notes-not-instructions.
  • Remote streamable-HTTP MCP, hosted on Cloudflare Workers; nothing to self-host; the stdio bridge below is optional.

Optional stdio bridge

Most AI apps connect to Tephra directly with the server URL above. For an app that only speaks stdio, this repository ships a bridge (bin/tephra-mcp.mjs, MIT) that starts mcp-remote (pinned to 0.15.2, published 2026-10-20 with GitHub provenance) pointed at https://tephra.obsidian-metrics.com/mcp:

npx -y github:andylang598/tephra-mcp#v1.0.0

Only this github: form is official; the names tephra-mcp and tephra-mcp-bridge are not registered on npm. Use the tag, not the default branch: npm ignores this repository's lockfile for git installs, so mcp-remote is exact but its own dependencies resolve within their version ranges when you install (the committed package-lock.json applies to npm ci from a clone). npx -y github:andylang598/tephra-mcp#v1.0.0 --print-config shows the one URL the bridge would use without connecting.

  • Sign-in is Tephra's own OAuth 2.1 flow, run by mcp-remote in your browser. The bridge's own code never handles a password, key or token. mcp-remote keeps the sign-in tokens it receives in ~/.mcp-auth on your machine (owner-only file mode); delete that folder to sign out.
  • The bridge accepts one MCP URL, https://tephra.obsidian-metrics.com/mcp, and refuses any other host, scheme, port or path, and any argument except --print-config. The child process inherits your environment, so proxy and certificate settings you have set apply to it.
  • The mcprush security grade for Tephra covers this bridge's source and its dependency tree as installed. It is not a review of the Tephra service, which runs at its own address.
  • Tests: npm test from a clone (offline). Node 20.18.1 or newer.

Limits

  • Tephra is a paid product: no free tier. Access is Premium ($19/mo at the member rate through the Obsidian Metrics community, $29/mo direct) or a $399 one-time Tephra seat with no subscription; no usage metering. Keys and connections pause if the membership lapses.
  • Rate limits: 60 requests per minute per AI key or connected app, plus a member-wide cap of 120 per minute.
  • The AI must call tephra_remember; Tephra does not auto-capture chats and has no Gmail/Slack/Drive connectors.
  • No image/audio ingest. Members cannot publish into the shared library.

Benchmark

LongMemEval-S, all 500 questions, top-10 retrieval, gpt-4o-2024-08-06 judge, one run: 85.2% with a gpt-4o reader; 95.2% with a Claude Opus 5.5 reader (run via Claude Code sub-agents); same retrieval. Retrieval had at least one needed session in the top 10 for 467 of 470, and all needed sessions for 435. Not a ranking.

來源:README.md,提交 205338d

工具

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版本歷史

3
  1. v1.0.2最新Oct 29, 2026
  2. v1.0.1Oct 25, 2026
  3. v1.0.0Oct 16, 2026

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