
Fidelis Memory
io.github.hermes-labs-ai由 GitHub 帳號 hermes-labs-ai 發布v0.2.0更新於 Oct 24, 2026
Recall locally stored agent memories through an MCP-compatible host.
發布方自己的服務:Memory.fit
概覽
本機記憶伺服器,讓助理逐字保存筆記,並在後續工作階段取回原始段落。
- 可以做什麼
- 從本機記憶庫取回已保存的筆記與段落
- 逐字保存新的文字與筆記,供後續工作階段使用
- 更正或取代舊記錄,同時保留其歷史狀態
- 取得並檢視單筆記憶記錄及其有效性
- 在共用儲存區上執行關鍵字與向量混合檢索
- 適用情境
- 適合需要把先前工作階段中的確切措辭、條件或注意事項帶進新工作階段,而非依賴摘要的情境。也適合希望筆記只留在本機、單機本地優先的使用方式。
- 執行需求
- 以本機 Python 套件執行(Python 3.10+,macOS 或 Ubuntu),可透過 uvx 或 pip 啟動。需要本機 Ollama 服務與 nomic-embed-text 模型產生嵌入向量,不需模型 API 金鑰。環境變數 FIDELIS_PORT 指定本機服務連接埠(預設 19420)。安裝會註冊隨登入啟動的使用者層級背景服務。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Fidelis Memory,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
Fidelis Memory
[Fidelis Memory mascot]Your agent can forget a summary. Fidelis brings back the note.
Local memory for Codex, Claude Code, and other agents: save text across sessions and retrieve the original passage when it matters.
by Hermes Labs
A project summary might say “billing migration rolled back.” The original note says why it failed and do not retry until the idempotency fix is verified. When your next session depends on that condition, the missing sentence matters.
Fidelis stores your Markdown and text notes and retrieves their stored wording. Its default retrieval does not ask a generative model to rewrite your memory.
Try it with one note
This path supports Python 3.10+, macOS or Ubuntu, and a local Ollama service. Start Ollama if needed (ollama serve in a separate terminal). No model API key is required. The current release is 0.3.0rc1.
fidelis watch and fidelis recall-hybrid use the background service started by fidelis init.
Look for both the rollback and the retry condition in the retrieved text. This is retrieval of a saved note, not a generated answer. For your own files, replace "$demo_dir" with a notes directory. If retrieval fails, run fidelis health and confirm Ollama has nomic-embed-text available. Keep the virtual environment after fidelis init; the background service uses it.
What this changes on your machine: fidelis init installs a per-user background service (launchd on macOS, systemd --user on Linux) that starts fidelis-server automatically at login. fidelis watch sends the note to that server, which saves it in the local store at ~/.cogito/store by default, not in the temporary demo directory. fidelis recall-hybrid also queries that same running server and searches the whole shared store, so its results can include notes you saved earlier, not only the demo note. The watcher also records ingested files in ~/.fidelis/watched.json. To remove the default service on macOS, run fidelis init --uninstall; it stops the service and deletes the launchd plist only. On Linux, find the installed unit with systemctl --user list-unit-files '*fidelis-server*', then run systemctl --user disable --now <unit>, delete that unit file from ~/.config/systemd/user/, and run systemctl --user daemon-reload. Neither path deletes your data. The store is shared by everything you save with Fidelis, so deleting ~/.cogito/store erases all of it, not just the demo note; do that only on a throwaway install. Also delete the temporary demo directory ($demo_dir), and ~/.fidelis/watched.json if you want its record of the file path gone.
Connect an agent
Once the note is retrievable locally, install the MCP connection for your client:
Restart the client and try: “Use Fidelis to find my Atlas billing migration note. What must happen before we retry? Quote the relevant text.”
The client gets tools to recall, store, correct, fetch, and inspect memory. It decides when to call them; installing the connection does not make every turn recall automatically. Other clients and uninstall commands include Cursor, Gemini CLI, Copilot CLI, and OpenClaw. A separate Pi extension provides prompt-time recall.
What Fidelis preserves
- Original wording.
watch,store, and other verbatim write paths keep the text you supplied, so retrieval can return the condition that a summary might omit. - Local retrieval. Fast vector search is the default MCP recall path. Explicit hybrid search combines keyword and vector results without a generative LLM at its
zero_llmtier; local embeddings still require Ollama. - Corrections over time. A correction can supersede a prior record without erasing it. Recall can show validity and historical status instead of silently replacing the old note.
Fidelis also has optional extraction and model-assisted routes. Those can transform or filter inputs; use the verbatim path when the original wording is the point. Retrieved text can still be wrong or out of date, and your agent's model provider may see it when answering.
Current scope
Fidelis 0.3.0rc1 is a single-machine pre-release, not a hosted team memory service. The LongMemEval-S retrieval run measured whether the redesigned default path retrieved material across 470 questions; it did not measure answer accuracy. See the results, user-fit guide, and security policy for deeper detail.
Full reference · Upgrade notes · Contribute · Changelog
Apache-2.0. Hermes Labs builds agentic infrastructure for autonomous systems.
來源:README.md,提交 9504c4a
工具
0版本歷史
2- v0.2.0最新Sep 20, 2026
- v0.1.0Sep 16, 2026
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