
EchoVault Memory
io.github.go-ports由 GitHub 帳號 go-ports 發布v0.3.3更新於 Oct 24, 2026
Local-first memory for coding agents; stores decisions, bugs, and context across sessions.
發布方自己的服務:Memory.fit
概覽
面向編碼代理的本地優先記憶伺服器,把決策、缺陷與上下文以 Markdown 保存在本機,並支援跨工作階段儲存、搜尋與重新載入。
- 可以做什麼
- 儲存記憶,包括標題、原因、影響、標籤與分類,並支援結構化詳情範本或詳情檔案,之後可依 ID 或前綴刪除。以關鍵字與可選語意向量混合搜尋記憶,並取得某筆結果的完整詳情。在工作階段開始時載入既有上下文,列出目前專案的記憶與工作階段檔案。讓 Claude Code、Cursor、Codex 與 OpenCode 共用一個記憶庫,並透過命令列管理記憶目錄與嵌入設定。
- 適用情境
- 當你希望編碼代理把決策、缺陷歷史與專案上下文從一個工作階段帶到下一個工作階段,又不依賴雲端服務時,適合安裝。若你同時使用多個代理並希望它們共用一個可用 Markdown 瀏覽的記憶庫,也很有用。
- 執行需求
- 以 stdio 作為本機程序執行;Go 版本是單一靜態二進位檔,從原始碼建置需要 C 編譯器,因為要連結 SQLite 函式庫。需先初始化記憶庫並安裝代理設定。環境變數 MEMORY_HOME 指定儲存目錄,應指向持久化儲存。語意搜尋可選用本機 Ollama,或在設定檔中填入 OpenAI 或 OpenRouter 的 API 金鑰。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 EchoVault 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
EchoVault — Go
Local memory for coding agents. Your agent remembers decisions, bugs, and context across sessions — no cloud, no API keys, no cost.
Install · Features · How it works · Commands
This is the Go port of EchoVault. It is a single static binary with no Python runtime dependency. The vault format and MCP interface are fully compatible with the Python version — you can switch between them without losing any memories.
Features
Works with 4 agents — Claude Code, Cursor, Codex, OpenCode. One command sets up MCP config for your agent.
MCP native — Runs as an MCP server exposing memory_save, memory_search, and memory_context as tools. Agents call them directly — no shell hooks needed.
Local-first — Everything stays on your machine. Memories are stored as Markdown in ~/.memory/vault/, readable in Obsidian or any editor.
Zero idle cost — No background processes, no daemon, no RAM overhead. The MCP server only runs when the agent starts it.
Hybrid search — FTS5 keyword search works out of the box. Add Ollama or OpenAI for semantic vector search.
Secret redaction — 3-layer redaction strips API keys, passwords, and credentials before anything hits disk. Supports explicit <redacted> tags, pattern detection, and custom .memoryignore rules.
Cross-agent — Memories saved by Claude Code are searchable in Cursor, Codex, and OpenCode. One vault, many agents.
Obsidian-compatible — Session files are valid Markdown with YAML frontmatter. Point Obsidian at ~/.memory/vault/ and browse your agent's memory visually.
Install
Pre-built binary
Download the latest release for your platform from the releases page and place the binary somewhere on your $PATH.
Build from source
CGO required. The binary links against
go-sqlite3andsqlite-vec, so a C compiler (gcc/clang) must be present. On macOS:xcode-select --install. On Debian/Ubuntu:apt install build-essential.
First run
That's it. memory setup installs the MCP server config automatically.
By default the config is installed globally. To install for a specific project:
Configure embeddings (optional)
Embeddings enable semantic search. Without them, you still get fast keyword search via FTS5.
Generate a starter config:
This creates ~/.memory/config.yaml with sensible defaults:
What each section does:
embedding— How memories get turned into vectors for semantic search.ollamaruns locally;openaiandopenroutercall cloud APIs.nomic-embed-textis a good local model for Ollama.context— Controls how memories are retrieved at session start.autouses vector search when embeddings are available, falls back to keywords.topup_recentalso includes recent memories so the agent has fresh context.
For cloud providers, add api_key under the provider section. API keys are redacted in memory config output.
Configure memory location
By default, EchoVault stores data in ~/.memory.
You can change that in two ways:
MEMORY_HOME=/path/to/memory(highest priority, per-shell/per-process)memory config set-home /path/to/memory(persistent default)
Useful commands:
memory config shows both memory_home and memory_home_source (env, config, or default).
The --memory-home global flag overrides everything for a single invocation:
Usage
Once set up, your agent uses memory via MCP tools:
- Session start — agent calls
memory_contextto load prior decisions and context - During work — agent calls
memory_searchto find relevant memories - Session end — agent calls
memory_saveto persist decisions, bugs, and learnings
The MCP tool descriptions instruct agents to save and retrieve automatically. No manual prompting needed in most cases.
You can also use the CLI directly:
For long details, use --details-file notes.md. To scaffold structured details automatically, use --details-template.
How it works
- Markdown vault — one file per session per project, with YAML frontmatter
- SQLite index — FTS5 for keywords, sqlite-vec for semantic vectors
- Compact pointers — search returns ~50-token summaries; full details fetched on demand
- 3-layer redaction — explicit tags, pattern matching, and
.memoryignorerules
Supported agents
All agents share the same memory vault at your effective memory_home path (default ~/.memory/). A memory saved by Claude Code is searchable from Cursor, Codex, or OpenCode.
Commands
Global flags
Uninstall
To also remove all stored memories: rm -rf ~/.memory/
Privacy
Everything stays local by default. If you configure OpenAI or OpenRouter for embeddings, those API calls go to their servers. Use Ollama for fully local operation.
License
MIT — see LICENSE.
來源:README.md,提交 cc0802b
工具
0版本歷史
1- v0.3.3最新Sep 16, 2026
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