@rvboris/opencode-mempalace

Persistent memory for OpenCode — zero config, visible results.

Your AI coding assistant forgets everything between sessions. This plugin fixes that. It silently saves what matters and finds it when needed — no extra prompts, no manual effort.

Русская версия

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What it does

Before every reply, the plugin searches your memory for relevant context. After every session, it quietly saves durable knowledge. You never have to say "remember this" — but when you do, it listens.

You: "What build tool does this project use?"
AI:  [searches memory] → "Bun. You decided that on April 10."

The result

• Answers informed by your past decisions, preferences, and project history
• No repeated explanations across sessions
• Privacy-first: secrets and private blocks are never stored
• Works entirely locally — no cloud, no API keys, no MCP server

Quick start

Prerequisites: OpenCode and Python 3.10+ with pip.

pip install mempalace
mempalace init ~/.mempalace/palace

Add to opencode.json:

{
  "plugin": ["@rvboris/opencode-mempalace"]
}

That's it. Memory search, autosave, and both tools are active immediately.

Features

Hidden retrieval

Before each answer, the plugin injects a search instruction so the model checks your memory first. No tool call noise in the chat — the context just appears.

Background autosave

On session idle, compaction, or close, the plugin mines the conversation transcript for durable facts and saves them to the right memory area automatically.

mempalace_memory — the one tool

Four modes, one interface:

Mode	Purpose
save	Store a preference, fact, or decision
search	Find relevant memory by query
kg_add	Add a structured fact to the knowledge graph
diary_write	Save a short work note

Examples:

mempalace_memory  mode: save  scope: user  room: preferences  content: Prefers concise responses.

mempalace_memory  mode: search  scope: project  room: decisions  query: build tool

mempalace_memory  mode: kg_add  subject: my-repo  predicate: uses  object: bun

mempalace_status — visible proof

Check whether the plugin is actually helping:

mempalace_status

Shows retrieval hit rate, last autosave outcome, memory previews, and cumulative counters. Use verbose: true for full detail.

TUI HUD — memory stats in your prompt

A compact session stats line appears in the OpenCode prompt area:

MEM hits 3 · saved 2 · failed 0 · writes 1

Color-coded indicators for SKIPPED and FAILED states. Requires a tui.json entry (see below).

Memory areas

User memory — cross-project preferences and habits:

• preferences — coding style, communication preferences
• workflow — working patterns, tool choices
• communication — language, response format

Project memory — repository-specific knowledge:

• architecture — design decisions, patterns
• workflow — build commands, CI config
• decisions — ADRs, trade-offs
• bugs — known issues, workarounds
• setup — environment setup, dependencies

Privacy

• <private>...</private> blocks are respected and never stored
• Common secrets (API keys, tokens, passwords) are redacted before writes
• Fully private content is skipped entirely

Configuration

Optional config file at ~/.config/opencode/mempalace.jsonc:

{
  "autosaveEnabled": true,
  "retrievalEnabled": true,
  "keywordSaveEnabled": true,
  "maxInjectedItems": 6,
  "retrievalQueryLimit": 5,
  "privacyRedactionEnabled": true
}

Environment variables:

Variable	Purpose
MEMPALACE_AUTOSAVE_ENABLED	Toggle background autosave
MEMPALACE_RETRIEVAL_ENABLED	Toggle hidden retrieval
MEMPALACE_KEYWORD_SAVE_ENABLED	Toggle keyword-triggered saves
MEMPALACE_PRIVACY_REDACTION_ENABLED	Toggle secret redaction
MEMPALACE_ADAPTER_PYTHON	Path to Python binary
MEMPALACE_ADAPTER_TIMEOUT_MS	Adapter timeout (default 15000)

TUI HUD setup

To enable the prompt-area stats display, add a tui.json in your OpenCode config directory:

{
  "$schema": "https://opencode.ai/tui.json",
  "plugin": [
    "file:///path/to/mempalace-autosave/plugin/tui/index.tsx"
  ]
}

Or when installed from npm, use the package entry:

{
  "$schema": "https://opencode.ai/tui.json",
  "plugin": ["@rvboris/opencode-mempalace/tui"]
}

How it works

User message
  → system hook injects "search memory first" instruction
  → model calls mempalace_memory [search]
  → results inform the answer

Session ends / idles
  → event hook mines transcript
  → Python adapter saves durable facts via MemPalace

The plugin uses a local Python bridge (bridge/mempalace_adapter.py) to communicate with MemPalace. It does not require the MemPalace MCP server.

Compatibility

Requirement	Version
OpenCode	latest
Python	3.10+
MemPalace	3.3+
OS	macOS, Linux, Windows

Project docs

• Changelog — release history
• Contributing — changelog rules

Local development

git clone https://github.com/rvboris/opencode-mempalace.git
cd opencode-mempalace/mempalace-autosave
npm install
npm run build

Load from source in opencode.json:

{
  "plugin": ["file:///ABSOLUTE/PATH/TO/mempalace-autosave/plugin/index.ts"]
}

Debug: opencode --log-level DEBUG or check ~/.mempalace/opencode_autosave.log.

Links

• OpenCode: https://opencode.ai
• MemPalace: https://github.com/milla-jovovich/mempalace
• npm: https://www.npmjs.com/package/@rvboris/opencode-mempalace

License

MIT