Files
librefang-registry/plugins/mempalace-indexer
Evan 7881d327a5 refactor: migrate icon fields from emoji to lucide:<name> tokens (#63)
* refactor: migrate icon fields from emoji to lucide:<name> tokens

Every TOML manifest's `icon = "<emoji>"` line is replaced with
`icon = "lucide:<kebab-name>"` — a reference to a lucide-react icon,
which the librefang.ai site and dashboard render as crisp SVG. Reasons
for the switch:

- Emoji render very differently across OS/browser/font stacks; the
  registry catalog looked inconsistent from one row to the next.
- Five manifests (clip / creator / linkedin / reddit / twitter) had
  their icons stored as literal Python-style escape strings
  ("\\U0001F3AC") because the TOML parser upstream never decoded
  them. Switching away from emoji drops that class of bug entirely.
- As a drive-by, also decode the \\uXXXX accent escapes in the
  [i18n.fr] block of hands/creator/HAND.toml so "Créateur" shows
  up correctly.

87 files touched. example manifests left untouched (still "TODO").

* fix: backfill i18n name + drop the single-member email category

- Every existing [i18n.<lang>] block now has a `name` field. 60 files
  previously translated description but kept the English name
  implicitly — which rendered as "some English some Chinese" in the
  registry UI. Fill in the missing name from the English brand (or a
  known localized equivalent: DingTalk→钉钉, Feishu→飞书, Email→
  电子邮件 / メール / E-Mail / Correo / Courriel, and a handful of
  hands that have Chinese product names like 视频剪辑 Hand).
- channels/email.toml was the only item under category="email";
  reclassify it as "messaging" so the sub-category filter chip list
  on the category page isn't littered with singletons.

* feat(i18n): localize 76 agents/integrations/plugins into 7 languages

Adds full [i18n.zh], [i18n.zh-TW], [i18n.ja], [i18n.ko], [i18n.de],
[i18n.es], [i18n.fr] blocks with name + description to every manifest
that previously shipped English-only.

Coverage:
- 32 agents (academic-researcher, analyst, architect, assistant,
  code-reviewer, coder, customer-support, data-scientist, debugger,
  devops-lead, doc-writer, email-assistant, health-tracker,
  hello-world, home-automation, legal-assistant, meeting-assistant,
  ops, orchestrator, personal-finance, planner, recipe-assistant,
  recruiter, researcher, sales-assistant, security-auditor,
  social-media, test-engineer, translator, travel-planner, tutor,
  writer)
- 33 integrations (AWS, Azure, Bitbucket, Brave Search, Discord,
  Dropbox, Elasticsearch, Exa Search, Fetch, Filesystem, GCP, Git,
  GitHub, GitLab, Gmail, Google Calendar, Google Drive, Google Maps,
  Jira, Linear, Memory, MongoDB, Notion, PostgreSQL, Puppeteer, Redis,
  Sentry, Sequential Thinking, Slack, SQLite, Teams, Time, Todoist) —
  brand names kept as-is across all locales, only descriptions
  translated.
- 11 plugins (auto-summarizer, context-decay, conversation-logger,
  episodic-memory, guardrails, keyword-memory, mempalace-indexer,
  sentiment-tracker, todo-tracker, topic-memory, user-profile)

The descriptions are one-line summaries — hand-translated rather than
machine-generated, so technical terms (MCP, PR, CI/CD, etc.) stay
consistent across locales.

* feat(i18n): close remaining per-lang gaps for channels, workflows, devteam

Third pass on i18n coverage. Every non-example manifest now carries a
full set of [i18n.zh], [i18n.zh-TW], [i18n.ja], [i18n.ko], [i18n.de],
[i18n.es], [i18n.fr] blocks.

- 44 channel adapters: added French descriptions (zh/zh-TW/ja/ko/de/es
  were already present). Brand names kept as-is in all locales so users
  recognize Discord / Slack / LINE / etc. consistently.
- 22 workflows: filled zh-TW / ja / ko / de / es / fr blocks. Each
  translation mirrors the existing zh one in structure and tone so the
  catalog reads consistently across locales.
- hands/devteam/HAND.toml: added the four langs that were missing
  (zh-TW, de, es, fr).

Only the 6 templates under examples/ are left without i18n blocks on
purpose — they still contain "TODO:" placeholders.
2026-04-17 22:04:26 +09:00
..

mempalace-indexer

LibreFang plugin for persistent, local semantic memory via MemPalace. No API keys, no cloud.

Quick start

librefang plugin install mempalace-indexer
librefang plugin requirements mempalace-indexer

mempalace init /path/to/workspace --yes
mempalace mine /path/to/workspace

Restart the daemon. Done.

Hooks

Hook When What
ingest Message arrives Searches palace for relevant memories, injects into context
after_turn After LLM responds Auto-saves memorable turns with dedup + classification
prune On demand / scheduled Deletes drawers older than MEMPALACE_MAX_AGE_DAYS

How after_turn saves

Five filters run before writing to the palace:

  1. MCP dedup — skip if the agent already called mcp_mempalace_add_drawer this turn
  2. Length — skip exchanges under MEMPALACE_MIN_CHARS (default 80)
  3. Relevance — English text must match keywords (decisions, appointments, contacts, etc.); non-English passes on length alone
  4. Content dedup — skip if a near-identical turn was already saved (SHA-256 hash store)
  5. Noise — code blocks are stripped; residual tool/error output is discarded

Matched turns are classified and written to the appropriate room:

Content type Wing Room
Contacts, email addresses, family people contacts
Appointments, meetings, reminders time calendar
Payments, invoices, expenses finance transactions
Packages, shipments logistics orders
Decisions, preferences knowledge decisions
Everything else default sessions

A single turn can match multiple rooms and will be written to all of them.

Configuration

All settings are optional environment variables:

Variable Default Description
MEMPALACE_PALACE_PATH ~/.mempalace/palace Palace directory
MEMPALACE_MIN_CHARS 80 Minimum text length to save
MEMPALACE_WINDOW_SIZE 6 Recent messages to consider
MEMPALACE_DEDUP_MAX 500 Hash store rolling cap
MEMPALACE_LANG_DETECT 1 Set to 0 to disable language detection
MEMPALACE_MAX_CHARS 300 Max characters per injected memory snippet
MEMPALACE_MIN_SIMILARITY 0.3 Min similarity score for ingest results (0 = disabled)
MEMPALACE_N_RESULTS 5 Number of memories to inject per turn
MEMPALACE_MAX_AGE_DAYS 90 Prune drawers older than this (0 = disabled)

MCP server (optional)

Add 19 explicit memory tools to all agents:

[[mcp_servers]]
name = "mempalace"
timeout_secs = 60
[mcp_servers.transport]
type = "stdio"
command = "python3"
args = ["-m", "mempalace.mcp_server"]

Pruning

Run manually:

python3 ~/.librefang/plugins/mempalace-indexer/hooks/prune.py --dry-run
python3 ~/.librefang/plugins/mempalace-indexer/hooks/prune.py

Or trigger via the LibreFang hook system on a schedule.