Palace gives Claude Code, Codex, Cursor, Gemini CLI, VS Code, OpenCode,
Cline, Zed, Goose, Windsurf, and Claude Desktop a memory that
lasts between sessions. It stores what happened verbatim, recalls it
automatically when it's relevant, and cites where each answer came from.
You: why did we switch the queue to SQLite last month?
Agent: [palace_search → wing my_api, room decisions, filed 2026-09-03]
You dropped Redis because the deploy target had no persistent volume.
The benchmark you ran is in the same drawer.
Local-first memory for coding agents — MCP server, single SQLite file, local embeddings
MIT
पिछली जाँच
2026-11-15
स्टार
10
टूल
—
अपटाइम
—
🧭 Why Palace
Every new agent session starts with no memory. You explain the architecture
again. The agent repeats a fix you rejected last week. It greps the whole repo
to rediscover a convention you settled months ago.
Palace fixes that by:
Storing text verbatim. Code, notes, and conversations are stored as
written, not as an LLM summary that loses detail.
Running locally. Embeddings come from all-MiniLM-L6-v2 on ONNX
Runtime, on your CPU. Nothing leaves your machine unless you turn on
remote mode.
Recalling without being asked. Hooks inject relevant memory when a
session starts, when you send a prompt, and while the agent investigates.
The agent does not need to remember to search.
Citing sources. Every result carries its wing, room, source file, drawer
id, and score breakdown, so you can check where an answer came from.
Shipping as one binary. No Python, no vector database, no Docker. One
palace executable and one palace.db file.
It also works outside software projects. The creative and personalprofiles adapt it for worldbuilding, fiction, coaching, or
household notes.
📦 Install
Pick one. Each method installs the palace binary. Run palace install
afterwards to connect your agents.
macOS / Linux
curl -fsSL https://raw.githubusercontent.com/AncientiCe/palace-rs/main/scripts/install.sh | sh
The scripts download the matching GitHub Release binary, verify its SHA-256
checksum, and install it. To upgrade later, run the same command again.
Homebrew (macOS Apple Silicon / Linux)
brew tap AncientiCe/palace
brew install palace
To upgrade, refresh the tap first. Without brew update, Homebrew can keep
reporting the old version as already installed:
brew update && brew upgrade palace
When a release changes the memory protocol rule (the CHANGELOG says so), run
palace install again afterwards so your agents get the new rule text.
MCP registry / MCPB bundle. Palace is listed in the official
MCP registry as
io.github.ancientice/palace-rs. Each release also ships a palace-<version>.mcpb
bundle (Linux x86_64, macOS arm64, Windows x86_64) for one-click install in
MCPB-aware hosts such as Claude Desktop.
From source
git clone https://github.com/AncientiCe/palace-rs && cd palace-rs
cargo build --release # binary at target/release/palace
Platform
Status
Linux x86_64
Supported
macOS Apple Silicon
Supported
Windows x86_64
Supported
macOS Intel
Not supported (no ONNX Runtime build)
The embedding model (~90 MB) downloads from Hugging Face the first time you
mine or search, then stays cached in ~/.cache/huggingface.
⚡ Quick start
palace install # connect every supported agent on this machine
palace doctor # check that every client is wired up
palace init ~/my-project --yes --auto-mine # detect rooms, write palace.yaml, mine
Restart your agent app so it reloads its MCP config. Then try:
"What do we know about how this project handles database migrations?"
The agent should call palace_search and answer from memory, citing the
drawer it used. You can also search from the terminal:
palace search "how did we decide on the database schema"
From then on, the agent writes a diary entry after substantial work and stores
durable decisions as facts. Tomorrow's session, from any of your agents, picks
up where today's left off.
🔍 How it works
The palace
Memory is organised like a building, which keeps search focused:
Figure 1. One palace holds many wings. Rooms group drawers, and the knowledge graph and diaries sit alongside them.
Concept
What it is
Example
Wing
A project or a topic
my_api, sales_notes
Room
An area inside a wing
backend, testing, decisions
Drawer
One chunk of verbatim text plus its embedding and metadata
a paragraph of db.rs, a diary entry
Knowledge graph
Time-stamped facts: subject → predicate → object
my_api → uses_queue → SQLite (valid from 2026-09-03)
Diary
Per-agent session notes for continuity
"Fixed the flaky migration test by…"
Tunnel
A link between rooms in different wings
my_api/auth ↔ my_web/login
Wings are either project wings (a folder on disk, created by palace mine)
or topic wings (no folder, such as chat history or meeting notes, created
with palace_create_wing).
Retrieval
flowchart LR
Q["💬 Question<br/>from you or the agent"] --> S["Sanitize<br/>strip pasted dumps"]
S --> I["Classify intent<br/>decision · how_to · preference …"]
I --> H["Hybrid search<br/>BM25 + cosine"]
H --> B["Coding boosts<br/>+ preference pass"]
B --> R{"Rerank?<br/>optional"}
R --> OUT["📎 Results<br/>scores + source + neighbours"]
DB[("palace.db<br/>local embeddings")] -.-> H
Figure 2. What happens to a query. Everything runs locally on your CPU.
Search fuses BM25 keyword scoring with cosine similarity over local
embeddings. It then applies intent boosts for coding questions. Each query is
classified as preference, decision, how_to, definition, temporal, or
unknown. Preference-shaped questions ("how do I like my commits?") get a
dedicated pass against tagged preference spans. A local cross-encoder
reranker is available as an option (--rerank or PALACE_RERANK=1).
Agent-generated query dumps are cleaned up before retrieval. Results come back
with score provenance (combined, cosine, bm25, coding_boost,
preference_match, rerank_score, intent) and the neighbouring chunks from
the same source file.
Automatic recall (hooks)
palace install registers user-level hooks, so memory works in every project
without editing per-project files:
Figure 3. Three hooks read memory into the session. The fourth makes sure the session's lessons get written back.
Hook
What it does
Session start
Injects the memory protocol, your standing rules from general/preferences (verbatim, in every project), recent diary entries for this project (from any agent), and the top drawers of the project's wing.
Prompt submit
Searches Palace with your actual question and injects matching drawers before the agent answers. If a history question finds nothing, it tells the agent to run palace_search. In Claude Code it also adds a one-line reminder until the session calls a Palace tool. Skips short prompts and slash commands. Claude Code and Codex only.
Post tool use
While the agent greps and reads files, recalls related memory so earlier decisions surface without a search. In Claude Code it also records the session's Palace calls.
Stop
If the session did real work but saved nothing, asks the agent once to write a diary entry and record decisions before it finishes. In Claude Code this is judged per session, including sessions that never used Palace; other agents use a recent-activity window.
Auto-recall is limited to the current project. Drawers from your other
project wings and diaries from other projects stay out. Topic wings still
appear.
All hooks fail open: if the palace is missing or empty, the agent works as
normal.
The memory protocol
palace install also writes a short rule into each client's instruction file.
The rule tells the agent when to use memory:
Before answering a question about past decisions, preferences, or
history: palace_search and palace_kg_query, before grep.
After work:palace_diary_write, plus palace_kg_add for durable facts.
Grep remains the right first tool for current symbols, exact definitions, and
code that may have changed since it was mined.
The nine protocol tools are marked _meta."anthropic/alwaysLoad" = true, so
Claude Code 2.1.121 and later keeps them loaded instead of deferring them
behind tool search.
Top drawers by importance, grouped by room (~600–900 tokens)
L2
On demand
Wing- and room-filtered retrieval
L3
Deep search
Full hybrid search across the palace
palace wake-up prints L0 and L1. Agents reach L2 and L3 through MCP tools.
🔌 Supported clients
palace install configures every supported client by default
(--client all). Gemini CLI, VS Code, Windsurf, OpenCode, Cline, Zed and
Goose are included only when their config folder exists, so Palace never sets up an agent you don't
have. Use --client <name> to configure one explicitly.
Client
--client
MCP config
Rule file
Hooks
Claude Code
claude
~/.claude.json
~/.claude/CLAUDE.md
~/.claude/settings.json
Codex
codex
~/.codex/config.toml
~/.codex/AGENTS.md
~/.codex/hooks.json (run /hooks once in the Codex CLI to trust them)
Cursor
cursor
~/.cursor/mcp.json
~/.cursor/rules/palace.mdc
~/.cursor/hooks.json
Gemini CLI
gemini
~/.gemini/settings.json
~/.gemini/GEMINI.md
~/.gemini/settings.json (run only in folders you trust in Gemini)
VS Code (Copilot)
vscode
Code/User/mcp.json
Code/User/prompts/palace.instructions.md
~/.copilot/hooks/palace.json (no prompt-time recall: VS Code can't inject there)
OpenCode
opencode
~/.config/opencode/opencode.json
~/.config/opencode/palace.md, listed under instructions
~/.config/opencode/plugins/palace.js
Cline
cline
~/.cline/data/settings/cline_mcp_settings.json
~/.cline/rules/palace.md
Documents/Cline/Hooks (prompt and post-tool recall; Cline can't continue after a task, so no save nudge). Your own hook scripts are never overwritten.
Zed
zed
Zed settings.json (context_servers)
Zed's global AGENTS.md
None. Zed's agent has no hooks; external agents in Zed use their own Palace setup.
Goose
goose
Goose config.yaml (extensions)
Goose .goosehints
~/.agents/plugins/palace (save nudge only; Goose hooks can't inject context; needs sh on Windows)
Windsurf
windsurf
~/.codeium/windsurf/mcp_config.json
~/.codeium/windsurf/memories/global_rules.md
None. Cascade hooks can't inject context. Devin Local reuses the Claude Code hooks.
Rule files are written as a managed block. Your existing content is kept.
palace install --client claude # one client only
palace install --scope project --path ./my-project # project-level rule files
palace install --no-rule # MCP wiring only, no rule
palace install --dry-run # preview the changes
palace uninstall # undo everything
With --scope project, rules go to <project>/CLAUDE.md, <project>/AGENTS.md
(Codex, OpenCode, Cline, Zed and Goose), <project>/GEMINI.md, <project>/.github/copilot-instructions.md,
<project>/.windsurf/rules/palace.md, and <project>/.cursor/rules/palace.mdc.
Cursor, VS Code and OpenCode also get a project MCP config
(.cursor/mcp.json, .vscode/mcp.json, opencode.json).
Any MCP client can run Palace as a stdio server with palace mcp.
JSON clients (Claude Code, Cursor, Claude Desktop):
Claude Desktop cannot run hooks, so the server offers two prompts in its
prompt picker:
Prompt
What it does
continue-session
Loads warm-start context so the agent picks up where you left off
save-session
Saves the session to memory so it carries over next time
Profiles
A profile changes the agent rule, the protocol text, and which rooms
palace init looks for:
Profile
For
Typical rooms
coding (default)
Software projects
frontend, backend, testing, docs, config
creative
Worldbuilding, D&D, fiction
characters, places, lore, factions, timeline
personal
Coaching, caregiving, household, client notes
people, health, finances, home, schedule
palace install --profile creative
The profile is saved to ~/.palace/config.json. Set PALACE_PROFILE to
override it for one process.
Remote mode (shared team memory)
By default, palace mcp serves your local palace. Remote mode turns it into a
stdio-to-HTTP bridge to a shared Palace Server,
the commercial, self-hosted team edition. Client registrations do not change.
palace remote set --endpoint https://palace.yourco.com # prompts for the ps_… API key
palace remote on
palace remote test # runs the MCP handshake and reports the tool count
palace remote status # mode, endpoint, masked key
palace local # back to the local palace
🧰 CLI reference
Run palace <command> --help for every flag.
Setup
Command
What it does
palace install
Register the MCP server, rules, and hooks with your agents
palace uninstall
Remove them again
palace doctor
Check the binary, database, MCP configs, and rules
palace seed-adoption-facts
Seed knowledge-graph facts that make agent recall measurable
flowchart LR
DIR["📁 Your repo"] --> F["Filter<br/>.gitignore + skip build dirs"]
F --> C{"Changed since<br/>last mine?"}
C -- no --> SKIP["Skip"]
C -- yes --> CH["Chunk + pick room<br/>using palace.yaml"]
CH --> E["Embed locally<br/>all-MiniLM-L6-v2"]
E --> DB[("palace.db")]
Figure 4. Mining only touches files that changed, so re-running it is cheap.
palace mine respects .gitignore and skips .git, node_modules,
target, build, dist, vendor, and other build output. It reads common
text and source formats: md, txt, rs, py, js, ts, tsx, go,
java, rb, sh, sql, json, yaml, toml, html, css, csv, and
more.
palace mine ~/my-project \
--wing my_project # override the wing name
--limit 100 # process at most 100 new or changed files
--dry-run # preview without storing
--no-gitignore # ignore .gitignore rules
--include vendor,third_party # force-include these paths
--limit runs can be resumed: the next run continues from where the last
one stopped.
Measuring value with palace gain
palace gain # last 30 days
palace gain --project my_project --since 7d
palace gain --history # recent tool calls
palace gain --json
palace gain --record <query_id> <drawer_id> useful # or not_useful / wrong_answer
Search diaries. all_agents: true searches every agent's diary.
palace_session_context
Warm-start context. Falls back to other agents' recent work on the project.
palace_list_agents
List agent diaries
Internal
Tool
Description
palace_get_aaak_spec
The AAAK compressed-memory dialect spec
palace_hook_settings
Hook settings
palace_memories_filed_away
Acknowledgement used by the stop hook
🔧 Configuration
Settings load in this order: environment variables, then
~/.palace/config.json, then defaults.
Env var
Default
Description
PALACE_PALACE_PATH
~/.palace/palace
Data directory. The database is palace.db inside it.
PALACE_PROFILE
coding
coding, creative, or personal
PALACE_RERANK
off
1 turns on the local reranker for every search
PALACE_RERANK_MODEL
built-in
Override the reranker model
PALACE_ENTITY_LANGUAGES
en
Comma-separated languages for entity detection
PALACE_GAIN_DISABLED
off
1 turns off usage recording
PALACE_PROJECT
auto
Project name used for gain attribution
PALACE_SOURCE_DIR
~/Desktop/transcripts
Default source for palace split
PALACE_MINE_TRACE
off
1 prints per-stage mining timings
PALACE_MCP_MODE
local
local or remote
PALACE_REMOTE_ENDPOINT
none
Palace Server URL (host, base URL, or full /mcp URL)
PALACE_API_KEY
none
Palace Server API key (ps_…)
config.json takes the same settings as keys: palace_path, profile,
entity_languages, topic_wings, people_map, mcp_mode,
remote_endpoint, remote_api_key. Palace writes this file with owner-only
0600 permissions.
palace.yaml (per project)
palace init creates this file. Edit it to tune how files map to rooms:
wing: my_project
rooms:
- name: backend
description: Server and API code
keywords: [api, server, routes, models]
- name: frontend
description: UI components
keywords: [ui, components, pages, views]
- name: general
description: Everything else
keywords: []
📊 Benchmarks
Coding-agent memory eval
A fixture of realistic project memories (decisions, past failures, commands,
conventions, preferences, current direction) with 40 questions such as:
why did we choose bundled sqlite?
how did we fix the migration test failure last time?
what clippy command should I run?
cargo test --test coding_agent_eval -- --nocapture
The test reports recall@1 and recall@5, and fails if retrieval drops below
a fixed threshold. It answers the question that matters: can a coding agent
find the right project context when it needs it?
LongMemEval
Retrieval recall on LongMemEval s_cleaned: 470 evaluated questions, each
over a haystack of about 50 sessions and 115k tokens. The 30 abstention
questions are excluded, as is standard.
Split
R@1
R@5
R@10
longmemeval_oracle (sanity check)
1.000
1.000
1.000
longmemeval_s_cleaned
0.889
0.981
0.991
Granularity: one drawer per session, with user and assistant turns
embedded together. No filtering, summarisation, or LLM extraction.
Retrieval: BM25 (k1=1.5, b=0.75, weight 0.35) fused with cosine (weight
0.65), top-K 10. This run predates the coding-agent intent boosts.
No LLM at any stage, no per-dataset tuning, no GPU.
Metric:recall_any@K at session granularity.
Hardware: Apple M1 Pro, 32 GB RAM.
Question type
R@1
R@5
R@10
knowledge-update
0.944
1.000
1.000
multi-session
0.909
0.983
1.000
single-session-assistant
1.000
1.000
1.000
single-session-preference
0.633
0.867
0.933
single-session-user
0.922
1.000
1.000
temporal-reasoning
0.835
0.976
0.984
The oracle split only contains the gold sessions, so it checks the pipeline
rather than measuring retrieval. Most top-1 misses on s_cleaned are
near-misses at rank 2–5. Preference questions are the weakest category,
because "I prefer…" sentences rarely share keywords with the question. The
dedicated preference pass added since this run targets that gap.
🔒 Privacy and data
Everything is local by default. One SQLite file at
~/.palace/palace/palace.db. Embeddings are computed on your CPU.
Network access is limited to the one-time model download from Hugging
Face, and to your own Palace Server if you turn on remote mode.
No telemetry.palace gain statistics are written to your local
database only.
Back up with palace export, or copy palace.db.
Delete a single memory with palace_forget, or everything by removing
~/.palace.
Palace stores whatever you mine. Exclude secrets with .gitignore before you
mine a repository.
🩺 Troubleshooting
Problem
Fix
The agent never calls Palace
Run palace doctor, then fully restart the agent app. In the Codex CLI, run /hooks once to trust the hooks.
palace: command not found
Open a new terminal so PATH picks up the install directory, or run palace doctor with the full path.
No search results
Check palace status. If the project has no drawers, run palace init <dir> --yes --auto-mine.
Results are out of date
Run palace mine <dir> again (only changed files are processed), or keep palace watch <dir> running.
Model download fails
Check that huggingface.co is reachable, then retry. The model is cached after the first successful download.
Searches feel slow on first run
The first call loads the ONNX model. Later calls in the same session are fast.
Some drawers have no vectors
palace repair
❓ FAQ
No. After palace install, hooks inject relevant memory at session start, when
you send a prompt, and while the agent reads code. The installed rule tells the
agent to search memory before answering history questions and to save what it
learned afterwards.
Those files are instructions you write and maintain by hand, and every line is
loaded into every session. Palace is searchable memory that grows as you work:
only the parts relevant to the current question are recalled, and the same
memory is shared by Claude Code, Codex, Cursor, and Claude Desktop. Keep using
instruction files for rules; use Palace for history.
No. Storage, embeddings, and search all run locally. The only network calls
are the one-time model download from Hugging Face and, if you turn it on,
your own Palace Server in remote mode. See Privacy and data.
Searches typically take tens of milliseconds (palace gain shows your real
p50 and p95). The first call in a session loads the embedding model. Hooks fail
open, so a missing or broken palace never blocks the agent.
Re-running palace mine updates changed files. For facts, agents call
palace_kg_invalidate and add the new fact, so the timeline keeps both.
palace_conflicts flags facts that look stale or contradictory, and
palace_forget or palace prune removes drawers you no longer want.
Different agents on one machine already share it: a Codex session can pick up
a Claude Code session's diary. For a team, remote mode
points every palace mcp at a shared, self-hosted Palace Server.
No. The creative and personalprofiles tune Palace for
worldbuilding, fiction, coaching, caregiving, and household notes. Palace
reads Markdown and text files, so Claude Desktop users can install the MCPB
bundle and start without writing code.
📚 Using Palace as a library
Palace is also a Rust crate (palace). Add it as a git dependency:
use palace::{db, knowledge_graph, store};
let conn = db::open_in_memory()?;
store::add_drawer(&conn, "wing_code", "backend",
"We use SQLite with WAL mode for concurrent reads.",
None, "architecture.md", 0, "example", 4.0)?;
knowledge_graph::add_triple(&conn, "Palace", "stores_data_in", "SQLite",
Some("2026-04-01"), None, 1.0, None, None)?;
default-features = false leaves out the CLI dependencies. For the full
example, see examples/basic_usage.rs
(cargo run --example basic_usage). palace::palace::Palace::search_with_provenance returns
the same score details as the MCP tools.
Version 0.2.0 renamed the project from mempalace to palace. The 0.2.x line
kept the old names working with warnings. They were removed in 0.3.0.
To upgrade from 0.1.x, either install a 0.2.x release first and run
palace install, which migrates configs and moves ~/.mempalace to
~/.palace, or rename by hand: ~/.mempalace → ~/.palace,
mempalace.yaml → palace.yaml, MEMPALACE_* → PALACE_*, and the
mempalace_* MCP tools → palace_*. Hooks that ran mempalace mcp or
python -m mempalace.mcp_server should now run palace mcp.
The Rust version replaces ChromaDB plus SQLite with a single palace.db.
ChromaDB data cannot be converted, so re-ingest:
palace init ~/my-project --yes --auto-mine
palace mine-convos ~/Desktop/transcripts
palace status
identity.txt, people_map.json, and known_names.json in ~/.palace/ are
still compatible and are read automatically.
अभी टूल सूची नहीं है। रिमोट सर्वर को पहले हेल्थ चेक के बाद सूची मिलती है।
FAQ
सवाल
Palace कैसे इंस्टॉल करें?
इस पेज पर Cursor, Claude Desktop, Claude Code या VS Code के लिए stdio कॉन्फ़िग कॉपी करें। यह पब्लिशर का इंस्टॉल इस्तेमाल करता है, PlugMCP प्रॉक्सी नहीं।
क्या Palace के लिए API key चाहिए?
इस रिकॉर्ड में कोई ज़रूरी एनवायरनमेंट वेरिएबल दर्ज नहीं है।
Palace कौन सा ट्रांसपोर्ट इस्तेमाल करता है?
Palace stdio पर लोकल चलता है।
Palace की पिछली जाँच कब हुई थी?
पिछली जाँच 2026-11-15 को हुई। Local-first memory for coding agents — MCP server, single SQLite file, local embeddings
