13 KiB
YAMS - Yet Another Memory System
Persistent memory for LLMs and applications. Content-addressed storage with deduplication, semantic search, and full-text indexing.
Features
- Content-Addressed Storage - SHA-256 based, ensures data integrity
- Deduplication - Block-level with Rabin fingerprinting
- Compression - Zstandard and LZMA with intelligent policies
- Search - Full-text (SQLite FTS5) and semantic (vector embeddings)
- Crash Recovery - Write-ahead logging for durability
- High Performance - 100MB/s+ throughput, thread-safe
Build
Requirements
- C++20 compiler (GCC 11+, Clang 14+)
- CMake 3.20+
- OpenSSL 3.0+
- SQLite3
- Protocol Buffers 3.0+
Dependencies
macOS
brew install cmake openssl@3 protobuf sqlite3
export OPENSSL_ROOT_DIR=$(brew --prefix openssl@3)
Linux
# Ubuntu/Debian
apt install build-essential cmake libssl-dev libsqlite3-dev protobuf-compiler
# Fedora/RHEL
dnf install cmake openssl-devel sqlite-devel protobuf-compiler
Build Profiles
Quick Start - Release Build
For end users who just want the CLI and MCP server:
mkdir build && cd build
cmake -DYAMS_BUILD_PROFILE=release ..
make -j$(nproc)
sudo make install
# Installs: yams, yams-mcp-server
Note: If you encounter WebSocket compilation errors, build without MCP server:
cmake -DYAMS_BUILD_PROFILE=custom -DYAMS_BUILD_MCP_SERVER=OFF ..
Development Build
For developers who need everything including tests:
mkdir build && cd build
cmake -DYAMS_BUILD_PROFILE=dev ..
make -j$(nproc)
ctest --output-on-failure
Build Options
| Option | Default | Description |
|---|---|---|
YAMS_BUILD_PROFILE |
custom | Preset: release, dev, or custom |
YAMS_BUILD_CLI |
ON | Build command-line interface |
YAMS_BUILD_MCP_SERVER |
ON | Build MCP server |
YAMS_BUILD_MAINTENANCE_TOOLS |
OFF | Build gc and stats tools |
YAMS_BUILD_TESTS |
OFF | Build unit tests |
YAMS_BUILD_BENCHMARKS |
OFF | Build performance benchmarks |
CMAKE_BUILD_TYPE |
Release | Build type: Debug, Release, RelWithDebInfo |
Setup
# Initialize with XDG defaults (non-interactive)
yams init --non-interactive
# Optional: custom storage root
export YAMS_STORAGE="$HOME/.local/share/yams"
yams init --non-interactive
# Print resulting config (secrets masked)
yams init --non-interactive --print
LLM Integration Guide
YAMS is designed to work seamlessly with Large Language Models through simple, pipeline-friendly commands:
# Store conversation context
echo "User asked about X, I explained Y" | yams add -
# Store code snippets
echo "def function(): return 42" | yams add -
# Retrieve previous context
yams list --format minimal | tail -5 | while read hash; do
yams get $hash
done
# Search for relevant content
yams search "error handling" --format json
# Chain commands
yams list --format minimal | \
grep -v manifest | \
head -10 | \
xargs -I {} yams get {} > combined.txt
Best Practices for LLMs
-
Use stdin for content storage: Avoids file creation
echo "content to store" | yams add - -
Use minimal format for piping: Clean output for processing
yams list --format minimal | head -5 -
Explicit data directory: Always specify storage location
yams --data-dir /tmp/project-memory add - -
JSON for structured data: Parse responses easily
yams stats --format json | jq '.totalObjects' -
Direct stdout retrieval: No intermediate files
yams get <hash> | process_somehow
Usage
MCP Server
Start the MCP server over WebSocket:
yams serve --transport websocket --host 127.0.0.1 --port 8080 --path /mcp
Use TLS (wss):
yams serve --transport websocket --host your.domain --port 443 --path /mcp --ssl
StdIO transport (recommended for local integration and Claude Desktop):
yams serve --transport stdio
Claude Desktop (MCP) Integration
Use stdio (recommended). Add this to your Claude Desktop config (e.g., ~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"yams": {
"command": "/usr/local/bin/yams",
"args": ["serve", "--transport", "stdio"],
"env": {
"YAMS_STORAGE": "$HOME/.local/share/yams"
}
}
}
}
Alternative (WebSocket) for clients that support ws:
{
"mcpServers": {
"yams-ws": {
"command": "/usr/local/bin/yams",
"args": ["serve", "--transport", "websocket", "--host", "127.0.0.1", "--port", "8080", "--path", "/mcp"],
"env": {
"YAMS_STORAGE": "$HOME/.local/share/yams"
}
}
}
}
CLI Usage
Initialize Storage
# One-time setup with defaults
yams init --non-interactive --no-keygen
# Custom storage location
yams --data-dir /path/to/storage init --non-interactive
Store Documents
# Add a file
yams add file.txt
# Add from stdin
echo "content" | yams add -
cat file.txt | yams add -
# Add multiple files
find . -name "*.txt" -exec yams add {} \;
List Documents
# Table format (default)
yams list
# JSON output for programmatic use
yams list --format json
# Just hashes for piping
yams list --format minimal
# Sort and filter
yams list --sort size --reverse --limit 10
yams list --sort date
Retrieve Documents
# Output to stdout
yams get <hash>
# Save to file
yams get <hash> -o output.txt
# Pipe to other commands
yams get <hash> | grep pattern
yams get <hash> | wc -l
# Get first document from list
yams list --format minimal --limit 1 | xargs yams get
Browse Documents (TUI)
# Launch ranger-style browser
yams browse
# Navigation:
# j/k or ↑/↓ - Move up/down
# h/l or ←/→ - Switch columns
# g/G - Jump to top/bottom
# d then D - Delete document
# r - Refresh
# ? - Help
# q or Esc - Quit
Search
yams search "query" --limit 10 yams search "error" --type "log"
Retrieve
yams get yams get --output file.txt
List & Stats
yams list --recent 20 yams stats --json # JSON output for scripts
Browse (interactive TUI)
yams browse # Interactive document browser
### API
```cpp
#include <yams/api/content_store.h>
auto store = yams::api::createContentStore(getenv("YAMS_STORAGE"));
// Store
yams::api::ContentMetadata meta{.tags = {"code", "v1.0"}};
auto result = store->store("file.txt", meta);
// Search
auto results = store->search("query", 10);
// Retrieve
store->retrieve(hash, "output.txt");
Python
import subprocess, json
def yams_store(content, tags=[], type="text"):
cmd = ["yams", "store", content]
if tags: cmd.extend(["--tags", ",".join(tags)])
if type: cmd.extend(["--type", type])
return subprocess.run(cmd, capture_output=True, text=True)
def yams_search(query, limit=10):
cmd = ["yams", "search", query, "--limit", str(limit)]
return subprocess.run(cmd, capture_output=True, text=True)
LLM Usage Guide
Quick Start for LLMs
# Always specify data directory explicitly
export YAMS_STORAGE="/tmp/yams-data"
# Initialize once (quiet mode)
yams --data-dir "$YAMS_STORAGE" init --non-interactive --force
# Store content from stdin (most common for LLMs)
echo "Important information to remember" | yams --data-dir "$YAMS_STORAGE" add --tags "memory"
# Search for content
yams --data-dir "$YAMS_STORAGE" search "important" --json
# Retrieve specific document
yams --data-dir "$YAMS_STORAGE" get <hash> --json
# Get storage statistics
yams --data-dir "$YAMS_STORAGE" stats --json
Best Practices for LLMs
- Always use explicit paths: Use
--data-dirto avoid ambiguity - Use JSON output: Add
--jsonflag for structured data - Prefer stdin input: Pipe content directly instead of creating temp files
- Use simple commands:
add,search,get,statsinstead of complex TUI commands - Tag consistently: Use descriptive tags like "code", "config", "memory", "context"
Common Patterns
# Store code changes
git diff | yams --data-dir "$YAMS_STORAGE" add --tags "git-diff,$(date +%Y%m%d)"
# Store conversation context
echo "User asked about: $TOPIC" | yams --data-dir "$YAMS_STORAGE" add --tags "context,$TOPIC"
# Store external documentation
curl -s "$API_DOCS_URL" | yams --data-dir "$YAMS_STORAGE" add --tags "api-docs,external"
# Search and retrieve in one line
hash=$(yams --data-dir "$YAMS_STORAGE" search "$QUERY" --json | jq -r '.results[0].hash')
yams --data-dir "$YAMS_STORAGE" get "$hash"
LLM Integration
When to Use YAMS
YAMS is ideal for LLMs to maintain persistent memory across sessions:
- Code Development: Track changes, store working versions, remember context
- Research: Cache web content, API responses, documentation
- Conversation Context: Store important discussions, decisions, requirements
- Knowledge Base: Build searchable repository of project knowledge
CLI Usage Examples
Development Workflow
# Store current code state before making changes
git diff | yams store - --tags "pre-refactor,auth-module,$(date +%Y%m%d)"
# Track implementation decisions
yams store "Decided to use JWT tokens with 24h expiry for auth" \
--tags "decision,auth,architecture"
# Store error context for debugging
yams store "$(tail -100 app.log)" --tags "error,production,$(date +%Y%m%d-%H%M)"
# Save working implementation
yams store-file auth_handler.py --tags "working,auth,v2.1"
Research & Documentation
# Store web research
curl -s https://api.example.com/docs | yams store - \
--tags "api-docs,external,example-api" \
--source "https://api.example.com/docs"
# Cache fetched content
yams store "$WEB_CONTENT" --tags "research,oauth,implementation-guide"
# Store meeting notes
yams store-file meeting-notes-2024-01-15.md --tags "meeting,requirements,client"
Search Patterns
# Find related code changes
yams search "authentication" --type "code" --limit 10
# Retrieve specific version
yams search "working auth" --tags "v2.1"
# Get recent errors
yams list --recent 20 --tags "error"
# Semantic search for concepts
yams search "token expiry handling"
MCP (Model Context Protocol) Integration
MCP provides direct integration with Claude Desktop and other MCP-compatible clients.
When to Use MCP vs CLI
Use MCP when:
- Working in Claude Desktop or MCP-enabled environment
- Need real-time memory access during conversations
- Want automatic context persistence
- Building knowledge bases incrementally
Use CLI when:
- Scripting or automation needed
- Working with git hooks or CI/CD
- Batch processing files
- Integration with existing tools
MCP Server Setup
- Install MCP Server:
# Clone and build MCP server
cd tools/mcp-server
npm install
npm run build
- Configure Claude Desktop:
Add to
~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"yams": {
"command": "/path/to/yams/mcp-server",
"args": ["--storage", "$HOME/yams"],
"env": {
"YAMS_STORAGE": "$HOME/yams"
}
}
}
}
- MCP Usage Examples:
// Store via MCP
await mcp.store({
content: "Implementation details...",
tags: ["feature", "auth"],
metadata: { version: "2.1" }
});
// Search via MCP
const results = await mcp.search({
query: "authentication flow",
limit: 5
});
Architecture
yams/
├── include/yams/ # Headers
├── src/ # Implementation
├── tests/ # Unit tests
├── benchmarks/ # Performance
└── tools/ # CLI
Components
- Core - Types, error handling
- Storage - Content-addressed store
- Chunking - Content-defined chunking
- Compression - Multi-algorithm
- Metadata - SQLite with FTS5
- Search - Full-text and semantic
- WAL - Write-ahead logging
Development
# Debug build
cmake -DCMAKE_BUILD_TYPE=Debug ..
make -j
# Test
ctest --output-on-failure
# Coverage
cmake -DYAMS_ENABLE_COVERAGE=ON ..
make coverage
Troubleshooting
Build Issues
OpenSSL not found on macOS:
export OPENSSL_ROOT_DIR=$(brew --prefix openssl@3)
export PKG_CONFIG_PATH="$OPENSSL_ROOT_DIR/lib/pkgconfig"
Protobuf compilation errors:
# Ensure protoc is in PATH
which protoc
# Reinstall if needed
brew reinstall protobuf
Runtime Issues
Storage initialization fails:
# Check permissions
ls -la ~/yams
# Fix permissions
chmod -R 755 ~/yams
Search returns no results:
# Rebuild search index
yams reindex --full
# Check metadata database
yams stats --verbose
Performance Tuning
Optimize for large files:
# Adjust chunk size for better deduplication
export YAMS_CHUNK_SIZE=64KB # Default: 16KB
# Increase cache size
export YAMS_CACHE_SIZE=1GB # Default: 256MB
Reduce memory usage:
# Use streaming mode for large files
yams store-file --stream large-file.bin
# Enable compression
export YAMS_COMPRESSION=zstd # Options: none, zstd, lzma
License
Apache-2.0