Getting Started
August 5, 2026 ยท View on GitHub
Install
curl -fsSL https://raw.githubusercontent.com/codecoradev/uteke/main/install.sh | sh
See the Installation guide for all methods (Cargo, binary, Docker).
๐ก First run downloads the embedding model (~188MB). No API keys needed.
Interactive Onboarding
New to uteke? Run the onboarding wizard โ it detects your install, configures extraction, tests your memory system, and introduces Rooms:
uteke onboard
Non-interactive mode (use defaults, skip prompts):
uteke onboard --yes --agent hermes --namespace default
The wizard covers:
- Install detection โ checks if
utekeis on PATH and if a store exists - Agent selection โ Hermes, Claude, Cursor, Pi, or OpenCode
- Integration mode โ manual tool (explicit calls) vs memory-provider (auto recall + extraction)
- Namespace โ for multi-agent isolation
- Extraction configuration โ choose offline (rule-based, zero API), external LLM (OpenAI-compatible), or manual-only
- Feature toggles โ Aging, Auto-maintenance, Graph rerank, Salience/Recency boost, Server mode
- Config write โ generates
~/.codecora/uteke/uteke.tomlwith your choices - Agent init โ runs
uteke init --agent <your-choice>automatically - Memory system test โ stores and recalls a test memory to verify everything works
- Rooms intro โ optionally creates your first Room for multi-agent memory sharing
- Feature showcase โ prints all uteke commands grouped by category
Your First Memory
# Store a memory with metadata enrichment
uteke remember --tags project "My app uses SvelteKit 5 with Tailwind" \
--entity my-app --category frontend
# Hybrid search (vector + FTS5, ranked by RRF)
uteke recall "What frontend framework do I use?"
# Filter by entity or category
uteke recall "frontend" --entity my-app
uteke list --category frontend
# Text search with tag filter
uteke search "SvelteKit" --tags project
# List all memories
uteke list
# Check system health
uteke doctor
Tag Management
# List all tags with usage counts
uteke tags list --by-count
# Rename a tag across all memories
uteke tags rename old-name new-name
# Delete a tag from all memories
uteke tags delete unused-tag
Multi-Agent Isolation
Each agent gets its own namespace. Memories never leak between agents:
# Agent "architect" stores its context
uteke --namespace architect remember "We chose PostgreSQL for ACID compliance"
# Agent "dev" has its own separate memory
uteke --namespace dev remember "Database connection string: postgres://localhost:5432/app"
# Each only sees its own memories
uteke --namespace architect recall "database"
uteke --namespace dev recall "database"
Recall Cache
The recall cache eliminates redundant embedding for repeated queries (~50ms savings). It's automatic โ no configuration needed. Use --context for AI-prompt formatted output:
# AI-optimized context output
uteke recall "api design" --context
Export & Import
Port your memories anywhere:
# Export to JSONL (no embeddings โ small, portable)
uteke export > memories.jsonl
# Import on another machine
uteke import memories.jsonl
# Import with LLM fact extraction (distills raw text into atomic facts)
uteke import notes.txt --extract
MCP Integration
Add uteke as an MCP server to your AI coding agent in seconds:
Claude Code โ add to .mcp.json:
{ "mcpServers": { "uteke": { "command": "uteke-mcp" } } }
With HTTP (requires uteke-serve):
{ "mcpServers": { "uteke": { "url": "http://127.0.0.1:8767/mcp" } } }
See MCP Server for all supported clients and tools.
๐ก Hermes users? Three integration modes available:
- Mode C (shell hook): Lightest โ automatic recall via
pre_llm_callhook, no plugin/daemon needed. See Hermes integration.- Mode B (memory-provider): Full auto โ
uteke init --agent hermes --memory-provider. Automatic recall + LLM fact extraction.- Mode A (uteke-tool): Manual โ
uteke init --agent hermes. Explicituteke(action="...")calls with multi-agent room support.The install script installs all three binaries (
uteke,uteke-serve,uteke-mcp) so MCP integration is available immediately.
Troubleshooting
If something goes wrong, uteke has built-in self-healing:
# Check system health (DB, index, model, consistency)
uteke doctor
# Verify DB and index consistency
uteke verify
# Repair index by rebuilding from SQLite
uteke repair
Where is Data Stored?
All data lives in ~/.codecora/uteke/:
~/.codecora/uteke/
โโโ uteke.db # SQLite (memories + metadata + FTS5)
โโโ uteke_index.usearch # Persistent HNSW vector index
โโโ uteke_index.keys # Index key mapping
โโโ embeddinggemma-q4/ # Local ONNX embedding model (~188MB)
โ โโโ onnx/ # model_q4.onnx + model_q4.onnx_data
โโโ logs/
โโโ uteke.log # Current log
โโโ uteke.log.YYYY-MM-DD # Rotated logs
Copy the entire folder to back up or transfer to another machine.
Next Steps
- Installation โ all install methods
- Rooms โ multi-agent shared memory with author attribution
- Time-Travel Queries โ recall memories at any point in time
- Smart Decay โ pinning, importance scoring, aging
- Relationship Graph โ link and traverse memories
- Benchmarks โ performance numbers
- Shell Hooks โ auto-load project context
- MCP Server โ AI agent integration
- CLI Reference โ complete command reference
- Configuration โ config file and options