Configuration
MUR's configuration lives at ~/.mur/config.yaml. Run mur init for an interactive setup wizard.
Full Configuration Reference
# Semantic search / embedding
embedding:
provider: ollama # ollama | openai | gemini | anthropic
model: qwen3-embedding:0.6b # see Embedding Models below
dimensions: 1024 # must match model (set automatically by mur init)
ollama_endpoint: http://localhost:11434
# Pattern extraction LLM
llm:
provider: anthropic # anthropic | openai | gemini | ollama
model: claude-sonnet-4-20250514
api_key_env: ANTHROPIC_API_KEY
# openai_url: https://openrouter.ai/api/v1 # for OpenRouter
Model Registry (agents & cost router)
The models that agents and the cost router use live in a separate registry at ~/.mur/models.yaml, not in config.yaml. Manage it with the mur model commands rather than editing the file by hand:
mur model add gpt5 --provider openai --model gpt-5.2 --secret env:OPENAI_API_KEY
mur model list
Pricing (input/output USD-per-1k) and context window are auto-filled from the models.dev catalog. API keys are stored as SecretRefs (env: / keychain: / file: / cmd:), never in plaintext. The MUR Hub desktop app's Model Library offers a GUI: connect a cloud provider (key → macOS Keychain) or auto-detect a local runtime (Ollama / MLX / LM Studio), then pick which discovered models to register.
Embedding Models
Ollama (Free, Local — Recommended)
No API key needed, runs entirely on your machine:
# Pull your chosen model first
ollama pull qwen3-embedding:0.6b
| Model | RAM | Quality | Dimensions |
|---|---|---|---|
qwen3-embedding:0.6b | ~1.5GB | Good (recommended) | 1024 |
qwen3-embedding:4b | ~8GB | Better multilingual | 2560 |
qwen3-embedding:8b | ~16GB | Best (MTEB #1) | 4096 |
nomic-embed-text | ~300MB | Lightweight | 768 |
embedding:
provider: ollama
model: qwen3-embedding:0.6b
dimensions: 1024
OpenAI
Low cost (~$0.001 per 200 patterns):
embedding:
provider: openai
model: text-embedding-3-small
dimensions: 1536
api_key_env: OPENAI_API_KEY
After changing embedding config, rebuild the index:
mur reindex
LLM Providers
MUR uses an LLM for pattern extraction (mur learn extract) and contradiction detection (mur feedback auto).
Cloud providers
llm:
provider: anthropic # or openai, gemini
model: claude-sonnet-4-20250514
api_key_env: ANTHROPIC_API_KEY
OpenRouter (access to many models)
llm:
provider: openai
model: google/gemini-2.5-flash
api_key_env: OPENROUTER_API_KEY
openai_url: https://openrouter.ai/api/v1
Ollama (free, local)
llm:
provider: ollama
model: llama3.2:3b
File Locations
| Path | Purpose |
|---|---|
~/.mur/config.yaml | Main configuration |
~/.mur/patterns/ | Pattern YAML files (source of truth) |
~/.mur/workflows/ | Workflow YAML files |
~/.mur/index/ | LanceDB vector index (rebuildable) |
~/.mur/sessions/ | Session recordings |
See Also
- Semantic Search — Deep dive into search configuration
- Commands — Full command reference