About
Fully AI enabled personal management system
README
catalerum is a self-hostable, automated, fully-integrated LLM assistant, a catalogue of the things in your life.
This is my idea of a highly capable agentic workflow environment.

Goals
- fully integrated automated personal management system
- easy way to do ai native stuff and expose it via mcp servers
- ability to integrate the whole software in coding agents
Recipes
Run just to list every recipe:
| Recipe | What it does |
|---|---|
just up |
Start backing services + the echo llmleaf container and wait for store health. |
just dev |
Boot the API (migrates + seeds + prints the magic-link). |
just llmleaf |
Run the llmleaf proxy container with the echo config on :8088 (standalone). |
just web |
Serve the web workbench with trunk serve on :8080. |
just migrate |
Migrations run automatically on boot; this documents that path. |
just seed |
Admin + workspace + magic-link are seeded automatically on boot. |
just down |
Stop and remove the backing services. |
just reset |
Wipe volumes and recreate the dev stack. |
just test |
cargo test across the native workspace. |
just check |
cargo check --workspace --exclude catalerum-web. |
just check-web |
cargo check -p catalerum-web --target wasm32-unknown-unknown. |
just fmt / just lint |
Format / clippy (native + wasm web). |
just e2e / just mcp |
Placeholders wired up in later milestones. |
All-in-one container
For a single-node installation, the all-in-one bake target packages the
frontend, API/workers, terminal runner, preview service, llmleaf, Qdrant, and
same-origin routing into one image. It exposes only port 8080, uses SQLite and
an in-process coordination store, and provides one-time owner setup plus user
management. Neo4j is replaced by the relational graph fallback.
docker buildx bake all-in-one --load
docker run --rm -p 8080:8080 \
-v catalerum-data:/data -v "$PWD/files:/files" -v catalerum-work:/work \
registry.k3s.s.fionn-router.internal/catalerum/catalerum-all-in-one:dev
See docs/all-in-one.md for volumes, first boot, dynamic llmleaf providers, and the distinction from the existing distributed mode.
OpenTelemetry and Langfuse
Tracing is opt-in under [telemetry] in config/catalerum.toml. Catalerum can
export application, HTTP, and GenAI spans to a standard OTLP/HTTP collector,
directly to Langfuse, or to both at once. Incoming W3C traceparent headers are
honored and exporters flush on graceful process exit.
The OTLP and Langfuse destinations each have an independent LLM content policy:
metadata-only(default): model, latency, finish state, token/cache usage, cost, and errors; no prompts or generated content.all-except-system-prompts: full inputs/outputs with every system-role message removed.everything: full request, response, reasoning text, and tool payloads.
For Langfuse, enable [telemetry.langfuse] and inject
CATALERUM_TELEMETRY__LANGFUSE__PUBLIC_KEY and
CATALERUM_TELEMETRY__LANGFUSE__SECRET_KEY. The default endpoint is Langfuse
Cloud EU; set CATALERUM_TELEMETRY__LANGFUSE__ENDPOINT for another region or a
self-hosted instance. Generic OTLP is configured under [telemetry.otlp], with
optional static headers for authenticated collectors.
License
Licensed under either of
- Apache License, Version 2.0 (LICENSE-APACHE), or
- MIT License (LICENSE-MIT)
at your option.
Installing Catalerum
This server has no published package — it is built from source. Open the repository and follow its README.
▸ github.com/codefionn/catalerumFAQ
Is Catalerum MCP free?
Yes, Catalerum MCP is free — one-click install via Unyly at no cost.
Does Catalerum need an API key?
No, Catalerum runs without API keys or environment variables.
Is Catalerum hosted or self-hosted?
Self-hosted: the server runs locally on your machine via the install command above.
How do I install Catalerum in Claude Desktop, Claude Code or Cursor?
Open Catalerum on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
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