# Osler > A native Mac canvas for AI agent workflows. Four node types, MCP tools, and local models via Ollama — no account, no cloud, no telemetry. - **Type:** MCP server - **Install:** `agentstack add mcp-albertofettucini-osler` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [albertofettucini](https://agentstack.voostack.com/s/albertofettucini) - **Installs:** 0 - **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [albertofettucini](https://github.com/albertofettucini) - **Source:** https://github.com/albertofettucini/Osler ## Install ```sh agentstack add mcp-albertofettucini-osler ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # Osler Design AI agent workflows on a canvas, on your Mac. Drop nodes, wire them into a flow, hit Run — the graph executes and every node's output streams in live. No Docker, no web stack, no account, no subscription, no telemetry. Everything runs on your machine and everything stays there. With [Ollama](https://ollama.com) it runs without an API key at all. ## Four node types That's the point. The whole vocabulary is: - **Input** — the starting text. - **Agent** — a system prompt and a model. Takes the incoming text, calls the LLM, streams text out. Can call MCP tools. - **Condition** — routes to a `yes` or `no` branch, either by keyword or by asking a model a yes/no question. - **Output** — shows the final text. Branches that don't depend on each other run **concurrently**, several inputs can fan into one node (they're joined in edge order), and the branch a condition didn't take is marked skipped rather than silently dropped. ## Why so few nodes? Because the vocabulary is small, not the ceiling. An Agent reaches anything through MCP tools, `{{Node name}}` reaches any value upstream, and iteration is coming as a node that loops inside itself rather than a cycle on the canvas. Hosted builders solve a different problem — they're infrastructure for companies shipping products, with evals, tracing and one-click deployment, and they run that vendor's models. Osler is a Mac app for one person's work. It can run Claude, GPT and a local model in the same flow, offline if you want, with no account to make. ## Reaching sideways Text flows along the wires, but a node can also reach a value that isn't wired into it. Write `{{Node name}}` in an Agent's system prompt (or a Condition's question) and it's replaced at run time with that node's output: ``` Compare the two. Original: {{Text}} Translation: {{Translate}} ``` References may only point *upstream* — at a node that's guaranteed to have finished first. Anything else is flagged before the flow runs, so a value can never race its reader. The inspector lists what's in reach. ## Tools, via MCP An Agent can call tools from [MCP](https://modelcontextprotocol.io) servers — files, web, APIs, anything with a server. Add one in **Settings → MCP** as a local command: ``` npx -y @modelcontextprotocol/server-filesystem ~/Documents ``` Hit **Test** to launch it and see its tools, then enable the server on any Agent node. The agent decides when to call what; each call shows up in the node's output as it happens. Today Osler speaks to stdio servers only, and a tool-enabled agent answers turn by turn instead of streaming live. Tool calls run without an approval step — an Approval node is next on the [roadmap](ROADMAP.md). ## Models Bring your own key, or bring your own machine: | Provider | Needs a key | Notes | | --- | --- | --- | | Anthropic | yes | Messages API, streaming | | OpenAI | yes | Chat Completions, streaming | | Ollama | **no** | Local models, fully offline | Keys live in the macOS **Keychain** — never on disk in plain text, never sent anywhere except the provider you're calling. Ollama needs nothing but a running server at `localhost:11434`. ## Getting started **[Download the latest release](https://github.com/albertofettucini/Osler/releases/latest)** — macOS 14 or newer. Open the `.dmg`, drag Osler to Applications, then **right-click it and choose Open** the first time. That first-launch warning isn't a problem with the app — it just isn't signed with a paid Apple developer account. Right-click → Open tells macOS you meant it, once. (No "Open" in the menu? System Settings → Privacy & Security → **Open Anyway**.) After that Osler updates itself, and every update is signature-verified, so a tampered download is refused. ### Or build it Requirements: Swift 5.9+ (Xcode 15+). ```sh git clone https://github.com/albertofettucini/Osler.git cd Osler swift run Osler ``` And to produce the app bundle itself: ```sh ./scripts/package-app.sh --desktop # builds Osler.app and copies it to ~/Desktop ``` Other targets: ```sh swift test # engine tests swift run osler-cli --demo linear # headless run (uses Ollama when no key is set) swift run osler-cli --demo tools # MCP tool loop against a mock server swift run osler-cli --demo cycle # cycle detection, no model needed ``` ## Around the canvas Eight starter templates ship with the app — Summarize, Sentiment Router, Translate & Polish, Writer & Critic, Parallel Brainstorm, Research with Tools, Email Drafter, Meeting Notes → Actions. Open one, press Run, take it apart. Wiring is two-way: drag from either port onto another node to connect, click a wire (or a port dot) to cut it. Double-click empty canvas to add a node where you clicked, or drag one in from the library. Shift-click and shift-drag select several nodes; ⌘Z undoes anything. ⌘K opens a command palette. Save any flow as a template and it joins the library. Flows are plain JSON files (`.oslerflow`) — readable, diffable, and yours. A flow saved by a newer version keeps its unknown nodes intact when an older build opens it. Appearance follows the system, or you can pin light/dark and pick a background wash and card tint in Settings. ## Architecture **`OslerEngine`** is a headless Swift library with no UI dependency: - `FlowGraph` / `Node` / `Edge` — the Codable graph model. - `GraphValidator` — structural checks and topological ordering, with real cycle errors instead of hangs. - `FlowEngine` — readiness-based scheduling (independent branches run in parallel), per-node state as an async event stream, cancellation throughout. - `LLMProvider` — a two-method protocol: stream text, or take one tool-calling turn. Adding a provider is a single type. - `MCPClient` / `MCPToolbox` — stdio JSON-RPC, tool discovery, call routing. **`Osler`** is the SwiftUI app — canvas, inspector, run controller — bound to the engine's event stream. **`osler-cli`** runs flows headlessly. 64 tests cover the engine, including a real subprocess round-trip against a scripted MCP server. ## License MIT — see [LICENSE](LICENSE). ## Source & license This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [albertofettucini](https://github.com/albertofettucini) - **Source:** [albertofettucini/Osler](https://github.com/albertofettucini/Osler) - **License:** MIT Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** yes - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/mcp-albertofettucini-osler - Seller: https://agentstack.voostack.com/s/albertofettucini - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.