01 / INITIAL SETUP
Install once. Choose a surface when you work.
The Windows setup includes Knodr.App.exe for visual editing and knodr.exe for both CLI and MCP use. The standard installer places the current release under %LOCALAPPDATA%\Knodr\current; the portable ZIP keeps the same files together wherever you extract it.
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01
Install and launch
Run the setup executable, then open Knodr from the Start menu. No .NET SDK or separate CLI download is required.
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02
Create a flow
Choose File → New, add a few nodes, connect their ports, and save the file with the
.knodrflowextension. -
03
Enable terminal access
Add the folder containing
knodr.exeto your Windows userPATH, or invoke it by its full path. Portable users can run.\knodr.exefrom the extracted folder.
$ $env:Path += ";$env:LOCALAPPDATA\Knodr\current" $ knodr --help
.knodrflow files. You do not export or convert a flow when switching surfaces.02 / DESKTOP UI
Build and debug on the canvas
The desktop app is the quickest way to understand a flow. Its canvas is the graph; the palette adds work; and the inspector shows the selected node and the values produced by a run.
Add and connect nodes
Use the searchable palette to add a node. Configure it in the node editor, then drag from an output port to a compatible input port.
Execute the graph
Select Run. Independent branches run concurrently and each node reports its current state on the canvas.
Follow the data
Select a node to inspect its inputs, outputs, errors, and timing. Double-click a node when you need to edit its parameters.
Pause or replay
Toggle a breakpoint from the node header gutter, step or continue a paused run, and use Replay to rerun a selected node with its previous inputs.
Plaintext project variables
Use Project → Configuration for non-sensitive values referenced as {{var.NAME}}. These values are saved in the flow, so they are suitable for flags, paths, and defaults—not credentials.
03 / SECRETS
Store references in flows, never secret values
Nodes that need credentials use a name such as openai-personal in their credentialRef field. Knodr resolves the value only when the node runs.
Settings → Secrets stores values with Windows DPAPI in %APPDATA%\Knodr\secrets.dat. The settings screen lists names, not values.
A .knodrflow or project bundle contains the credential name only. Secret values are not serialized into flow files or returned through MCP tools.
KNODR_CREDENTIAL_<UPPER_SNAKE_NAME> wins over the stored value, which is useful for CI and per-run environments.
Add a secret
- Open Settings → Secrets.
- Enter a memorable name and the secret value, then select Save.
- Enter that same name in the node's
credentialReffield.
$ $env:KNODR_CREDENTIAL_OPENAI_PERSONAL = "your-api-key" $ knodr run .\flows\assistant.knodrflow
--var values are plaintext configuration. Use credentialRef and the secret store or credential environment variables for sensitive values.04 / CLI
Validate, run, and automate from a terminal
The CLI is designed for local scripts and CI. Human-readable output is the default; add --output-format json when another program will consume the result.
Check a flow before running it
$ knodr validate .\flows\main.knodrflow $ knodr doctor .\flows\main.knodrflow
Run with input and variables
$ knodr run .\flows\review.knodrflow ` --input "Review the staged changes" ` --var MODE=strict ` --timeout 2m $ Get-Content .\prompt.txt -Raw | knodr run .\flows\review.knodrflow --output-format json
--input, --input-file, or redirected stdin binds to a flow with exactly one Manual Input node. Repeat --var NAME=value for runtime overrides, or use --vars-file with a KEY=VALUE file.
Useful commands
knodr list-nodesList the node types available in this release.knodr organize flow.knodrflowAuto-arrange a flow and save it in place.knodr doctor [flow]Check agent CLIs, credentials, and optional live authentication.knodr serve flow.knodrflowRun a live flow with triggers until you stop it.knodr run --helpSee every input, concurrency, timeout, and output option.05 / MCP
Give an agent the Knodr toolset
knodr mcp starts a local stdio MCP server. It exposes the node catalog, flow authoring and validation, run control and observability, plus node-level debugging. The --project directory is the base for relative flow paths and run history.
Register the server in an MCP client
Add a server entry to the configuration used by your MCP client. Use absolute paths so the client can start Knodr regardless of its working directory.
{
"mcpServers": {
"knodr": {
"command": "C:\\Users\\you\\AppData\\Local\\Knodr\\current\\knodr.exe",
"args": [
"mcp",
"--project",
"C:\\work\\my-project"
]
}
}
}
Restart the MCP client after changing its configuration. If you use the portable build, point command at the extracted knodr.exe instead.
Use the tools as a workflow
- Discover: call
list_nodesandget_node_schemabefore choosing node types and ports. - Author: scaffold a project or flow, then use
add_node,set_node_params, andconnect_nodes. - Check: call
organize_flowandvalidate_flow. Fix validation errors before execution. - Run: call
start_run, then pollget_run_status; use logs and snapshots when a run needs inspection.
“Using the Knodr tools, inspect the node catalog, create a flow that reads a file and summarizes it with an LLM, validate and organize the flow, then run it with a sample path.”
Restrict execution when needed
Add --read-only to the MCP arguments to remove execution and node-debugging tools. Catalog, validation, and flow-authoring tools remain available, so use filesystem permissions as the boundary when the client must not edit flows.
06 / REFERENCE & TUTORIALS
Build from small, working patterns
Browse the complete catalog, then follow a runnable example from canvas to automation. Each tutorial includes a downloadable .knodrflow.
Available nodes
Inputs, triggers, agents, AI, system tools, files, Git, HTTP, control flow, and outputs.
Open node catalog → Tutorial · 2 nodesCI test flow
Put a test command, timeout, failure policy, and output into a versioned flow.
Build the CI flow → Tutorial · 4 nodesAgent tools & skills
Author and run an agent flow through MCP, then wrap it in a reusable AI-client skill.
Build the agent tool →More to come
Grow the library with us.
Next topics can expand into live triggers, debugging, containers, subflows, and complete multi-agent examples.