The pflow registry command group manages the node registry - a catalog of all nodes available for building workflows. This includes core nodes, MCP tools, and custom user nodes.
Agent commands. These commands are primarily used by your AI agent to discover and test nodes when building workflows. The scan command is the exception - you run that to add custom nodes.
Commands
| Command | Description |
|---|
list | List all registered nodes |
describe | Show detailed node information |
discover | Find nodes using natural language |
scan | Add custom nodes from a directory |
run | Execute a single node for testing |
pflow registry list
List all registered nodes, optionally filtered by pattern.
pflow registry list [FILTER_PATTERN] [--json]
FILTER_PATTERN - Optional keywords to filter (space-separated, AND logic)
Options:
Examples:
# List all nodes grouped by package
pflow registry list
# Filter by keyword
pflow registry list github
# Filter by multiple keywords (AND logic)
pflow registry list "github api"
# JSON output
pflow registry list --json
Core nodes:
file (5 nodes):
- read-file: Read file contents
- write-file: Write content to file
- copy-file: Copy a file
- move-file: Move or rename a file
- delete-file: Delete a file
llm (1 node):
- llm: Send prompts to LLM
MCP tools:
github (15 tools):
- mcp-github-create-issue: Create a new GitHub issue
- mcp-github-list-issues: List issues from a repository
...
pflow registry describe
Show detailed information about one or more nodes including parameters, inputs, and outputs.
pflow registry describe <NODE>...
NODE - One or more node names/IDs to describe (required)
Examples:
# Single node
pflow registry describe llm
# Multiple nodes at once
pflow registry describe read-file write-file llm
# MCP tool (multiple name formats work)
pflow registry describe mcp-github-create-issue
pflow registry describe github-create-issue
pflow registry describe create-issue
Node: llm
Type: core
Description: Send prompts to an LLM and get responses
Parameters:
- prompt (string, required): The prompt to send
- system (string): System prompt for context
- model (string): Model to use (default: auto-detect)
- temperature (float): Response randomness (0-1)
Inputs:
- context (string): Optional context from shared store
Outputs:
- response (string): LLM response text
Example usage:
pflow registry run llm prompt="Hello world"
For MCP tools, pflow handles name variations automatically. create-issue, github-create-issue, and mcp-github-create-issue all resolve to the same tool (if unique).
pflow registry discover
Use AI to find nodes relevant to a natural language task description.
pflow registry discover "<QUERY>"
QUERY - Natural language description of what you need (max 500 characters)
Example:
pflow registry discover "I need to read files and call APIs"
Based on your task, these nodes are relevant:
read-file
Read file contents from the filesystem
Parameters: file_path (required), encoding
http
Make HTTP requests to APIs
Parameters: url (required), method, headers, body
Use 'pflow registry describe <node>' for full details.
Requires an Anthropic API key. Set it with pflow settings set-env ANTHROPIC_API_KEY "your-key".
pflow registry scan
Scan a directory for custom user nodes and add them to the registry.
pflow registry scan [PATH] [--force] [--json]
PATH - Directory to scan (default: ~/.pflow/nodes/)
Options:
--force, -f - Skip confirmation prompt--json - Output as JSON
Example:
# Scan default location
pflow registry scan
# Scan custom directory
pflow registry scan ./my-nodes/
# Skip confirmation
pflow registry scan --force
Found 3 Python files to scan...
Valid nodes:
✓ my-custom-node: Custom processing logic
✓ data-transformer: Transform data formats
Invalid (skipped):
⚠ broken-node.py: Missing exec() method
Add 2 nodes to registry? [y/N]: y
✓ Added 2 nodes to registry
Custom nodes execute with your user privileges. Only add nodes from sources you trust.
pflow registry run
Execute a single node independently for testing.
pflow registry run <NODE> [PARAMS...] [OPTIONS]
NODE - Node name/ID to execute (required)PARAMS - Parameter key=value pairs
Options:
--output-format text|json - Output format (default: text)--timeout INT - Execution timeout in seconds (default: 60)-v, --verbose - Show detailed execution information
Examples:
# Test file reading
pflow registry run read-file file_path=/tmp/test.txt
# Test LLM node
pflow registry run llm prompt="Hello world"
# Test with JSON output
pflow registry run read-file file_path=/tmp/test.txt --output-format json
# Test MCP tool
pflow registry run mcp-github-list-issues repo=owner/repo state=open
# With timeout
pflow registry run http url="https://api.example.com" --timeout 30
count=10 # integer
rate=0.5 # float
enabled=true # boolean
tags='["a","b"]' # JSON array
config='{"key":"val"}'# JSON object
name=example # string
✓ Node executed successfully
Output structure:
$.content (string) - 42 chars
$.metadata.size (number)
$.metadata.created (string)
✓ Node executed successfully
content: "Hello world..."
metadata:
size: 123
created: "2024-01-15"
Execution time: 45ms
{
"success": true,
"outputs": {
"content": "Hello world...",
"metadata": {"size": 123}
},
"execution_time_ms": 45
}
Agents use registry run to test node parameters before building workflows. It helps discover output structure for nodes with dynamic types.
Node types
| Type | Description | Example |
|---|
| Core | Built-in pflow nodes | read-file, llm, http |
| MCP | Tools from MCP servers | mcp-github-create-issue |
| User | Custom user-defined nodes | Scanned from ~/.pflow/nodes/ |
mcp-{server}-{tool}. Multiple name formats work:
| Format | Example |
|---|
| Full | mcp-github-create-issue |
| Server-qualified | github-create-issue |
| Short (if unique) | create-issue |
File locations
| Path | Purpose |
|---|
~/.pflow/registry.json | Registry data |
~/.pflow/nodes/ | Default custom node location |
