MCP tools

Agent commands. Your AI agent uses this node in workflows. You manage the MCP servers that provide these tools with pflow mcp commands.

MCP (Model Context Protocol) lets you extend pflow with external tools. When you add an MCP server, its tools become pflow nodes — same validation, same error handling, same template access as built-in nodes.

How it works

Add an MCP server with pflow mcp add
Sync tools with pflow mcp sync (or let auto-sync handle it)
Tools become nodes named mcp-{server}-{tool}
Agent uses them like any other node

# Add a GitHub MCP server
pflow mcp add github.mcp.json

# Tools are now available
pflow mcp list github
# mcp-github-create_issue
# mcp-github-list_repos
# mcp-github-search_code

Node naming

MCP tools become nodes with the pattern mcp-{server}-{tool}:

Server	Tool	Node name
github	create_issue	`mcp-github-create_issue`
slack	send_message	`mcp-slack-send_message`
filesystem	read_file	`mcp-filesystem-read_file`

Parameters

MCP node parameters come directly from the tool’s input schema. Each MCP server defines its own tools with their own parameters. To see a tool’s parameters:

pflow mcp describe mcp-github-create_issue

Output

All MCP nodes write to:

Key	Type	Description
`result`	any	Tool execution result
`error`	str	Error message (only on failure)

For dict results, read nested fields through result: If a tool returns {"issue_url": "...", "issue_number": 123}, use:

${github-issue.result.issue_url}
${github-issue.result.issue_number}

MCP nodes do not extract top-level result fields into ${node.field} and do not write a {server}_{tool}_result alias. Each workflow node already has its own namespace, so ${node.result} is the canonical success output.

Example workflow

### create_issue

Create a GitHub issue from the error summary.

- type: mcp-github-create_issue
- repository: myorg/myrepo
- title: "Bug: ${error_summary}"
- body: ${error_details}

### notify

Send a Slack notification with the issue link.

- type: mcp-slack-send_message
- channel: "#alerts"
- text: "Created issue: ${create_issue.result.issue_url}"

Setup

To use MCP tools, first add MCP servers to pflow. See Adding MCP servers for configuration format, authentication, and examples. pflow supports both local (stdio) and remote (HTTP) MCP servers. Both work identically in workflows - same naming, parameters, and output structure.

Error handling

MCP nodes return error action on:

Connection failure: Server not reachable
Tool error: Tool reported an error (via isError flag)
Timeout: Request took too long (default 30 seconds)

The node does not retry automatically - MCP calls start a server subprocess, and retries would cause resource conflicts.

Auto-sync

When you run a workflow, pflow automatically syncs MCP tools if the server configuration has changed. You don’t need to manually run pflow mcp sync after adding servers. Manual sync is useful for:

Testing connection immediately after adding a server
Debugging connection issues
Forcing re-discovery without running a workflow

CLI commands

Nodes

Configuration

Experimental

How it works

Node naming

Parameters

Output

Example workflow

Setup

Error handling

Auto-sync

​How it works

​Node naming

​Parameters

​Output

​Example workflow

​Setup

​Error handling

​Auto-sync

How it works

Node naming

Parameters

Output

Example workflow

Setup

Error handling

Auto-sync