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MCP Proxyv1.0.0

@agiflowai/powertool

MCP Proxy Server for Claude Code and marketplace plugins. Aggregates multiple MCP servers with built-in project management prompts.

When to Use

Use @agiflowai/powertool when:

  • ✓Using Claude Code with MCP servers
  • ✓Installing marketplace plugins
  • ✓Aggregating multiple MCP servers
  • ✓Using built-in project management prompts

Use @agiflowai/agent-cli when:

  • ✓Running agents with daemon mode
  • ✓Remote agent management
  • ✓Persistent agent connections
  • ✓Team collaboration workflows

Installation

Install globally with npm
npm install -g @agiflowai/powertool
Or use with npx (no installation needed)
npx @agiflowai/powertool mcp-serve

Quick Start

1. Get Your Configuration from Agiflow

  • •Sign up at agiflow.io
  • •Create a new project in the dashboard
  • •Follow the setup wizard to generate your MCP configuration
  • •Copy your project endpoint URL and API key

2. Add to Claude Code

Add to your .mcp.json:

{ "mcpServers": { "agiflow": { "command": "npx", "args": ["-y", "@agiflowai/powertool", "mcp-serve"], "env": { "AGIFLOW_MCP_PROXY_ENDPOINT": "https://agiflow.io/api/v1/projects/your-project-id/mcp-configs", "AGIFLOW_MCP_API_KEY": "your-generated-api-key" } } } }

Configuration Methods

The proxy server supports three configuration methods (in order of precedence):

Method 1: Environment Variables (Recommended for CI/CD)

Get your endpoint and API key from the Agiflow dashboard setup wizard:

export AGIFLOW_MCP_PROXY_ENDPOINT=https://agiflow.io/api/v1/projects/your-project-id/mcp-configs export AGIFLOW_MCP_API_KEY=your-api-key-here @agiflowai/powertool mcp-serve

Method 2: Saved Credentials (Recommended for Development)

Simply run the command without configuration. The CLI will prompt for authentication and save credentials:

# First time setup @agiflowai/powertool mcp-serve → Enter your endpoint URL: https://agiflow.io/api/v1/projects/... → Enter your API key: **** ✓ Credentials saved to ~/.agiflow/mcp.credentials.json

Credentials are saved per project directory and automatically loaded on subsequent runs.

Method 3: Local Configuration File (For Testing)

Use a local JSON configuration file:

# Using a local config file @agiflowai/powertool mcp-serve --config-file ./mcp-config.json # With HTTP transport @agiflowai/powertool mcp-serve --config-file ./mcp-config.json --type http --port 3000

Built-in Prompts

Powertool includes built-in prompts for project management workflows with LiquidJS template rendering and 14 custom filters.

agiflow:project-plan

Break down project requirements into structured tasks and work units with automatic task dependency detection.

agiflow:run-task

Implement single tasks with progress tracking, validation, and automated status updates.

agiflow:run-work

Execute work units (features/epics) with multiple tasks, handling sequential task implementation.

MCP Proxy Capabilities

Multi-Server Proxy

Connect to and proxy multiple MCP servers (stdio, HTTP, SSE) with automatic connection pooling and lifecycle management.

Tool Aggregation

Aggregate tools from all connected servers with automatic namespacing to avoid conflicts. Tools are accessible as serverName/toolName.

Resource & Prompt Proxying

Proxy resources and prompts from all connected servers. Resources are prefixed as serverName://resourceUri.

Remote Configuration

Fetch MCP server configurations from Agiflow hosted at agiflow.io with automatic caching and updates.

Command Options

-t, --typeTransport type: stdio, http, or sse (default: stdio)
-p, --portPort to listen on for HTTP/SSE (default: 3000)
--hostHost to bind to for HTTP/SSE (default: localhost)
-f, --config-filePath to local MCP configuration JSON file

Troubleshooting

Connection Issues

If you're having trouble connecting to Agiflow:

  • •Verify your endpoint URL and API key are correct
  • •Check your internet connection
  • •Ensure you're using the latest version: npm update -g @agiflowai/powertool
  • •Check saved credentials: cat ~/.agiflow/mcp.credentials.json

MCP Server Connection Errors

If specific MCP servers fail to connect:

  • •Verify the MCP server configuration in Agiflow dashboard
  • •Check that the MCP server is running and accessible
  • •Review server logs for specific error messages
  • •Test the MCP server independently without the proxy

Permission Errors

If you encounter permission errors during installation:

# On macOS/Linux, you may need to use sudo sudo npm install -g @agiflowai/powertool # Or configure npm to use a different directory npm config set prefix ~/.npm-global export PATH=~/.npm-global/bin:$PATH

Debug Mode

Enable verbose logging for debugging:

# Run with debug flag @agiflowai/powertool mcp-serve --debug # Or set environment variable DEBUG=agiflow:* @agiflowai/powertool mcp-serve

API Reference

Complete Command Reference

For a complete list of all commands and options, use the built-in help:

# Get help for all commands @agiflowai/powertool --help # Get help for specific command @agiflowai/powertool mcp-serve --help

Links

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