PraisonAI/examples/mcp_server

PraisonAI MCP Server Examples

This directory contains examples for running PraisonAI as an MCP (Model Context Protocol) server.

Overview

PraisonAI can expose its capabilities via MCP protocol, allowing integration with:

• Claude Desktop
• Cursor
• Windsurf
• VSCode MCP clients
• Any MCP-compatible client

Protocol Version

These examples use MCP Protocol Version 2025-11-25.

Examples

1. STDIO Server (stdio_server.py)

Run PraisonAI as an MCP server using STDIO transport (for Claude Desktop integration).

# Run directly
python stdio_server.py

# Or via CLI
praisonai mcp serve --transport stdio

2. HTTP Stream Server (http_stream_server.py)

Run PraisonAI as an MCP server using HTTP Stream transport.

# Run directly
python http_stream_server.py

# Or via CLI
praisonai mcp serve --transport http-stream --port 8080

3. Custom Tools Server (custom_tools_server.py)

Register custom tools and expose them via MCP.

python custom_tools_server.py

4. Client Example (mcp_client_example.py)

Example of connecting to a PraisonAI MCP server as a client.

python mcp_client_example.py

CLI Commands

# Start STDIO server
praisonai mcp serve --transport stdio

# Start HTTP Stream server
praisonai mcp serve --transport http-stream --port 8080

# Start with authentication
praisonai mcp serve --transport http-stream --api-key YOUR_KEY

# List available tools
praisonai mcp list-tools

# List available resources
praisonai mcp list-resources

# List available prompts
praisonai mcp list-prompts

# Generate client configuration
praisonai mcp config-generate --client claude-desktop

# Check server health
praisonai mcp doctor

Client Configuration

Claude Desktop

Add to ~/.config/claude/claude_desktop_config.json:

{
  "mcpServers": {
    "praisonai": {
      "command": "praisonai",
      "args": ["mcp", "serve", "--transport", "stdio"]
    }
  }
}

Cursor

Add to Cursor settings:

{
  "mcpServers": {
    "praisonai": {
      "command": "praisonai",
      "args": ["mcp", "serve", "--transport", "stdio"]
    }
  }
}

Environment Variables

Set the following environment variables for full functionality:

export OPENAI_API_KEY=your_key
export ANTHROPIC_API_KEY=your_key  # Optional
export GOOGLE_API_KEY=your_key     # Optional

Available Tools

Run praisonai mcp list-tools to see all available tools, including:

• praisonai.chat.completion - Chat with LLM
• praisonai.agent.chat - Chat with an agent
• praisonai.agent.run - Run a task with an agent
• praisonai.workflow.run - Run a workflow
• praisonai.images.generate - Generate images
• praisonai.audio.transcribe - Transcribe audio
• praisonai.embed.create - Create embeddings
• praisonai.memory.* - Memory operations
• praisonai.knowledge.* - Knowledge base operations
• And many more...

Available Resources

• praisonai://memory/sessions - List memory sessions
• praisonai://workflows - List available workflows
• praisonai://tools - List available tools
• praisonai://agents - List agent configurations
• praisonai://knowledge/sources - List knowledge sources
• praisonai://config - Get current configuration
• praisonai://mcp/status - Get MCP server status

Available Prompts

• deep-research - Generate deep research prompts
• code-review - Generate code review prompts
• workflow-auto - Generate workflow auto-generation prompts
• guardrail-check - Generate guardrail check prompts
• context-engineering - Generate context engineering prompts
• eval-criteria - Generate evaluation criteria prompts
• agent-instructions - Generate agent instructions prompts