Praison AI

Agent MCP Integration

Connect agents to external tools and services via Model Context Protocol

MCP (Model Context Protocol) enables agents to connect to external tool servers using standardized transports – stdio, SSE, HTTP stream, or WebSocket.

Diagram

MCP Architecture

🤖 Agent

🔌 MCP Client

🖥️ MCP Server

🔧 Tools

Quick Start

  1. Install MCP Support
    bash
    pip install praisonaiagents[mcp]
  2. Connect to MCP Server
    python
    from praisonaiagents import Agent
from praisonaiagents.mcp import MCP

# Connect to an MCP server
agent = Agent(
    instructions="You are a helpful assistant",
    tools=MCP("python /path/to/mcp_server.py")
)

agent.start("Use the available tools to help me")

Transport Types

Diagram

MCP Transports

Local servers

Legacy HTTP

Modern HTTP

Real-time

📟 stdio
Subprocess

📡 SSE
Server-Sent Events

🌐 HTTP Stream
Current Standard

🔗 WebSocket
SEP-1288

Use Case

TransportURL PatternUse Case
stdioCommand stringLocal subprocess servers
SSEhttp://...​/sseLegacy HTTP+SSE servers
HTTP Streamhttp://...Modern HTTP servers
WebSocketws://... or wss://...Real-time bidirectional

Connection Methods

Stdio (Subprocess)

python
from praisonaiagents.mcp import MCP

# Method 1: Single command string
tools = MCP("python /path/to/server.py")

# Method 2: Separate command and args
tools = MCP(
    command="/usr/bin/python",
    args=["/path/to/server.py"]
)

# Method 3: NPX for npm packages
tools = MCP("npx -y @anthropic/mcp-server-fetch")

HTTP/SSE

python
# SSE endpoint (legacy)
tools = MCP("http://localhost:8080/sse")

# HTTP Stream (modern)
tools = MCP("http://localhost:8080/mcp")

WebSocket

python
# WebSocket connection
tools = MCP("wss://mcp.example.com/ws")

# With authentication
tools = MCP(
    "wss://mcp.example.com/ws",
    auth_token="your-token"
)

Configuration Options

python
from praisonaiagents.mcp import MCP

mcp = MCP(
    command_or_string="python server.py",  # Command or URL
    args=None,                              # Arguments (for stdio)
    timeout=60,                             # Initialization timeout
    debug=False,                            # Enable debug logging
    # HTTP Stream options
    responseMode="streaming",               # Response mode
    headers={"Authorization": "Bearer ..."},
    # WebSocket options
    auth_token="token",                     # Auth token
)
OptionTypeDefaultDescription
command_or_stringstrRequiredCommand, URL, or command string
argslistNoneArguments for stdio transport
timeoutint60Timeout in seconds
debugboolFalseEnable debug logging
auth_tokenstrNoneAuthentication token (WebSocket)

How It Works

Diagram
MCP ServerMCP ClientAgentMCP ServerMCP ClientAgentInitializeConnect (stdio/HTTP/WS)List toolsTools availableCall toolExecute toolResultTool result

Tool Discovery

MCP automatically discovers tools from the server:

python
from praisonaiagents.mcp import MCP

mcp = MCP("python server.py")

# Tools are automatically available
print(mcp.tools)  # List of callable functions

Tool Execution

Tools are executed through the MCP protocol:

python
agent = Agent(
    instructions="You can search the web",
    tools=MCP("npx -y @anthropic/mcp-server-fetch")
)

# Agent automatically uses MCP tools
agent.start("Fetch the content from example.com")

Creating MCP Servers

Expose your tools as an MCP server:

python
from praisonaiagents.mcp import ToolsMCPServer, launch_tools_mcp_server

def my_tool(query: str) -> str:
    """Search for information."""
    return f"Results for: {query}"

# Create and launch server
server = ToolsMCPServer(tools=[my_tool])
launch_tools_mcp_server(server)

Common Patterns

NPX Servers (Smithery)

python
# Fetch server
tools = MCP("npx -y @anthropic/mcp-server-fetch")

# Filesystem server
tools = MCP("npx -y @anthropic/mcp-server-filesystem /path/to/dir")

# GitHub server
tools = MCP("npx -y @anthropic/mcp-server-github")

Multi-Server Setup

python
from praisonaiagents import Agent
from praisonaiagents.mcp import MCP

# Combine tools from multiple servers
fetch_tools = MCP("npx -y @anthropic/mcp-server-fetch")
fs_tools = MCP("npx -y @anthropic/mcp-server-filesystem .")

agent = Agent(
    instructions="You can fetch web content and manage files",
    tools=fetch_tools + fs_tools  # Combine tool lists
)

Best Practices

Use appropriate transport
  • stdio: Best for local tools, simple setup
  • HTTP Stream: Best for remote servers, modern standard
  • WebSocket: Best for real-time, bidirectional communication
Set reasonable timeouts

Increase timeout for slow-starting servers or network latency.

Enable debug for troubleshooting

Use debug=True to see MCP protocol messages when debugging.

Handle server availability

MCP servers may not always be available. Handle initialization failures gracefully.

Related

Tools

Function-based tools

 Skills

Modular skill packages