Deploy as a Server: Tools

pip install "praisonaiagents[mcp]"

from praisonaiagents.mcp import ToolsMCPServer

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

def calculate(expression: str) -> str:
    """Calculate a math expression."""
    return str(eval(expression))

server = ToolsMCPServer(name="my-tools")
server.register_tool(search)
server.register_tool(calculate)
server.run(transport="sse", host="0.0.0.0", port=8080)

🚀 Starting MCP server 'my-tools' with SSE transport
📡 SSE endpoint: http://0.0.0.0:8080/sse
🛠️  Available tools: search, calculate

curl http://localhost:8080/sse

from praisonaiagents.mcp import launch_tools_mcp_server

launch_tools_mcp_server(
    tool_names=["tavily_search", "wikipedia_search"],
    transport="sse",
    port=8080
)

🚀 Starting MCP server 'praisonai-tools' with SSE transport
📡 SSE endpoint: http://0.0.0.0:8080/sse
🛠️  Available tools: tavily_search, wikipedia_search

from praisonaiagents.mcp import ToolsMCPServer

def my_tool(query: str) -> str:
    """Process a query."""
    return f"Processed: {query}"

server = ToolsMCPServer(name="my-tools", tools=[my_tool])
server.run(transport="stdio")

🚀 Starting MCP server 'my-tools' with stdio transport
🛠️  Available tools: my_tool

{
  "mcpServers": {
    "my-tools": {
      "url": "http://localhost:8080/sse"
    }
  }
}

{
  "mcpServers": {
    "my-tools": {
      "command": "python",
      "args": ["/path/to/mcp_server.py"]
    }
  }
}

# List tools
curl -X POST http://localhost:8080/messages/ \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc": "2.0", "method": "tools/list", "id": 1}'

# Call tool
curl -X POST http://localhost:8080/messages/ \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "method": "tools/call",
    "params": {"name": "search", "arguments": {"query": "AI news"}},
    "id": 2
  }'