"""
Tool registry for MemoryGraph MCP server.
This module maps MCP tool names to their handler functions. The registry
pattern allows for clean separation between tool definitions and implementations.
To add a new tool:
1. Create the handler function in the appropriate module under tools/
2. Add the mapping to TOOL_HANDLERS dictionary
3. Add the tool definition to the server's tool collection
Tool handlers receive a ToolContext and kwargs from the tool call,
and return the result to be sent back to the MCP client.
"""
from typing import Any, Awaitable, Callable, Dict
from mcp.types import CallToolResult
from .activity_tools import (
handle_get_memory_statistics,
handle_get_recent_activity,
handle_search_relationships_by_context,
)
from .memory_tools import (
handle_delete_memory,
handle_get_memory,
handle_store_memory,
handle_update_memory,
)
from .relationship_tools import (
handle_create_relationship,
handle_get_related_memories,
)
from .search_tools import (
handle_contextual_search,
handle_recall_memories,
handle_search_memories,
)
# Type alias for tool handlers
ToolHandler = Callable[[Any, Dict[str, Any]], Awaitable[CallToolResult]]
# Registry mapping tool names to handlers
TOOL_HANDLERS: Dict[str, ToolHandler] = {
"store_memory": handle_store_memory,
"get_memory": handle_get_memory,
"update_memory": handle_update_memory,
"delete_memory": handle_delete_memory,
"search_memories": handle_search_memories,
"recall_memories": handle_recall_memories,
"contextual_search": handle_contextual_search,
"create_relationship": handle_create_relationship,
"get_related_memories": handle_get_related_memories,
"get_memory_statistics": handle_get_memory_statistics,
"get_recent_activity": handle_get_recent_activity,
"search_relationships_by_context": handle_search_relationships_by_context,
}
def get_handler(tool_name: str) -> ToolHandler | None:
"""
Get handler function for a tool by name.
Args:
tool_name: Name of the MCP tool to get handler for
Returns:
Handler function if found, None otherwise
Example:
handler = get_handler("store_memory")
if handler:
result = await handler(context, kwargs)
"""
return TOOL_HANDLERS.get(tool_name)
