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KamalabotKamalabot
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got the page update for the tasks
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‎notion_brain_dump/.gitignore‎

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# Python-generated files
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__pycache__/
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*.py[oc]
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build/
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dist/
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wheels/
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*.egg-info
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# Virtual environments
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.venv

‎notion_brain_dump/.python-version‎

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3.11

‎notion_brain_dump/README.md‎

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‎notion_brain_dump/mcpclient.py‎

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import asyncio
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from typing import Optional
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from contextlib import AsyncExitStack
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# pyright: reportMissingImports=false
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# pyright: reportOptionalSubscript=false
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from mcp import ClientSession, StdioServerParameters
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from mcp.client.stdio import stdio_client
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from anthropic import Anthropic
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from dotenv import load_dotenv
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# uncomment this when running in your local environment
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# ensure you have updated the .env file with the Anthropic API Key
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# load_dotenv() # load environment variables from .env
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class MCPClient:
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def __init__(self):
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# Initialize session and client objects
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self.session: Optional[ClientSession] = None
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self.exit_stack = AsyncExitStack()
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self.anthropic = Anthropic()
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# methods will go here
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async def connect_to_server(self, server_script_path: str):
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"""Connect to notion MCP server
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Args:
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server_script_path: Path to the server script (.py or .js)
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"""
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is_python = server_script_path.endswith(".py")
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is_js = server_script_path.endswith(".js")
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if not (is_python or is_js):
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raise ValueError("Server script must be a .py or .js file")
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command = "python" if is_python else "node"
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server_params = StdioServerParameters(
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command=command, args=[server_script_path], env=None
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)
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stdio_transport = await self.exit_stack.enter_async_context(
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stdio_client(server_params)
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)
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self.stdio, self.write = stdio_transport
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self.session = await self.exit_stack.enter_async_context(
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ClientSession(self.stdio, self.write)
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)
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await self.session.initialize()
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# List available tools
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response = await self.session.list_tools()
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tools = response.tools
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print(
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"\nConnected to Notion MCP server with tools:",
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[tool.name for tool in tools],
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)
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async def process_query(self, query: str) -> str:
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"""Process a query using Claude and available tools"""
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messages = [{"role": "user", "content": query}]
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response = await self.session.list_tools()
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available_tools = [
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{
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"name": tool.name,
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"description": tool.description,
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"input_schema": tool.inputSchema,
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}
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for tool in response.tools
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]
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# Initial Claude API call
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response = self.anthropic.messages.create(
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model="claude-3-5-haiku-20241022",
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max_tokens=1000,
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messages=messages,
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tools=available_tools,
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)
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# Process response and handle tool calls
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tool_results = []
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final_text = []
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for content in response.content:
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if content.type == "text":
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final_text.append(content.text)
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elif content.type == "tool_use":
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tool_name = content.name
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tool_args = content.input
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# Execute tool call
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result = await self.session.call_tool(tool_name, tool_args)
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tool_results.append({"call": tool_name, "result": result})
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final_text.append(f"[Calling tool {tool_name} with args {tool_args}]")
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# Continue conversation with tool results
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if hasattr(content, "text") and content.text:
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messages.append({"role": "assistant", "content": content.text})
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messages.append({"role": "user", "content": result.content})
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# Get next response from Claude
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response = self.anthropic.messages.create(
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model="claude-3-5-haiku-20241022",
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max_tokens=1000,
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messages=messages,
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)
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final_text.append(response.content[0].text)
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return "\n".join(final_text)
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async def chat_loop(self):
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"""Run an interactive chat loop"""
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print("\nMCP Client Started!")
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print("Type your queries or 'quit' to exit.")
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while True:
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try:
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query = input("\nQuery: ").strip()
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if query.lower() == "quit":
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break
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response = await self.process_query(query)
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print("\n" + response)
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except Exception as e:
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print(f"\nError: {str(e)}")
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async def cleanup(self):
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"""Clean up resources"""
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await self.exit_stack.aclose()
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async def main():
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if len(sys.argv) < 2:
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print("Usage: python mcpclient.py mcpserver.py")
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sys.exit(1)
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client = MCPClient()
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try:
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await client.connect_to_server(sys.argv[1])
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await client.chat_loop()
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finally:
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await client.cleanup()
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if __name__ == "__main__":
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import sys
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asyncio.run(main())

‎notion_brain_dump/pyproject.toml‎

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[project]
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name = "notion-brain-dump"
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version = "0.1.0"
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description = "Add your description here"
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readme = "README.md"
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requires-python = ">=3.11"
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dependencies = [
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"anthropic>=0.49.0",
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"mcp[cli]>=1.6.0",
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"notion-client>=2.3.0",
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"python-dotenv>=1.1.0",
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]

‎notion_brain_dump/server.py‎

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from mcp.server.fastmcp import FastMCP
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from notion_client import AsyncClient
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import os
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from typing import List
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token = "ntn_token"
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mcp = FastMCP("notion_bd_server")
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brain = AsyncClient(auth=token)
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@mcp.tool()
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async def add_task(task: str):
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"""Add a task to the Notion database and returns the new page ID"""
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dump_db = "1d784ade96ac80a3b7ecf54f3eae5f49"
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newpage = {
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"TaskTitle": {"title": [{"text": {"content": task}}]},
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}
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pg_create = await brain.pages.create(
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parent={"database_id": dump_db},
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properties=newpage,
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)
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return f"Task has been added {pg_create['id']}"
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@mcp.prompt()
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def task_steps(task_text: str) -> str:
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"""Prompt to get the steps to complete the tasks"""
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return f"Provide the step by approach required to complete the {task_text}"
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@mcp.prompt()
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def task_analysis(tasks: str) -> str:
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"""Prompt to analyse the tasks"""
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return f"Analyse the {tasks} and provide the steps to complete the task"
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@mcp.resource("notion://dumpdb/{task_text}")
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async def search_db(task_text: str) -> str:
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"""Get the filtered task from the Notion database and returns the data as text"""
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dump_db = "1d784ade96ac80a3b7ecf54f3eae5f49"
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search_results = await brain.databases.query(
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database_id=dump_db,
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filter={
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"property": "TaskTitle",
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"title": {
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"contains": task_text,
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},
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},
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)
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results = search_results.get("results", [])
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text_conv = ""
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for result in results:
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page_id = result["id"]
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created_time = result["created_time"]
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last_edited_time = result["last_edited_time"]
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# getting the properties now
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task_title = result["properties"]["TaskTitle"]["title"][0]["text"]["content"]
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task_status = result["properties"]["TaskStatus"]["select"]
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area = result["properties"]["Area"]["rich_text"]
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resource = result["properties"]["Resource"]["rich_text"]
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due_date = result["properties"]["DueDate"]["date"]
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url = result["url"]
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text_conv += f"Task: {task_title}\t Status: {task_status}\t Area: {area}\t Resource: {resource}\t Due Date: {due_date}\t URL: {url}\t Page ID: {page_id}\t Last Edited Time: {last_edited_time}\t "
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# return results[0]["text"]
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return text_conv
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# @mcp.tool()
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async def analyse_tasks(task_kw: str) -> str:
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"""Searches the database for the task, and gets the steps to complete the task"""
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task_info = await mcp.read_resource(f"notion://dumpdb/{task_kw}")
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assembled_prompt = await mcp.get_prompt(
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"task_analysis",
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arguments={
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"tasks": task_info[0].content,
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},
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)
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return assembled_prompt.messages[0].content.text
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@mcp.tool()
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async def update_task(task_title: str, task_data: str):
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"""Update the task in the database with given task title"""
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# First find the task and get its page id
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dump_db = "1d784ade96ac80a3b7ecf54f3eae5f49"
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search_results = await brain.databases.query(
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database_id=dump_db,
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filter={
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"property": "TaskTitle",
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"title": {
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"equals": task_title,
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},
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},
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)
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results = search_results.get("results", [])
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page_id = results[0]["id"]
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# Then update the data into the page using append method
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page_data = {
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"object": "block",
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"type": "paragraph",
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"paragraph": {"rich_text": [{"text": {"content": task_data}}]},
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}
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await brain.blocks.children.append(
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block_id=page_id,
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children=[page_data],
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)
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# Inform the LLM that the work has been done
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return f"The page with {page_id} has been updated"
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# "TaskTitle": {"id": "title", "type": "title", "title": [{"type": "text", "text": {"content": "test", "link": null}, "annotations": {"bold": false, "italic": false, "strikethrough": false, "underline": false, "code": false, "color": "default"}, "plain_text": "test", "href": null}] [ "properties": {"TaskStatus": {"id": "IJax", "type": "select", "select": null}, "Area": {"id": "c%3C%60%7C", "type": "rich_text", "rich_text": []}, "DueDate": {"id": "ce%3DU", "type": "date", "date": null}, "Resource": {"id": "kUxZ", "type": "rich_text", "rich_text": []}, }}, "url": "https://www.notion.so/test-1d784ade96ac81a38f7bdd1eccaa13c4", "public_url": null}]',]
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if __name__ == "__main__":
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print("Starting MCP server...")
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mcp.run()

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