AI Agent & Knowledge Management

Notion MCP Agent

AI-Powered Notion Assistant with Real-Time Interaction.Turn your Notion workspace into a live, intelligent hub using Model Context Protocol (MCP). Interact in real time via a local desktop app to append content, create tables, manage pages, and generate summaries—all powered by AI and local LLMs.

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Project Overview

Notion-MCP-Agent is a desktop-based system that brings AI-powered interaction to your Notion workspace. Built on the Model Context Protocol (MCP), it enables real-time communication with Notion via a local FastMCP server and SSE, using local or cloud-based LLMs.

Users can interact through a simple GUI to append content, build tables, extract structured notes, and manage metadata—all via natural language. The system also supports text-to-speech generation using Coqui TTS, offering a seamless, local-first workflow.

Core Capabilities

Live Notion Integration – Real-time read/write via FastMCP and Server-Sent Events (SSE).
Structured AI Interaction – Summarizes, organizes, and interprets Notion content intelligently.
Content Automation – Appends Markdown, builds tables, and updates or creates pages.
Natural Language Commands – Query and control Notion using plain language prompts.
Search and Retrieval – Locate relevant pages and properties across the workspace.
Text-to-Speech – Converts Notion page content into audio files via Coqui TTS.

Agent Workflow

1. Connection & Tool Registration

When the FastMCP server launches, it registers all custom tools (e.g., append_content, create_table, get_page_text) and exposes them via MCP endpoints. These tools are dynamically loaded by the LangGraph-based REACT agent at runtime.

2. User Query via GUI

The user submits a natural language prompt through a local Tkinter-based desktop interface. This input is passed to the agent, which uses a selected LLM (e.g., GPT‑4o via OpenAI or a local Ollama model) to interpret the request.

3. Planning & Tool Selection

The agent selects the appropriate MCP tools to fulfill the user's request. This may include reading Notion content, generating structured notes, appending Markdown blocks, or creating subpages and tables.

4. Execution via FastMCP

Each tool call is routed through the FastMCP server, which interfaces directly with the Notion API or Coqui TTS engine. Actions like content writing, search, or speech synthesis are executed and results returned.

5. Streaming & Response Delivery

Responses are streamed back to the GUI in real time using Server-Sent Events (SSE). The agent displays structured outputs and optionally provides downloadable MP3 files for text-to-speech results.

Key Features

Interactive Agent

LangGraph-powered AI agent interprets user prompts and executes Notion operations using local or cloud LLMs in real time.

MCP Tooling

Custom Model Context Protocol tools enable structured read/write access to Notion content, metadata, and user data via FastMCP.

Live Streaming

Server-Sent Events (SSE) stream AI-generated responses instantly to the desktop GUI, maintaining fluid interaction throughout sessions.

Semantic Search

Leverages Notion's native API to locate relevant pages and properties using context-aware queries powered by language models.

Content Automation

Automates Markdown appending, table creation, metadata updates, and even TTS generation for audio-based note review.

Tools & Technologies

Category	Technology
Protocol	Model Context Protocol (MCP)
API Integration	Notion API, Coqui TTS (via local Python bindings)
Language Models	GPT‑4o (OpenAI), Ollama (local LLMs)
Framework	LangGraph (REACT agent), Pure Python (no LangChain runtime)
Backend	Python, FastMCP (FastAPI-based)
Database	Notion workspace (no external DB)
Authentication	.env-secured Notion API Token and OpenAI Key
Interface	Tkinter Desktop GUI
Transport	Server-Sent Events (SSE)
Deployment	Offline-capable, local-first (no external cloud dependencies)