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| title: Early Depression Detection MCP Agent | |
| emoji: 🧠 | |
| colorFrom: blue | |
| colorTo: purple | |
| sdk: gradio | |
| sdk_version: 6.2.0 | |
| app_file: app.py | |
| pinned: true | |
| tags: | |
| - mcp-in-action-track-consumer | |
| - sambanova | |
| - nebius | |
| - huggingface | |
| - depression-detection | |
| - mental-health | |
| - longformer | |
| - mcp | |
| - agents | |
| license: mit | |
| short_description: Agentic depression detection using Kimi K2/Llama 3 | |
| # 🧠 Early Depression Detection MCP Agent | |
| **Hackathon:** MCP 1st Birthday - Track 2: MCP in Action (Consumer) | |
| **Author:** Hassan Hassanzadeh Aliabadi | [LinkedIn](https://www.linkedin.com/in/hassanzh/) | |
| ## 📹 Demo Video | |
| [YOUTUBE LINK](https://youtu.be/U32a4QjXNz0) | |
| ## 🎯 Project Description | |
| This MCP-enabled agent detects depression risk from social media text by orchestrating specialized tools and LLM reasoning. It is built on Master's thesis research and is rigorously validated, achieving an F1-score of **0.7668** on the eRisk 2025 test data. | |
| ### 🤖 Multi-Provider Agent Architecture (MCP in Action) | |
| The agent operates in a two-tier structure: | |
| 1. **Tool Layer (The "Eyes"):** | |
| * **Tool:** `detect_depression_risk` (My Longformer model). | |
| * **Capability:** 4,096-token context window for long user timelines. | |
| * **Core Logic:** Implements thesis-derived thresholds (0.4 / 0.6) and classification based on behavioral patterns. | |
| 2. **Reasoning Layer (The "Brain"):** | |
| * **Purpose:** Provides empathetic, research-backed interpretation. | |
| * **Providers:** Uses **SambaNova** (Meta-Llama-3.3) and **Nebius** (Kimi K2) via the same `OpenAI` client for enhanced robustness and sponsor stacking. | |
| ## 🧪 Thesis Findings Integrated | |
| The agent doesn't just output a probability; it looks for and reports on specific linguistic biomarkers identified in my Master's Thesis: | |
| * **"Nocturnal Posting" & "High-Effort, Low-Frequency":** The primary behavioral signature of high-risk users. | |
| * **"Echo Chamber Interaction":** The signature of moderate-risk, supportive users engaging with high-risk topics (11.7x higher interaction rate). | |
| ## 🏆 Research Background | |
| Built on Master's thesis research at **University of Malaya**: | |
| - **Model:** `avtak/erisk-longformer-depression-v1`. | |
| - **Validation:** Rigorous 5-fold cross-validation. | |
| - **Data Augmentation:** Used Gemini 2.5 Flash Lite to balance the depressed class. | |
| ## ⚠️ Ethical Considerations | |
| This is a research tool, **not a medical diagnostic instrument**. | |
| **Crisis Resources:** | |
| - 🆘 Crisis Text Line: Text HOME to 741741 (US) | |
| - 🌍 International: [befrienders.org](https://befrienders.org) |