Update README.md

README.md

@@ -11,4 +11,118 @@ license: mit
 short_description: Gradio Whisper Transcription App (MCP)
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Here's a complete `README.md` tailored for your project hosted at [https://huggingface.co/spaces/Dreamcatcher23/mcp-server-track](https://huggingface.co/spaces/Dreamcatcher23/mcp-server-track). It assumes you're offering an audio transcription service using OpenAI's Whisper via Modal and exposing it as an MCP-compliant server using Gradio:
+
+---
+
+```markdown
+# 🎙️ Whisper Transcription Tool – MCP Server
+
+Welcome to the **MCP Server Track** submission for the Hugging Face & OpenAI Agents Hackathon!
+
+This tool provides speech-to-text transcription using OpenAI’s Whisper model, deployed via [Modal](https://modal.com/), and exposes the service through a Gradio interface that supports the **Model Context Protocol (MCP)**. Agents can access this tool via HTTP or streaming endpoints.
+
+---
+
+## 🧠 What It Does
+
+- Accepts an audio URL (MP3, WAV, FLAC, etc.)
+- Transcribes the speech to text using Whisper (`base` model)
+- Returns clean, readable output
+- Exposes an MCP-compliant API endpoint
+
+---
+
+## 🚀 How to Use
+
+### 🔹 Web Interface (UI)
+1. Enter an audio URL (e.g., a `.flac` or `.wav` file).
+2. Click the **Submit** button.
+3. View the transcribed text output instantly.
+
+### 🔹 As an MCP Tool (Programmatic Access)
+This app can be invoked by agents (e.g., SmolAI, LangChain, or custom agent scripts) using the MCP specification.
+
+- Endpoint: `/predict`
+- Method: POST
+- Input Schema: `{ "data": [ "AUDIO_URL_HERE" ] }`
+- Output Schema: `{ "data": [ "TRANSCRIPTION_TEXT" ] }`
+
+---
+
+## 🛠️ Stack
+
+| Layer        | Tech                                |
+|--------------|-------------------------------------|
+| Frontend     | [Gradio](https://gradio.app/)       |
+| Inference    | [OpenAI Whisper](https://github.com/openai/whisper) |
+| Hosting      | [Hugging Face Spaces](https://huggingface.co/spaces) |
+| Remote Compute | [Modal](https://modal.com/)       |
+| Protocol     | Model Context Protocol (MCP)        |
+
+---
+
+## 📦 Example Input
+
+```
+
+[https://huggingface.co/datasets/Narsil/asr\_dummy/resolve/main/mlk.flac](https://huggingface.co/datasets/Narsil/asr_dummy/resolve/main/mlk.flac)
+
+```
+
+Expected output:
+
+```
+
+I have a dream that one day this nation will rise up and live out the true meaning of its creed.
+
+````
+
+---
+
+## 📎 Notes
+
+- Supports English only (for now).
+- Long-form audio and larger models (e.g., `medium`, `large`) can be added later.
+- You can extend it to support file uploads or streaming audio.
+
+---
+
+## 🤖 Hackathon Submission
+
+- Track: `mcp-server-track`
+- MCP-Enabled: ✅
+- Repo/Space: [Dreamcatcher23/mcp-server-track](https://huggingface.co/spaces/Dreamcatcher23/mcp-server-track)
+
+---
+
+## 📚 References
+
+- [Modal Docs](https://modal.com/docs)
+- [Whisper GitHub](https://github.com/openai/whisper)
+- [Gradio MCP Guide](https://huggingface.co/docs/hub/spaces-sse)
+- [Agents Hackathon](https://huggingface.co/agents)
+
+---
+
+## 🧪 MCP Test Instructions
+
+Use tools like [curl](https://curl.se/), Postman, or a Python client to test the API:
+
+```bash
+curl -X POST https://your-space-url/predict \
+    -H "Content-Type: application/json" \
+    -d '{"data":["https://huggingface.co/datasets/Narsil/asr_dummy/resolve/main/mlk.flac"]}'
+````
+
+---
+
+## ✨ Built with ❤️ by Dreamcatcher23
+
+```
+
+---
+
+Let me know if you'd like a badge version (e.g., Hugging Face badge, Modal run badge) or Markdown preview for your Hugging Face Space directly!
+```
+