Update README: document dataset structure and HF Jobs setup

README.md

@@ -1,37 +1,47 @@
----
-license: mit
-tags:
-- agent
-- code
-pretty_name: MCP Client Information
-size_categories:
-- 1K<n<10K
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-dataset_info:
-  features:
-  - name: name
-    dtype: string
-  - name: version
-    dtype: string
-  - name: capabilities
-    dtype: string
-  - name: last_seen
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 4744
-    num_examples: 55
-  download_size: 4190
-  dataset_size: 4744
----
-
+# MCP Clients Dataset
 
 This data contains clients logged by the MCP Server at `huggingface.co/mcp`. 
 
-Some notes about the data:
- - Some Clients only send capabilities that have been configured (for example, `fast-agent` only sends the `roots` capability if they have been configured)
- - There are a number of capabilities out of specification that are helpful to track (e.g. MCP-UI, Skybridge, Apps SDK). We encourage the use of `experimental` to advertise these capabilities for tracking.
+## Dataset Contents
+
+The dataset contains unique MCP client configurations with the following fields:
+- **name**: MCP client name (e.g., "Cursor", "Anthropic/ClaudeAI", "chat-ui-mcp")
+- **version**: Client version
+- **capabilities**: Client capabilities (JSON string)
+- **last_seen**: Most recent timestamp when this client was seen
+
+## Notes about the Data
+
+- Some Clients only send capabilities that have been configured (for example, `fast-agent` only sends the `roots` capability if they have been configured)
+- There are a number of capabilities out of specification that are helpful to track (e.g. MCP-UI, Skybridge, Apps SDK). We encourage the use of `experimental` to advertise these capabilities for tracking.
+- The data is extracted from the `evalstate/hf-mcp-logs` dataset, filtering for `initialize` method calls and tracking the most recent `last_seen` timestamp for each unique client configuration.
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset('evalstate/mcp-clients', split='train')
+for client in ds:
+    print(f"{client['name']} v{client['version']}")
+    print(f"Capabilities: {client['capabilities']}")
+    print(f"Last seen: {client['last_seen']}")
+```
+
+## Updating the Dataset
+
+The dataset is kept up-to-date via Hugging Face Jobs, which runs the `mcp_clients_job.py` script on a schedule.
+
+To run the extraction script locally for testing:
+
+```bash
+# Run with limit (for testing)
+uv run mcp_clients_job.py --limit 10000
+
+# Run on full dataset
+uv run mcp_clients_job.py
+```
+
+## License
+
+MIT