diff --git a/.gitignore b/.gitignore index 521903f..68b4606 100644 --- a/.gitignore +++ b/.gitignore @@ -24,6 +24,9 @@ env/ # IDE .vscode/ +!.vscode/ +.vscode/* +!.vscode/mcp.json .idea/ *.swp *.swo @@ -84,4 +87,4 @@ site/ *.log *.tmp temp/ -tmp/ \ No newline at end of file +tmp/ diff --git a/.vscode/mcp.json b/.vscode/mcp.json new file mode 100644 index 0000000..65098fd --- /dev/null +++ b/.vscode/mcp.json @@ -0,0 +1,9 @@ +{ + "servers": { + "shortkit-ml": { + "type": "stdio", + "command": ".venv/bin/python", + "args": ["-m", "shortcut_detect.mcp_server"] + } + } +} \ No newline at end of file diff --git a/README.md b/README.md index 517fcfc..29a1655 100644 --- a/README.md +++ b/README.md @@ -177,13 +177,22 @@ Custom conditions can be registered via `@register_condition("name")`. See [Cond ## MCP Server -ShortKit-ML ships an [MCP](https://modelcontextprotocol.io/) server so AI assistants (Claude, Cursor, etc.) can call detection tools directly from chat — no Python script required. +ShortKit-ML ships an [MCP](https://modelcontextprotocol.io/) server so AI assistants (Claude, Cursor, GitHub Copilot in VS Code, etc.) can call detection tools directly from chat — no Python script required. ```bash uv pip install -e ".[mcp]" ``` -Full setup instructions for **Claude Code** and **Claude Desktop**, available tools, file-based input, and troubleshooting: [**criticaldata.github.io/ShortKit-ML/mcp-server**](https://criticaldata.github.io/ShortKit-ML/mcp-server/). +### GitHub Copilot in VS Code + +1. After installing the MCP extra, open VS Code and go to Settings (Ctrl+,). +2. Search for "GitHub Copilot Chat: MCP" and open the JSON settings. +3. Copy the server configuration from the repo's `.vscode/mcp.json` file into the `github.copilot.chat.mcp` object in your settings. +4. Ensure the `"command"` path points to your virtual environment's Python (e.g., update `.venv/bin/python` to the full path if needed). +5. Restart VS Code or reload the GitHub Copilot Chat extension. +6. The ShortKit-ML tools will now be available in Copilot Chat sessions. + +Full setup instructions for **Claude Code**, **Claude Desktop**, and **GitHub Copilot in VS Code**, available tools, file-based input, and troubleshooting: [**criticaldata.github.io/ShortKit-ML/mcp-server**](https://criticaldata.github.io/ShortKit-ML/mcp-server/). ## Paper Benchmark Datasets diff --git a/docs/mcp-server.md b/docs/mcp-server.md index a189313..cfdce8e 100644 --- a/docs/mcp-server.md +++ b/docs/mcp-server.md @@ -1,6 +1,6 @@ # MCP Server -ShortKit-ML ships a [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) server that exposes shortcut detection as callable tools. AI assistants like Claude can run full analyses — generate data, run detectors, compare methods — directly from chat, with no Python script required. +ShortKit-ML ships a [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) server that exposes shortcut detection as callable tools. AI assistants like Claude and GitHub Copilot in VS Code can run full analyses — generate data, run detectors, compare methods — directly from chat, with no Python script required. ## Prerequisites @@ -18,8 +18,6 @@ uv run python -m shortcut_detect.mcp_server The server should start without errors. Press `Ctrl+C` to stop it. ---- - ## Option 1 — Claude Code (recommended) Claude Code reads a `.mcp.json` file from the project root. This file is already committed to the repo, so no manual setup is needed after installing the package. @@ -215,3 +213,37 @@ To reuse a previous run: ``` Get the summary for session_id "my-run-1" ``` + +--- + +## GitHub Copilot in VS Code + +GitHub Copilot Chat in VS Code can consume the same MCP server through Agent mode. This repository includes a checked-in `.vscode/mcp.json` template so the ShortKit-ML server is ready to use once your `.venv` is installed. + +### 1. Install dependencies + +```bash +uv pip install -e ".[mcp]" +``` + +### 2. Open the workspace in VS Code + +Make sure the repo root is open so VS Code can read `.vscode/mcp.json`. + +### 3. Start Copilot Chat in Agent mode + +Open Copilot Chat, switch the mode dropdown to **Agent**, and open the tools list. You should see the `shortkit-ml` MCP server and the ShortKit-ML tools. + +### 4. Try a prompt + +```text +Generate 200 synthetic samples with a linear shortcut and run probe, statistical, and hbac on them. +``` + +### 5. Customize the Python path if needed + +Edit `.vscode/mcp.json` and point `command` at your workspace `.venv/bin/python` path. Use the same `shortcut_detect.mcp_server` module entry point as Claude Code and Claude Desktop. + +### Manual verification + +The repository-level config and tests are in place, but the Copilot Chat smoke test itself still needs to be confirmed in VS Code by opening the tools panel and running a real prompt. diff --git a/output/shortcut_report.html b/output/shortcut_report.html new file mode 100644 index 0000000..f4a39d4 --- /dev/null +++ b/output/shortcut_report.html @@ -0,0 +1,160 @@ + + + + + Shortcut Detection Report + + + +
+

🔍 Shortcut Detection Report

+ +
+

📋 Dataset Information

+ + + + + +
Samples:200
Embedding Dimensions:32
Detection Methods:statistical, geometric, probe, frequency
Unique Labels:2
+
+ +

🟡 MODERATE RISK: One method detected shortcuts

+
+

📊 Visualizations

+
+

PCA Projection

PCA Plot
+

t-SNE Projection

t-SNE Plot
+
+

3D Embedding Analysis

3D Embedding Plot
+
+Interactive 3D + +

Static view (if interactive does not load):

+3D static +
+

Statistical Test P-values

Top 20 most significant dimensions shown by default.

P-value Heatmap +
Expand to full heatmap
P-value Heatmap (Full)

Download full heatmap (PNG)

+
+
+ +
+

🧭 Geometric Analysis

+

Risk: Moderate

+

Reason: One geometric test indicates shortcut risk.

+

One geometric test indicates shortcut risk.

+

Top Bias Direction Pairs

+ + +
GroupsEffect SizeProjection GapAlignment
0 vs 10.4540.1670.623
+

Top Subspace Overlap Pairs

+ + +
GroupsMean CosineMin Angle (°)Max Angle (°)
0 vs 10.9516.033.6
+
+
+

🔬 Probe-based Detection

+

Risk: Low

+

Reason: f1 (0.529) compared against threshold (0.700).

+

f1: 52.94%

+
+
+

Embedding Frequency Shortcut

+

Risk: Low

+

Reason: 0/2 classes exceeded TPR/FPR thresholds (0.500/0.150).

+

Probe accuracy: 67.00%

+

Shortcut classes: []

+

Top-percent used: 0.05

+

Class Rates

+ + + + +
ClassTPRFPRSupportTop Dims
00.6630.323101[]
10.6770.33799[28, 18]
+
+
+

📈 Statistical Testing

+

Risk: Low

+

Reason: 0/1 comparisons have significant features after FDR_BH (alpha=0.050).

+

Group Comparisons

+ + + +
ComparisonSignificant Features
0_vs_10
+
+ + + + + + + + + + + + +
+

💡 Recommendations

+
No strong shortcuts detected. Continue monitoring with larger/different datasets.
+
General advice: Always validate findings with domain experts and test mitigation strategies on held-out data.
+
+ + + +
+ + \ No newline at end of file diff --git a/output/test_embeddings.csv b/output/test_embeddings.csv new file mode 100644 index 0000000..a9682d8 --- /dev/null +++ b/output/test_embeddings.csv @@ -0,0 +1,201 @@ +0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31 +-0.09145258427709382,-0.17849121278569424,-0.05880513244711306,0.0930291016500941,0.4571747620441146,0.10947182527678051,-0.10433710603407254,0.10820094029982241,-0.01686672257781897,-0.20509501687929405,0.058025776937228137,0.29655318761380073,-0.27146797082339064,-0.08183681441289134,0.2433864306486082,-0.2376324282881474,-0.11474282538877253,0.07588728114969266,-0.020034006397918903,-0.17181404222939076,0.010546749778843031,-0.046487395695518505,0.16035161599648975,0.09354142980914945,-0.2191358571070429,-0.14912660401884537,0.16012623365677495,-0.03956964514748189,0.10448289496781424,-0.37953539692284904,0.1392165877672382,0.13011221423983432 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diff --git a/output/test_group_labels.csv b/output/test_group_labels.csv new file mode 100644 index 0000000..ea85198 --- /dev/null +++ b/output/test_group_labels.csv @@ -0,0 +1,201 @@ +group +0 +1 +0 +0 +0 +1 +0 +0 +0 +1 +0 +0 +0 +0 +1 +0 +1 +1 +1 +0 +1 +0 +1 +1 +1 +1 +1 +1 +1 +1 +0 +0 +1 +1 +1 +0 +1 +0 +0 +0 +0 +0 +1 +1 +1 +1 +1 +0 +1 +1 +0 +1 +0 +1 +0 +1 +1 +0 +0 +0 +0 +0 +0 +0 +0 +1 +1 +0 +1 +1 +1 +1 +0 +1 +0 +1 +1 +1 +0 +1 +0 +1 +0 +1 +0 +0 +1 +0 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +0 +0 +1 +1 +1 +1 +1 +1 +1 +1 +0 +1 +0 +1 +1 +0 +1 +0 +1 +1 +0 +1 +0 +1 +0 +0 +1 +1 +0 +1 +1 +1 +0 +0 +0 +0 +0 +0 +0 +0 +0 +1 +0 +1 +1 +1 +0 +0 +0 +0 +1 +0 +0 +0 +0 +0 +1 +0 +1 +0 +1 +0 +0 +1 +1 +1 +0 +1 +0 +0 +1 +1 +0 +0 +1 +1 +1 +0 +0 +0 +0 +0 +0 +1 +0 +0 +0 +1 +0 +0 +1 +0 +0 +0 +0 +0 +1 +1 +1 +0 +0 diff --git a/output/test_group_labels.json b/output/test_group_labels.json new file mode 100644 index 0000000..9353813 --- /dev/null +++ b/output/test_group_labels.json @@ -0,0 +1 @@ +[0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0] \ No newline at end of file diff --git a/output/test_labels.csv b/output/test_labels.csv new file mode 100644 index 0000000..0155e70 --- /dev/null +++ b/output/test_labels.csv @@ -0,0 +1,201 @@ +label +0 +1 +0 +0 +1 +1 +0 +0 +0 +1 +0 +0 +0 +0 +1 +1 +0 +1 +0 +0 +1 +1 +1 +1 +1 +1 +0 +0 +1 +1 +0 +0 +1 +1 +0 +0 +1 +0 +0 +0 +0 +0 +1 +1 +1 +1 +1 +0 +1 +1 +1 +1 +0 +1 +0 +1 +1 +0 +0 +0 +0 +0 +0 +0 +0 +1 +1 +0 +1 +1 +1 +1 +0 +1 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1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0] \ No newline at end of file diff --git a/shortcut_detect/mcp_server.py b/shortcut_detect/mcp_server.py index cb813af..b1aff3a 100644 --- a/shortcut_detect/mcp_server.py +++ b/shortcut_detect/mcp_server.py @@ -1020,12 +1020,12 @@ def run_benchmark( # --------------------------------------------------------------------------- -@mcp.tool(name="list_methods") +@mcp.tool(name="list_methods", description="List all available shortcut detection methods with short descriptions.") def list_methods_tool() -> str: return list_methods() -@mcp.tool(name="generate_synthetic_data") +@mcp.tool(name="generate_synthetic_data", description="Generate synthetic shortcut detection data with configurable type, strength, and size.") def generate_synthetic_data_tool( n_samples: int = 200, n_features: int = 32, @@ -1044,7 +1044,7 @@ def generate_synthetic_data_tool( ) -@mcp.tool(name="run_detector") +@mcp.tool(name="run_detector", description="Run one or more shortcut detection methods on embeddings and return a summary result.") async def run_detector_tool( embeddings: list[list[float]] | None = None, labels: list[int] | None = None, @@ -1076,7 +1076,7 @@ async def run_detector_tool( return json.dumps({"error": traceback.format_exc()}) -@mcp.tool(name="get_summary") +@mcp.tool(name="get_summary", description="Retrieve a human-readable summary for a previous shortcut detection session.") async def get_summary_tool( session_id: str = "default", ctx: Context | None = None, @@ -1093,7 +1093,7 @@ async def get_summary_tool( return str(session["summary"]) -@mcp.tool(name="get_method_detail") +@mcp.tool(name="get_method_detail", description="Get detailed raw results for a specific detection method from a stored session.") async def get_method_detail_tool( method: str, session_id: str = "default", @@ -1112,7 +1112,7 @@ async def get_method_detail_tool( return json.dumps(_safe_serialize(raw[method]), indent=2) -@mcp.tool(name="compare_methods") +@mcp.tool(name="compare_methods", description="Compare multiple shortcut detection methods side-by-side and return a consensus summary.") async def compare_methods_tool( embeddings: list[list[float]] | None = None, labels: list[int] | None = None, @@ -1140,7 +1140,7 @@ async def compare_methods_tool( return json.dumps({"error": traceback.format_exc()}) -@mcp.tool(name="generate_report") +@mcp.tool(name="generate_report", description="Generate an HTML/PDF/Markdown report for a saved session and optionally return encoded content.") async def generate_report_tool( session_id: str = "default", output_path: str | None = None, @@ -1173,7 +1173,7 @@ async def generate_report_tool( return json.dumps({"error": traceback.format_exc()}) -@mcp.tool(name="run_benchmark") +@mcp.tool(name="run_benchmark", description="Run the full synthetic benchmark suite or a provided benchmark configuration.") async def run_benchmark_tool( config: dict[str, Any] | None = None, config_path: str | None = None, diff --git a/tests/test_copilot_mcp_config.py b/tests/test_copilot_mcp_config.py new file mode 100644 index 0000000..f827883 --- /dev/null +++ b/tests/test_copilot_mcp_config.py @@ -0,0 +1,21 @@ +"""Tests for the checked-in Copilot / MCP workspace configuration.""" + +import json +from pathlib import Path + + +def test_vscode_mcp_config_matches_project_entrypoint(): + root = Path(__file__).resolve().parents[1] + claude_config = json.loads((root / ".mcp.json").read_text(encoding="utf-8")) + vscode_config = json.loads((root / ".vscode" / "mcp.json").read_text(encoding="utf-8")) + + claude_server = claude_config["mcpServers"]["shortkit-ml"] + vscode_server = (vscode_config.get("mcpServers") or vscode_config.get("servers"))["shortkit-ml"] + + assert claude_server["type"] == "stdio" + assert vscode_server["type"] == "stdio" + assert claude_server["command"] == vscode_server["command"] == ".venv/bin/python" + assert claude_server["args"] == vscode_server["args"] == [ + "-m", + "shortcut_detect.mcp_server", + ]