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Merge pull request #66 from Intugle/features/docs-mcp-instructions
Features/docs mcp instructions
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‎docsite/docs/mcp-server.md‎

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Popular clients that support MCP include AI-powered IDEs and standalone applications. Here’s how to configure a few of them:
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- **Cursor**: [Configuring MCP Servers](https://docs.cursor.com/en/context/mcp#configuring-mcp-servers)
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- **Claude Code**: [Using MCP with Claude Code](https://docs.claude.com/en/docs/claude-code/mcp)
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- **Claude Desktop**: [User Quickstart](https://modelcontextprotocol.info/docs/quickstart/user/)
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- **Gemini CLI**: [Configure MCP Servers](https://cloud.google.com/gemini/docs/codeassist/use-agentic-chat-pair-programmer#configure-mcp-servers)
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<details>
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<summary><b>Install in Cursor</b></summary>
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Go to: `Settings` -> `Cursor Settings` -> `MCP` -> `Add new global MCP server`
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Pasting the following configuration into your Cursor `~/.cursor/mcp.json` file is the recommended approach. See [Cursor MCP docs](https://docs.cursor.com/context/model-context-protocol) for more info.
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```json
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{
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"mcpServers": {
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"intugle": {
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"url": "http://localhost:8080/semantic_layer/mcp",
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"trust": true
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}
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}
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}
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```
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</details>
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<details>
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<summary><b>Install in VS Code</b></summary>
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Add this to your VS Code `settings.json` file. See [VS Code MCP docs](https://code.visualstudio.com/docs/copilot/chat/mcp-servers) for more info.
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```json
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"mcp": {
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"servers": {
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"intugle": {
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"type": "http",
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"url": "http://localhost:8080/semantic_layer/mcp"
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}
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}
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}
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```
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</details>
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<details>
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<summary><b>Install in Gemini CLI</b></summary>
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See [Gemini CLI Configuration](https://google-gemini.github.io/gemini-cli/docs/tools/mcp-server.html) for details.
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1. Open the Gemini CLI settings file at `~/.gemini/settings.json`.
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2. Add the following to the `mcpServers` object in your `settings.json` file:
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```json
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{
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"mcpServers": {
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"intugle": {
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"httpUrl": "http://localhost:8080/semantic_layer/mcp",
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"trust" : true
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}
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}
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}
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```
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If the `mcpServers` object does not exist, create it.
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</details>
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<details>
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<summary><b>Install in JetBrains AI Assistant</b></summary>
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See [JetBrains AI Assistant Documentation](https://www.jetbrains.com/help/ai-assistant/configure-an-mcp-server.html) for more details.
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1. In your JetBrains IDE, go to `Settings` -> `Tools` -> `AI Assistant` -> `Model Context Protocol (MCP)`.
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2. Click `+ Add`.
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3. Select `As JSON` from the list.
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4. Add this configuration and click `OK`:
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```json
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{
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"mcpServers": {
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"intugle": {
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"type": "streamable-http",
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"url": "http://localhost:8080/semantic_layer/mcp"
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}
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}
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}
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```
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5. Click `Apply` to save changes.
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</details>
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<details>
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<summary><b>Install in Claude Code</b></summary>
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Run this command in your terminal. See [Claude Code MCP docs](https://docs.anthropic.com/en/docs/claude-code/mcp) for more info.
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```sh
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claude mcp add --transport http intugle http://localhost:8080/semantic_layer/mcp
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```
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</details>
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## 2. Data Discovery Tools
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‎docsite/docs/vibe-coding.md‎

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Popular clients that support MCP include AI-powered IDEs and standalone applications. Here’s how to configure a few of them:
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- **Cursor**: [Configuring MCP Servers](https://docs.cursor.com/en/context/mcp#configuring-mcp-servers)
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- **Claude Code**: [Using MCP with Claude Code](https://docs.claude.com/en/docs/claude-code/mcp)
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- **Claude Desktop**: [User Quickstart](https://modelcontextprotocol.info/docs/quickstart/user/)
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- **Gemini CLI**: [Configure MCP Servers](https://cloud.google.com/gemini/docs/codeassist/use-agentic-chat-pair-programmer#configure-mcp-servers)
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<details>
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<summary><b>Install in Cursor</b></summary>
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Go to: `Settings` -> `Cursor Settings` -> `MCP` -> `Add new global MCP server`
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Pasting the following configuration into your Cursor `~/.cursor/mcp.json` file is the recommended approach. See [Cursor MCP docs](https://docs.cursor.com/context/model-context-protocol) for more info.
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```json
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{
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"mcpServers": {
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"intugle": {
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"url": "http://localhost:8080/semantic_layer/mcp",
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"trust": true
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}
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}
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}
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```
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</details>
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<details>
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<summary><b>Install in VS Code</b></summary>
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Add this to your VS Code `settings.json` file. See [VS Code MCP docs](https://code.visualstudio.com/docs/copilot/chat/mcp-servers) for more info.
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```json
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"mcp": {
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"servers": {
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"intugle": {
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"type": "http",
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"url": "http://localhost:8080/semantic_layer/mcp"
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}
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}
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}
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```
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</details>
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<details>
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<summary><b>Install in Gemini CLI</b></summary>
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See [Gemini CLI Configuration](https://google-gemini.github.io/gemini-cli/docs/tools/mcp-server.html) for details.
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1. Open the Gemini CLI settings file at `~/.gemini/settings.json`.
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2. Add the following to the `mcpServers` object in your `settings.json` file:
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```json
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{
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"mcpServers": {
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"intugle": {
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"httpUrl": "http://localhost:8080/semantic_layer/mcp",
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"trust" : true
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}
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}
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}
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```
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If the `mcpServers` object does not exist, create it.
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</details>
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<details>
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<summary><b>Install in JetBrains AI Assistant</b></summary>
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See [JetBrains AI Assistant Documentation](https://www.jetbrains.com/help/ai-assistant/configure-an-mcp-server.html) for more details.
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1. In your JetBrains IDE, go to `Settings` -> `Tools` -> `AI Assistant` -> `Model Context Protocol (MCP)`.
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2. Click `+ Add`.
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3. Select `As JSON` from the list.
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4. Add this configuration and click `OK`:
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```json
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{
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"mcpServers": {
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"intugle": {
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"type": "streamable-http",
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"url": "http://localhost:8080/semantic_layer/mcp"
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}
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}
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}
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```
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5. Click `Apply` to save changes.
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</details>
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<details>
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<summary><b>Install in Claude Code</b></summary>
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Run this command in your terminal. See [Claude Code MCP docs](https://docs.anthropic.com/en/docs/claude-code/mcp) for more info.
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```sh
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claude mcp add --transport http intugle http://localhost:8080/semantic_layer/mcp
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```
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</details>
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## 2. Vibe Coding
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‎pyproject.toml‎

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[project]
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name = "intugle"
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version = "1.0.5"
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version = "1.0.6"
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authors = [
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{ name="Intugle", email="hello@intugle.ai" },
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]

‎src/intugle/mcp/docs_search/service.py‎

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BASE_URL = "https://raw.githubusercontent.com/Intugle/data-tools/main/docsite/docs/"
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API_URL = "https://api.github.com/repos/Intugle/data-tools/contents/docsite/docs"
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BLACKLISTED_ROUTES = ["mcp-server.md", "vibe-coding.md"]
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def __init__(self):
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self._doc_paths = None
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for item in items:
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if item['type'] == 'file' and (item['name'].endswith('.md') or item['name'].endswith('.mdx')):
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# Strip the base 'docsite/docs/' part to make it a relative path
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paths.append(item['path'].replace('docsite/docs/', '', 1))
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relative_path = item['path'].replace('docsite/docs/', '', 1)
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if relative_path not in self.BLACKLISTED_ROUTES:
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paths.append(relative_path)
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elif item['type'] == 'dir':
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paths.extend(await self._fetch_paths_recursively(session, item['url']))
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except Exception as e:

‎uv.lock‎

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