semvec/pypi-packages huggingface dataset:
copilot-offline-installer 1.0.0
Installe les extensions GitHub Copilot + Copilot Chat dans VS Code hors-ligne
Requires Python: >=3.6

# Copilot Offline Installer

Installe les extensions **GitHub Copilot** et **GitHub Copilot Chat** dans VS Code, même sur un PC sans accès au Marketplace.

## Installation

```bash
pip install copilot-offline-installer
```

## Utilisation

Après l'installation via pip, lancez :

```bash
install-copilot
```

Ou bien :

```bash
python -m copilot_offline_installer
```

Cela copie automatiquement les extensions dans le dossier `~/.vscode/extensions/` (ou `%USERPROFILE%\.vscode\extensions\` sur Windows).

## Ensuite

1. Redémarrez VS Code
2. Les extensions GitHub Copilot apparaîtront dans `Ctrl+Shift+X`
3. Connectez-vous à votre compte GitHub

## Proxy

Si vous êtes derrière un proxy, ajoutez dans les settings VS Code (`Ctrl+,`) :

```json
{
    "http.proxy": "http://user:pass@proxy.corp:8080",
    "http.proxyStrictSSL": false
}
```

## Contenu

- GitHub Copilot v1.388.0
- GitHub Copilot Chat v0.38.2026020704
iflow-mcp_rymurr-signal-mcp 0.1.1
Add your description here
Requires Python: >=3.11

# Signal MCP

An [MCP](https://github.com/mcp-signal/mcp) integration for [signal-cli](https://github.com/AsamK/signal-cli) that allows AI agents to send and receive Signal messages.

## Features

- Send messages to Signal users
- Send messages to Signal groups
- Receive and parse incoming messages
- Async support with timeout handling
- Detailed logging

## Prerequisites

This project requires [signal-cli](https://github.com/AsamK/signal-cli) to be installed and configured on your system.

### Installing signal-cli

1. **Install signal-cli**: Follow the [official installation instructions](https://github.com/AsamK/signal-cli/blob/master/README.md#installation)

2. **Register your Signal account**:
   ```bash
   signal-cli -u YOUR_PHONE_NUMBER register
   ```

3. **Verify your account** with the code received via SMS:
   ```bash
   signal-cli -u YOUR_PHONE_NUMBER verify CODE_RECEIVED
   ```

For more detailed setup instructions, see the [signal-cli documentation](https://github.com/AsamK/signal-cli/wiki).

## Installation

```bash
pip install -e .
# or use uv for faster installation
uv pip install -e .
```

## Usage

Run the MCP server:

```bash
./main.py --user-id YOUR_PHONE_NUMBER [--transport {sse|stdio}]
```

## API

### Tools Available

- `send_message_to_user`: Send a direct message to a Signal user
- `send_message_to_group`: Send a message to a Signal group
- `receive_message`: Wait for and receive messages with timeout support

## Development

This project uses:
- [MCP](https://github.com/mcp-signal/mcp) for agent-API integration
- Modern Python async patterns
- Type annotations throughout
epicsdev 2.1.2
Helper module for creating EPICS PVAccess servers using p4p
Requires Python: >=3.7

# epicsdev
Helper module for creating EPICS PVAccess servers.

Demo:
```
python pip install epicsdev
python -m epicsdev.epicsdev
```

To control and plot:
```
python pip install pypeto,pvplot
python -m pypeto -c config -f epicsdev
```

## Multi-channel waveform generator
Module **epicdev.multiadc** can generate large amount of data for stress-testing
the EPICS environment. For example the following command will generate 10000 of 
100-point noisy waveforms and 40000 of scalar parameters per second.
```
python -m epicsdev.multiadc -s0.1 -c10000 -n100
```
The GUI for monitoring:<br>
```python -m pypeto -c config -f multiadc```

The graphs should look like this: 
[control page](docs/epicsdev_pypet.png),
[plots](docs/epicsdev_pvplot.jpg).

Example of [Phoebus display](docs/phoebus_epicsdev.jpg), as defined in config/epicsdev.bob.

## Using AI to generate PVAccess server for arbitrary instruments.
The epicsdev module is designed to be suitable for automatic development using AI agents.<br>
The roadmap to create a server for new instrument using copilot at github:
- Create new repository.
- In the prompt section enter something like this:<br>
'Build device support for Tektronix MSO oscilloscopes using epicsdev_rigol_scope as a template and programming manual at < link to a pdf file >.'
- In 20-40 minutes the copilot will create a pull request.
- Follow instructions to review, commit and merge.

As an example, the generated server for Tektronix MSO oscilloscope was 99% correct and it reqiured very minor modifications.
iflow-mcp_sysdiglabs-aws-ireveal-mcp 0.1.0
AWS incident response and investigation tools
Requires Python: >=3.10

# AWS‑IReveal‑MCP

**AWS‑IReveal‑MCP** is a Model Context Protocol (MCP) server designed to give security teams and incident responders a unified interface to AWS services useful for investigation. By connecting AWS‑IReveal‑MCP to any MCP client (such as Claude Desktop or Cline), you can invoke queries and analyses across multiple AWS services without leaving your LLM‑driven workspace.

## Features

AWS‑IReveal‑MCP integrates with the following AWS services and functionalities:

- **CloudTrail** — Management event logs for API activity  
- **Amazon Athena** — SQL queries over CloudTrail logs  
- **CloudWatch** — Operational logs and ad hoc analysis  
- **Amazon GuardDuty** — Threat detection and finding investigation  
- **AWS Config** — Resource configuration history and compliance status  
- **VPC Flow Logs** — Network traffic metadata for forensic analysis  
- **Network Access Analyzer** — Reachability checks across SG/NACL/VPC  
- **IAM Access Analyzer** — Policy and resource‑based access findings  

Together, these services let you  
- Trace “who did what, when, and where” (CloudTrail, Config)  
- Examine detailed data events (Athena)  
- Search and visualize logs (CloudWatch, VPC Flow Logs)  
- Surface security alerts (GuardDuty, IAM Access Analyzer)  
- Verify network reachability and configuration (Network Access Analyzer)  

### Example Prompts

- analyze activity by IP x.x.x.x in the last 5 days
- analyze activity by role 'sysadmin' in the last 24 hours
- investigate suspicious activity on cloudtrail in the last 7 days on us-west-2
- is there any data event on buckets with name containing 'customers' in the last 7 days?
- investigate cloudwatch logs related to Bedrock
- propose remediations for GuardDuty findings with high risk happened in the last 2 days
- identify non-compliant resources, explain violated rules, and suggest remediation

## Installation

### Prerequisites

- Install UV with:
```bash
curl -Ls https://astral.sh/uv/install.sh | sh
```
- Clone the repo and set up the environment (this will install the required dependencies):
```bash
git clone https://github.com/sysdiglabs/aws-ireveal-mcp.git
cd aws-ireveal-mcp
uv venv
source .venv/bin/activate
```

### Configuration
Add the following configuration to your MCP client's settings file:

```
{
  "mcpServers": {
    "aws-ireveal": {
      "command": "uv",
      "args": [
        "--directory",
        "/path_to_your/aws-ireveal-mcp",
        "run",
        "server.py"
      ],
      "env": {
        "AWS_PROFILE": "<YOUR_PROFILE>"
      }
    }
  }
}
```