semvec/pypi-packages huggingface dataset:
iflow-mcp_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/Brucedh/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>"
      }
    }
  }
}
```
rma-kinetics 0.1.0
Kinetic models for released markers of activity.
Requires Python: >=3.10

# RMA Kinetics

Source code for "Modeling kinetics of synthetic serum markers for monitoring deep tissue gene expression".

## Getting Started

### Basic Usage

There are three main model classes for constitutive or drug induced RMA expression.

1. ConstitutiveRMA.
2. TetRMA (Tet-Off based marker expression).
3. ChemogeneticRMA (CNO induced marker expression with Tet-Off gating).

Models can be initialized from these classes and ran using the `simulate` method.

For example, to run the constitutive RMA expression model for 72 hours,

```python
from rma_kinetics.models import ConstitutiveRMA
import matplotlib.pyplot as plt

# initialize constitutive RMA model
model = ConstitutiveRMA(
    rma_prod_rate=7e-3,
    rma_rt_rate=1,
    rma_deg_rate=7e-3
)

# simulate model and plot plasma RMA
solution = model.simulate(t0=0, t1=72, y0=(0,0))
solution.plot_plasma_rma()
plt.gcf()
```

## Web App

To run locally, install marimo (available in the development dependencies) in
your virtual environment and run `marimo run app/main.py` or use the provided Just
command `just app-serve` to start the server.
Alternatively, if using uvx, `uvx marimo run app/main.py`.

## Notebooks

Notebooks can be found in the `notebooks` directory and require installing
development dependencies.

Note that the `diffopt` package requires OpenMPI. Please install openMPI or use
the provided [Nix shell](./shell.nix) (i.e., with `nix shell` from the project root).
simple_irc_bot 1.0.9
Simple IRC bot library

# ircbot

A minimal IRC bot library using the `irc` package.

## Installation

```bash
pip install simple-irc-bot
```

## Usage
```python
import ircbot

bot = ircbot.Bot("server:port","nick")

def cmd_echo(*args):
    bot.send(" ".join(args))

bot.add_command("echo",cmd_echo)

bot.cmd_prefix = "&"

bot.start("#testchannel")
```

Do not use SSL as it's not supported.