semvec/pypi-packages huggingface dataset:
muck-out 0.3.16
Provides normalization into pydantic objects for ActivityPub objects
Requires Python: >=3.11

# bovine - muck_out

The goal of this package is to provide normalization
routines for ActivityPub data. This means you input
some dictionary and get a [pydantic](https://docs.pydantic.dev/latest/) object back.

See [the documentation](https://bovine.codeberg.page/muck_out/)
for details.

* [@bovine/muck-out-types](https://codeberg.org/bovine/-/packages/npm/@bovine%2Fmuck-out-types/) a typescript package with the tpes generated from the muck_out schemas
* [@bovine/mucked_out_components](https://codeberg.org/bovine/mucked_up_components) preact components based on the muck_out types and other utilities to build Fediverse apps

## Development

Development is done using uv.

### Running tests

Download the test data from [funfedi.dev](https://funfedi.dev/) using

```bash
./resources/download_test_data.sh 
```

The script just runs two curl commands. Then you can run the tests using

```bash
uv run pytest
```

One can only run the doctests for the docs with `uv run pytest docs`.

### Generate json schemas

```bash
python -mmuck_out schemas
```
iflow-mcp_crewaiinc-enterprise-mcp-server 0.1.0
Add your description here
Requires Python: >=3.12

# CrewAI Enterprise MCP Server

## Overview

A Model Context Protocol (MCP) server implementation that provides deployed CrewAI workflows. This server enables kicking off your deployed crew and inspect the status giving the results of your crew.

## Tools

- kickoff_crew
- get_crew_status

## Env Variables

retrieve from app.crewai.com
`MCP_CREWAI_ENTERPRISE_SERVER_URL`
`MCP_CREWAI_ENTERPRISE_BEARER_TOKEN`

# Usage with Claude Desktop

![Claude Desktop with CrewAI Enterprise MCP Server](assets/tools.jpg)
![Claude Desktop with CrewAI Enterprise MCP Server](assets/kickoff.jpg)
![Claude Desktop with CrewAI Enterprise MCP Server](assets/status.jpg)

To use this MCP server with Claude Desktop, follow these steps:

1. Open Claude Desktop
2. Go to Settings > Developer Settings
3. Add a new MCP server with the configuration shown below

## Locally, cloned repo:

Install `mcp` and `mcp[cli]` locally

```json
{
  "mcpServers": {
    "crewai_enterprise_server": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "mcp[cli]",
        "mcp",
        "run",
        "<filepath of cloned repo>",
        "/crewai_enterprise_server.py"
      ],
      "env": {
        "MCP_CREWAI_ENTERPRISE_SERVER_URL": "<>",
        "MCP_CREWAI_ENTERPRISE_BEARER_TOKEN": "<>"
      }
    }
  }
}
```

## TODO: Added on PyPI: