semvec/pypi-packages huggingface dataset:
mimirai.mimir-mcp 0.1.0
MCP server for Mimir AI
License: MIT
Requires Python: >=3.8

# Mimir MCP

MCP (Model Context Protocol) server for Mimir AI with authenticated API support.

## Installation

```bash
# Clone the repository
git clone https://github.com/trymimirai/mimir-mcp.git
cd mimir-mcp

# Install the package
pip install -e .
```

## Configuration

This MCP uses our API, and thus requires configuration for the API base URL and authentication token. These can be provided in 2 different ways:

1. **Environment Variables** (prioritized):

   - `MIMIR_API_URL`: The base URL for the API (optional, default: "https://dev.trymimir.ai/api")
   - `MIMIR_API_TOKEN`: Your API authentication token (optional, but required for authenticated endpoints)

2. **Configuration File** (used when environment variables are missing):
   Create a file at `~/.mimir/config.json` with the following structure:

   ```json
   {
     "api_url": "https://dev.trymimir.ai/api",
     "api_token": "your-bearer-token-here"
   }
   ```

   > **Note:** If an environment variable is set, it will take precedence over the corresponding value in the config file. The config file is only read if at least one of the required values is not set as an environment variable.

### Claude Desktop Configuration

To use with Claude desktop, update your Claude configuration file (typically at `%APPDATA%\Claude\claude_desktop_config.json` on Windows) to include the environment variables:

```json
{
  "mcpServers": {
    "Mimir": {
      "command": "mimir-mcp",
      "env": {
        "MIMIR_API_URL": "https://dev.trymimir.ai/api",
        "MIMIR_API_TOKEN": "your-bearer-token-here"
      }
    }
  }
}
```

## Usage

Once installed, you can run the MCP server directly:

```bash
mimir-mcp
```

Or configure it in Claude desktop as described above.
grammarticle 1.1.0
Grammarticle spaCy pipeline
License: MIT
Requires Python: >=3.7

# Grammarticle

<img src="https://raw.githubusercontent.com/upunaprosk/grammarticle/master/logo.png" alt="GrammArticle Logo" width="150" align="right" />

GrammArticle is a RoBERTa-based grammar checker for English article usage. It detects three types of article errors:

1) Missing – when an article is absent but required
2) Wrong – when an incorrect article is used (e.g., "a apple" instead of "an apple", or "the" instead of "a/an")
3) Redundant – when an article is unnecessary (e.g., "the furniture")



## Installation

GrammArticle is trained on publicly available GEC datasets with synthetic augmentation and is available as a SpaCy pipeline.

`pip install grammarticle`

or

```bash
pip install spacy-transformers
python -m spacy download en_core_web_trf
pip install https://huggingface.co/iproskurina/en_grammarticle/resolve/main/en_grammarticle-1-py3-none-any.whl

```

## Usage

```
import grammarticle
nlp = grammarticle.load()
text = "This is sentence"
doc = nlp(text)
for span in doc.spans.get("sc", []): 
    print(f"[{span.label_}] {span.text}")
```

Outputs:
```
[Missing] sentence
```
___


![Example Output](https://raw.githubusercontent.com/upunaprosk/grammarticle/master/example.png)

___