MCP server: One MCP server.

Pomera AI Commander

@matbanikRun by its publisher: served from their own domain, namespace checked by the registry.MCP server · External

Desktop text workbench + MCP server: 22+ text processing tools for AI assistants

Freeno charge per call

Runs on your machine from its package; the steps are below.

Messy text → clean output → extracted URLs/emails → ready to ship
From the README

What it does

  1. Reads
  2. Writes
  3. High impact

At most: creates or changes data: records, files, settings.

What it costs

Free

Odel charges nothing per call. The publisher may charge for its own service.

Runs locally over stdio

This server isn't hosted — your MCP client launches it from a package registry. Use one of the commands below, or drop the config into your client (e.g. Claude Desktop).

PyPIpomera-ai-commanderv1.5.1

Run

uvx pomera-ai-commander

MCP client config

{
  "mcpServers": {
    "pomera-ai-commander": {
      "command": "uvx",
      "args": [
        "pomera-ai-commander"
      ]
    }
  }
}
npmpomera-ai-commanderv1.5.1

Run

npx -y pomera-ai-commander

MCP client config

{
  "mcpServers": {
    "pomera-ai-commander": {
      "command": "npx",
      "args": [
        "-y",
        "pomera-ai-commander"
      ]
    }
  }
}
README2 min read

Pomera AI Commander (PAC)

Pomera - the fluffy Pomeranian mascot

Download Latest Release

A desktop text "workbench" + MCP server: clean, transform, extract, and analyze text fast—manually in a GUI or programmatically from AI assistants (Cursor / Claude Desktop / MCP clients).

Stop pasting text into 10 random websites. Pomera (GUI + MCP) - do web searches with MCP and save your work as Pomera Notes in case of text corruption in IDE! Your search API keys are stored encrypted in local database instead of JSON config file.

📊 Why AI needs Pomera! - Pomera's MCP tools reduce token usage upto 70-80% for deterministic operations.

Download latest release · Docs: Tools · MCP Guide · CrewAI Integration · Troubleshooting


60-second demo (what to expect)

Messy text → clean output → extracted URLs/emails → ready to ship

Best-for workflows

  • Cleaning pasted logs / PDFs (whitespace, wrapping, stats)
  • Extracting emails/URLs/IDs via regex
  • Normalizing case, sorting, columns
  • Hashing/encoding utilities
  • Letting Cursor/Claude call these as MCP tools in a repeatable pipeline

Prerequisites

Python 3.8+ is required for all installation methods.

macOS (Homebrew)

bash
# Tkinter support (replace @3.14 with your Python version)
brew install python-tk@3.14
pip3 install requests reportlab python-docx

Ubuntu/Debian

bash
sudo apt-get install python3-tk
pip3 install requests reportlab python-docx

Windows

Tkinter is included with Python from python.org.

cmd
pip install requests reportlab python-docx

Note: For PEP 668 protected environments, use pip3 install --user or a virtual environment.


Install / Run

Download from Releases and run.

Option B — Python (PyPI)

bash
pip install pomera-ai-commander
# then run:
pomera-ai-commander --help

Option C — Node.js (npm)

bash
npm install -g pomera-ai-commander
# then run:
pomera-mcp --help

Create Desktop Shortcut

After installing via pip or npm, create a desktop shortcut for quick access:

bash
# For pip install:
pomera-create-shortcut

# For npm install (from package directory):
python create_shortcut.py

MCP Server for AI Assistants

Pomera exposes 22 text processing tools via MCP. Configure your AI assistant:

Cursor (.cursor/mcp.json):

json
{
  "mcpServers": {
    "pomera": {
      "command": "pomera-ai-commander",
      "timeout": 3600
    }
  }
}

Claude Desktop (claude_desktop_config.json):

json
{
  "mcpServers": {
    "pomera": {
      "command": "pomera-ai-commander",
      "timeout": 3600
    }
  }
}

💡 Tip: If the simple command doesn't work, use the full path. Find it with:

bash
# For npm install:
npm root -g
# Then use: <result>/pomera-ai-commander/pomera_mcp_server.py

# For pip install:
pip show pomera-ai-commander | grep Location

⏱️ Timeout: The "timeout": 3600 setting (in seconds) prevents MCP request timeouts during long-running AI operations like research and deepreasoning. Cline, Cursor, and Claude Desktop all default to a 60-second timeout, which is too short for AI calls involving web search + deep reasoning (60-300s). See Cline #1306.

See the full MCP Server Guide for Antigravity, executable configs, and troubleshooting.


License

MIT License - see LICENSE for details.

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