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Pomera AI Commander

matbanik/pomera-ai-commander
2STDIOregistry active
Summary

Exposes 22 text processing operations as MCP tools: case normalization, whitespace cleanup, email and URL extraction via regex, sorting, hashing, and encoding utilities. Built for cleaning messy logs or PDFs and running repeatable text pipelines from Cursor or Claude Desktop without pasting into random web tools. The developer claims token savings of 70-80% on deterministic operations by offloading string manipulation outside the LLM context window. Ships as a standalone desktop GUI plus stdio MCP server, installable via pip or npm. Includes encrypted storage for search API keys and a notes system for saving intermediate results. Supports Python 3.8+ with Tkinter across macOS, Linux, and Windows.

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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)

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

Ubuntu/Debian

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

Windows

Tkinter is included with Python from python.org.

pip install requests reportlab python-docx

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


Install / Run

Option A — Prebuilt executable (recommended)

Download from Releases and run.

Option B — Python (PyPI)

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

Option C — Node.js (npm)

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:

# 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):

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

Claude Desktop (claude_desktop_config.json):

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

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

# 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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Registryactive
Packagepomera-ai-commander
TransportSTDIO
UpdatedMay 31, 2026
View on GitHub