Desktop text workbench + MCP server: 22+ text processing tools for AI assistants
Runs on your machine from its package; the steps are below.

At most: creates or changes data: records, files, settings.
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).
Run
uvx pomera-ai-commander
MCP client config
{
"mcpServers": {
"pomera-ai-commander": {
"command": "uvx",
"args": [
"pomera-ai-commander"
]
}
}
}Run
npx -y pomera-ai-commander
MCP client config
{
"mcpServers": {
"pomera-ai-commander": {
"command": "npx",
"args": [
"-y",
"pomera-ai-commander"
]
}
}
}
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

Best-for workflows
Python 3.8+ is required for all installation methods.
# Tkinter support (replace @3.14 with your Python version)
brew install python-tk@3.14
pip3 install requests reportlab python-docx
sudo apt-get install python3-tk
pip3 install requests reportlab python-docx
Tkinter is included with Python from python.org.
pip install requests reportlab python-docx
Note: For PEP 668 protected environments, use
pip3 install --useror a virtual environment.
Download from Releases and run.
pip install pomera-ai-commander
# then run:
pomera-ai-commander --help
npm install -g pomera-ai-commander
# then run:
pomera-mcp --help
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
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:
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": 3600setting (in seconds) prevents MCP request timeouts during long-running AI operations likeresearchanddeepreasoning. 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.
MIT License - see LICENSE for details.