Pomera-AI-Commander/context7.json at master · matbanik/Pomera-AI-Commander · GitHub

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{
    "$schema": "https://context7.com/schema/context7.json",
    "url": "https://context7.com/matbanik/pomera-ai-commander",
    "public_key": "pk_Cvzym4K3ooqZx1JPTUfCa",
    "projectTitle": "Pomera AI Commander",
    "description": "A comprehensive text processing GUI and MCP server with 33+ tools for text transformation, encoding, extraction, and AI integration.",
    "folders": [
        "docs"
    ],
    "excludeFolders": [
        "core",
        "tools",
        "scripts",
        "build",
        "dist",
        "bin",
        "releases",
        "__pycache__",
        ".pytest_cache",
        "pomera_ai_commander.egg-info",
        ".git",
        ".github",
        ".cursor",
        ".vscode"
    ],
    "excludeFiles": [
        "pomera.py",
        "pomera_mcp_server.py",
        "test_azure_ai.py",
        "test_vertex_ai.py",
        "update_spec.py",
        "build.bat",
        "pomera.spec",
        "pomera-onedir.spec",
        "pomera-onefile.spec",
        "pomera-windows.spec",
        "mcp_filesystem.log",
        "requirements.txt",
        "pyproject.toml",
        "package.json",
        ".gitignore",
        "test_context7_mcp.js",
        "context7_results.txt"
    ],
    "rules": [
        "Pomera supports multi-tab editing where each tab has independent find/replace functionality - use Ctrl+T for new tab, Ctrl+F for per-tab find",
        "Real-time text statistics are displayed in the status bar showing characters, words, lines, paragraphs as you type - use pomera_text_stats MCP tool for detailed analysis",
        "Configure multiple AI providers (OpenAI, Vertex AI, Azure, Anthropic, Ollama) in settings.json under ai_providers - switch between them using AIProviderManager.switch_provider()",
        "Create custom text processing pipelines by chaining MCP tools: call pomera_whitespace then pomera_case_transform then pomera_sort in sequence",
        "Intelligent caching uses content hashing (ContentHashCache class) to cache operation results - same input+operation returns cached result instantly",
        "Run Pomera as an MCP server with: python pomera.py --mcp-server or pomera-mcp command",
        "All 33 MCP tools are prefixed with 'pomera_' (e.g., pomera_case_transform, pomera_extract_emails, pomera_notes_save)",
        "Configure MCP clients by adding Pomera to mcp.json: {\"mcpServers\": {\"pomera\": {\"command\": \"pomera-mcp\"}}}"
    ],
    "previousVersions": []
}