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Docling is an IBM-backed open-source toolkit that converts PDF, DOCX, PPTX, XLSX, HTML, images, audio, and LaTeX files into structured formats for gen AI workflows. It features advanced PDF layout understanding, OCR, table extraction, and integrations with LangChain, LlamaIndex, and CrewAI.
--- name: docling-ai-document-intelligence-pipeline-75808db32977 slug: "docling-ai-document-intelligence-pipeline" description: "Docling is an IBM-backed open-source toolkit that converts PDF, DOCX, PPTX, XLSX, HTML, images, audio, and LaTeX files into structured formats for gen AI workflows. It features advanced PDF layout understanding, OCR, table extraction, and integrations with LangChain, LlamaIndex, and CrewAI." github_stars: 56871 verification: "security_reviewed" source: "https://github.com/docling-project/docling" category: "Data Extraction & Transformation" framework: "Claude Code" tool_ecosystem: github_repo: "docling-project/docling" github_stars: 56871 --- # Docling AI Document Intelligence Pipeline Docling is an IBM-backed open-source toolkit that converts PDF, DOCX, PPTX, XLSX, HTML, images, audio, and LaTeX files into structured formats for gen AI workflows. It features advanced PDF layout understanding, OCR, table extraction, and integrations with LangChain, LlamaIndex, and CrewAI. ## Installation Use the upstream install or setup path that matches your environment: - pip install docling Requirements and caveats from upstream: - [](https://pypi.org/project/docling/) - **Note:** Python 3.9 support was dropped in docling version 2.70.0. Please use Python 3.10 or higher. - ## 3. Python usage (recommended) Basic usage or getting-started notes: - 🔌 Connect to any agent using the [MCP server](https://docling-project.github.io/docling/usage/mcp/) - 🔌 [MCP server](https://docling-project.github.io/docling/usage/mcp/) for agentic applications - ### 1. Install - Source: https://github.com/docling-project/docling - Extracted from upstream docs: https://raw.githubusercontent.com/docling-project/docling/HEAD/README.md ## Source - [Agent Skill Exchange](https://agentskillexchange.com/skills/docling-ai-document-intelligence-pipeline/)--- name: docling-ai-document-intelligence-pipeline-75808db32977 slug: "docling-ai-document-intelligence-pipeline" description: "Docling is an IBM-backed open-source toolkit that converts PDF, DOCX, PPTX, XLSX, HTML, images, audio, and LaTeX files into structured formats for gen AI workflows. It features advanced PDF layout understanding, OCR, table extraction, and integrations with LangChain, LlamaIndex, and CrewAI." github_stars: 56871 verification: "security_reviewed" source: "https://github.com/docling-project/docling" category: "Data Extraction & Transformation" framework: "Claude Code" tool_ecosystem: github_repo: "docling-project/docling" github_stars: 56871 --- # Docling AI Document Intelligence Pipeline Docling is an IBM-backed open-source toolkit that converts PDF, DOCX, PPTX, XLSX, HTML, images, audio, and LaTeX files into structured formats for gen AI workflows. It features advanced PDF layout understanding, OCR, table extraction, and integrations with LangChain, LlamaIndex, and CrewAI. ## Installation Use the upstream install or setup path that matches your environment: - pip install docling Requirements and caveats from upstream: - [](https://pypi.org/project/docling/) - **Note:** Python 3.9 support was dropped in docling version 2.70.0. Please use Python 3.10 or higher. - ## 3. Python usage (recommended) Basic usage or getting-started notes: - 🔌 Connect to any agent using the [MCP server](https://docling-project.github.io/docling/usage/mcp/) - 🔌 [MCP server](https://docling-project.github.io/docling/usage/mcp/) for agentic applications - ### 1. Install - Source: https://github.com/docling-project/docling - Extracted from upstream docs: https://raw.githubusercontent.com/docling-project/docling/HEAD/README.md ## Source - [Agent Skill Exchange](https://agentskillexchange.com/skills/docling-ai-document-intelligence-pipeline/)
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.