{"id":28722324,"url":"https://github.com/docling-project/docling-mcp","last_synced_at":"2025-06-15T08:08:58.976Z","repository":{"id":283491514,"uuid":"948391943","full_name":"docling-project/docling-mcp","owner":"docling-project","description":"Making docling agentic through MCP","archived":false,"fork":false,"pushed_at":"2025-05-21T13:59:22.000Z","size":543,"stargazers_count":79,"open_issues_count":11,"forks_count":18,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-05-21T14:56:02.835Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/docling-project.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":".github/SECURITY.md","support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-03-14T08:58:54.000Z","updated_at":"2025-05-21T14:02:10.000Z","dependencies_parsed_at":"2025-03-20T14:43:45.205Z","dependency_job_id":"381edede-19a2-49b6-85e4-2f6320e76a7f","html_url":"https://github.com/docling-project/docling-mcp","commit_stats":null,"previous_names":["docling-project/docling-mcp"],"tags_count":3,"template":false,"template_full_name":null,"purl":"pkg:github/docling-project/docling-mcp","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/docling-project%2Fdocling-mcp","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/docling-project%2Fdocling-mcp/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/docling-project%2Fdocling-mcp/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/docling-project%2Fdocling-mcp/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/docling-project","download_url":"https://codeload.github.com/docling-project/docling-mcp/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/docling-project%2Fdocling-mcp/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":259942797,"owners_count":22935330,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-06-15T08:08:57.878Z","updated_at":"2025-06-15T08:08:58.961Z","avatar_url":"https://github.com/docling-project.png","language":"Python","funding_links":[],"categories":["Python","📚 Projects (1974 total)","Search and Documentation"],"sub_categories":["MCP Servers"],"readme":"# Docling MCP: making docling agentic \n\n[![PyPI version](https://img.shields.io/pypi/v/docling-mcp)](https://pypi.org/project/docling-mcp/)\n[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/docling-mcp)](https://pypi.org/project/docling-mcp/)\n[![uv](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/uv/main/assets/badge/v0.json)](https://github.com/astral-sh/uv)\n[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)\n[![Pydantic v2](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/pydantic/pydantic/main/docs/badge/v2.json)](https://pydantic.dev)\n[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit\u0026logoColor=white)](https://github.com/pre-commit/pre-commit)\n[![License MIT](https://img.shields.io/github/license/docling-project/docling-mcp)](https://opensource.org/licenses/MIT)\n[![PyPI Downloads](https://static.pepy.tech/badge/docling-mcp/month)](https://pepy.tech/projects/docling-mcp)\n[![LF AI \u0026 Data](https://img.shields.io/badge/LF%20AI%20%26%20Data-003778?logo=linuxfoundation\u0026logoColor=fff\u0026color=0094ff\u0026labelColor=003778)](https://lfaidata.foundation/projects/)\n\nA document processing service using the Docling-MCP library and MCP (Message Control Protocol) for tool integration.\n\n \u003e [!NOTE]\n\u003e This is an unstable draft implementation which will quickly evolve.\n\n## Overview\n\nDocling MCP is a service that provides tools for document conversion, processing and generation. It uses the Docling library to convert PDF documents into structured formats and provides a caching mechanism to improve performance. The service exposes functionality through a set of tools that can be called by client applications.\n\n## Features\n\n- conversion tools:\n    - PDF document conversion to structured JSON format (DoclingDocument)\n- generation tools:\n    - Document generation in DoclingDocument, which can be exported to multiple formats\n- Local document caching for improved performance\n- Support for local files and URLs as document sources\n- Memory management for handling large documents\n- Logging system for debugging and monitoring\n- Milvus upload and retrieval\n\n## Getting started\n\nInstall dependencies\n\n```sh\nuv sync\n```\n\nInstall the docling_mcp package\n\n```sh\nuv pip install -e .\n```\n\nAfter installing the dependencies (`uv sync`), you can expose the tools of Docling by running\n\n```sh\nuv run docling-mcp-server\n```\n\n## Integration with Claude for Desktop\n\nOne of the easiest ways to experiment with the tools provided by Docling-MCP is to leverage [Claude for Desktop](https://claude.ai/download).\nOnce installed, extend Claude for Desktop so that it can read from your computer’s file system, by following the [For Claude Desktop Users](https://modelcontextprotocol.io/quickstart/user) tutorial.\n\nTo enable Claude for Desktop with Docling MCP, simply edit the config file `claude_desktop_config.json` (located at `~/Library/Application Support/Claude/claude_desktop_config.json` in MacOS) and add a new item in the `mcpServers` key with the details of a Docling MCP server. You can find an example of those details [here](docs/integrations/claude_desktop_config.json).\n\n\n## Converting documents\n\nExample of prompt for converting PDF documents:\n\n```prompt\nConvert the PDF document at \u003cprovide file-path\u003e into DoclingDocument and return its document-key.\n```\n\n## Generating documents\n\nExample of prompt for generating new documents:\n\n```prompt\nI want you to write a Docling document. To do this, you will create a document first by invoking `create_new_docling_document`. Next you can add a title (by invoking `add_title_to_docling_document`) and then iteratively add new section-headings and paragraphs. If you want to insert lists (or nested lists), you will first open a list (by invoking `open_list_in_docling_document`), next add the list_items (by invoking `add_listitem_to_list_in_docling_document`). After adding list-items, you must close the list (by invoking `close_list_in_docling_document`). Nested lists can be created in the same way, by opening and closing additional lists.\n\nDuring the writing process, you can check what has been written already by calling the `export_docling_document_to_markdown` tool, which will return the currently written document. At the end of the writing, you must save the document and return me the filepath of the saved document.\n\nThe document should investigate the impact of tokenizers on the quality of LLM's.\n```\n\n## Applications\n\n### Milvus RAG configuration\n\nCopy the .env.example file to .env in the root of the project.\n\n```sh\ncp .env.example .env\n```\n\nIf you want to use the RAG Milvus functionality edit the new .env file to set both environment variables.\n\n```text\nRAG_ENABLED=true\nOLLAMA_MODEL=granite3.2:latest\nEMBEDDING_MODEL=BAAI/bge-small-en-v1.5\n```\n\nNote:\n\nollama can be downloaded here https://ollama.com/. Once you have ollama download the model you want to use and then add the model string to the .env file.\n\nFor example we are using `granite3.2:latest` to perform the RAG search.\n\nTo download this model run:\n\n```sh\nollama pull granite3.2:latest\n```\n\nWhen using the docling-mcp server with RAG this would be a simple example prompt:\n\n```prompt\nProcess this file /Users/name/example/mock.pdf \n\nUpload it to the vector store. \n\nThen summarize xyz that is contained within the document.\n```\n\nKnown issues\n\nWhen restarting the MCP client (e.g. Claude desktop) the client sometimes errors due to the `.milvus_demo.db.lock` file. Delete this before restarting.\n\n\n## License\n\nThe Docling-MCP codebase is under MIT license. For individual model usage, please refer to the model licenses found in the original packages.\n\n## LF AI \u0026 Data\n\nDocling and Docling-MCP is hosted as a project in the [LF AI \u0026 Data Foundation](https://lfaidata.foundation/projects/).\n\n**IBM ❤️ Open Source AI**: The project was started by the AI for knowledge team at IBM Research Zurich.\n\n[docling_document]: https://docling-project.github.io/docling/concepts/docling_document/\n[integrations]: https://docling-project.github.io/docling-mcp/integrations/","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdocling-project%2Fdocling-mcp","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdocling-project%2Fdocling-mcp","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdocling-project%2Fdocling-mcp/lists"}