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Health: ActiveRecent health check succeeded.Last checked 9/7/2026, 7:39:34 PM

Docling MCP

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time β€” check back soon.
View Repository733 GitHub StarsTotal stargazers on GitHub for the source repository (733 stars).Visit Website

Convert PDFs and other documents to structured formats via Docling, for AI applications.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "docling-mcp": {
      "command": "uvx",
      "args": [
        "--from"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing AlternativesπŸ’» More in Developer Tools

Documentation Overview

Docling

Docling MCP: making docling agentic

CI PyPI version PyPI - Python Version uv Ruff Pydantic v2 pre-commit License MIT PyPI Downloads LF AI & Data MCP Registry docling-mcp MCP server MCP Toplist

A document processing service using the Docling-MCP library and MCP (Model Context Protocol) for tool integration.

Overview

Docling 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.

Compatibility

docling-mcpMCP Python SDK
>=3.0.0mcp>=2.0.0
>=2.0.0,<3.0.0mcp>=1.9.4,<2.0.0

If your MCP client application has not yet migrated to MCP SDK v2, pin:

Terminal
pip install "docling-mcp<3.0.0"

See MIGRATION.md for the full migration guide.

Installation Options

Remote Mode (Recommended - Lightweight)

For users with access to Docling Serve API:

Getting Docling Serve: Visit docling-serve for installation guides. You can deploy it from published container images or look for managed Docling SaaS offerings.

Terminal
pip install docling-mcp

Then configure your environment:

server.ts
export DOCLING_MCP_SERVICE_URL=https://your-docling-service.example.com
export DOCLING_MCP_SERVICE_API_KEY=your-api-key-here
export DOCLING_MCP_CONVERSION_MODE=remote

Local Mode (Full Features)

For users who need local conversion or don't have Docling Serve access:

Terminal
pip install docling-mcp[local]

Then configure your environment:

server.ts
export DOCLING_MCP_CONVERSION_MODE=local

Hybrid Mode (Best of Both)

Install with local support and enable automatic fallback:

Terminal
pip install docling-mcp[local]

Configure for remote with fallback:

server.ts
export DOCLING_MCP_SERVICE_URL=https://your-docling-service.example.com
export DOCLING_MCP_CONVERSION_MODE=remote
export DOCLING_MCP_FALLBACK_TO_LOCAL=true

Features

  • Conversion tools:
    • PDF document conversion to structured JSON format ([DoclingDocument][docling_document])
  • Generation tools:
    • Document generation in DoclingDocument, which can be exported to multiple formats
  • Local document caching for improved performance
  • Support for local files and URLs as document sources
  • Memory management for handling large documents
  • Logging system for debugging and monitoring
  • RAG applications with Milvus upload and retrieval

Configuration

All settings use the DOCLING_MCP_ prefix and can be supplied as environment variables, in a .env file in the working directory, or via the env block of your MCP client config. Copy .env.example as a starting point.

Conversion mode

VariableDefaultDescription
DOCLING_MCP_CONVERSION_MODEremoteremote or local

Remote service (required when DOCLING_MCP_CONVERSION_MODE=remote)

VariableDefaultDescription
DOCLING_MCP_SERVICE_URLβ€”URL of the Docling Serve instance
DOCLING_MCP_SERVICE_API_KEYβ€”API key for the service
DOCLING_MCP_SERVICE_TIMEOUT300.0Timeout in seconds for a whole conversion job
DOCLING_MCP_SERVICE_MAX_RETRIES3Max retry attempts
DOCLING_MCP_FALLBACK_TO_LOCALfalseFall back to local if service is unreachable (requires docling-mcp[local])

Conversion pipeline (applies to both modes)

VariableDefaultDescription
DOCLING_MCP_KEEP_IMAGESfalseRetain page images in output
DOCLING_MCP_IMAGES_SCALE1.0Image scale factor (increase to avoid tensor padding errors)
DOCLING_MCP_DO_OCRtrueRun OCR pipeline
DOCLING_MCP_DO_TABLE_STRUCTUREtrueDetect table structure

Markdown export

VariableDefaultDescription
DOCLING_MCP_IMAGE_EXPORT_MODEplaceholderHow images are rendered in Markdown output: placeholder (emits <!-- image -->), embedded (base64 data-URI), referenced (file path / URL)

LlamaIndex RAG (--tools llama-index-rag)

VariableDefaultDescription
DOCLING_MCP_LI_API_BASEhttp://127.0.0.1:1234/v1OpenAI-compatible LLM endpoint
DOCLING_MCP_LI_API_KEYnoneAPI key for the LLM endpoint
DOCLING_MCP_LI_MODEL_IDibm/granite-3.2-8bLLM model identifier
DOCLING_MCP_LI_EMBEDDING_MODELBAAI/bge-base-en-v1.5HuggingFace embedding model

LlamaStack (--tools llama-stack-rag / --tools llama-stack-ie)

VariableDefaultDescription
DOCLING_MCP_LLS_URLhttp://localhost:8321LlamaStack server URL
DOCLING_MCP_LLS_VDB_EMBEDDINGall-MiniLM-L6-v2Embedding model for vector DB
DOCLING_MCP_LLS_EXTRACTION_MODELopenai/gpt-oss-20bModel used for structured extraction

Setting variables in an MCP client config

config.json
{
  "mcpServers": {
    "docling": {
      "command": "uvx",
      "args": [
        "--from=docling-mcp",
        "docling-mcp-server"
      ],
      "env": {
        "DOCLING_MCP_CONVERSION_MODE": "remote",
        "DOCLING_MCP_SERVICE_URL": "https://your-docling-service.example.com",
        "DOCLING_MCP_SERVICE_API_KEY": "your-api-key-here"
      }
    }
  }
}

Getting started

The easiest way to install Docling MCP and connect it to your client is by launching it via uvx.

Depending on the transfer protocol required, specify the argument --transport, for example

  • stdio used e.g. in Claude for Desktop and LM Studio

    sh
    uvx --from docling-mcp docling-mcp-server --transport stdio
    
  • sse used e.g. in Llama Stack

    sh
    uvx --from docling-mcp docling-mcp-server --transport sse
    
  • streamable-http used e.g. in containers setup

    sh
    uvx --from docling-mcp docling-mcp-server --transport streamable-http
    

More options are available, e.g. the selection of which toolgroup to launch. Use the --help argument to inspect all the CLI options.

For developing the MCP tools further, please refer to the Developing section of CONTRIBUTING.md for instructions.

Integration with MCP clients

One of the easiest ways to experiment with the tools provided by Docling MCP is to leverage an AI desktop client with MCP support. Most of these clients use a common config interface. Adding Docling MCP in your favorite client is usually as simple as adding the following entry in the configuration file.

config.json
{
  "mcpServers": {
    "docling": {
      "command": "uvx",
      "args": [
        "--from=docling-mcp",
        "docling-mcp-server"
      ]
    }
  }
} 

When using Claude for Desktop, simply edit the config file claude_desktop_config.json with the snippet above or the example provided here.

In LM Studio, edit the mcp.json file with the appropriate section or simply click on the button below for a direct install.

Add MCP Server docling to LM Studio

Other integrations are described in the [integrations] page.

Examples

Converting documents

Example of prompt for converting PDF documents:

prompt
Convert the PDF document at <provide file-path> into DoclingDocument and return its document-key.

Generating documents

Example of prompt for generating new documents:

Read the full README β†’View source on GitHub β†’

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Reviews

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Frequently Asked Questions about Docling MCP

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "docling-mcp": { "command": "npx", "args": ["-y", "Docling MCP"] } }

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Technical Specs & Signals

CategoryπŸ’»Developer Tools
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimePython
Last updatedSep 7, 2026
Views0
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars733
GitHub Star CountTotal stargazers on GitHub representing community popularity (733 stars).
43Quality signal: Fair Β· 43/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools16/30
Adoption & activity6/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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