Unstructured Document Processor MCP
Supports processing JPEG/JPG files to extract content for large language models
Supports processing Org files to extract content for large language models
Supports processing SVG files to extract content for large language models
Supports processing XML files to extract content for large language models
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Unstructured Document Processor MCPextract the main points from this PDF report"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
A Model Context Protocol server that provides unstructured document processing capabilities. This server enables LLMs to extract and use content from an unstructured document.
This repo is work in progress, proceed with caution :)
Supported file types:
{".abw", ".bmp", ".csv", ".cwk", ".dbf", ".dif", ".doc", ".docm", ".docx", ".dot",
".dotm", ".eml", ".epub", ".et", ".eth", ".fods", ".gif", ".heic", ".htm", ".html",
".hwp", ".jpeg", ".jpg", ".md", ".mcw", ".mw", ".odt", ".org", ".p7s", ".pages",
".pbd", ".pdf", ".png", ".pot", ".potm", ".ppt", ".pptm", ".pptx", ".prn", ".rst",
".rtf", ".sdp", ".sgl", ".svg", ".sxg", ".tiff", ".txt", ".tsv", ".uof", ".uos1",
".uos2", ".web", ".webp", ".wk2", ".xls", ".xlsb", ".xlsm", ".xlsx", ".xlw", ".xml",
".zabw"}Prerequisites: You'll need:
Unstructured API key. Learn how to obtain one here
Claude Desktop installed locally
Quick TLDR on how to add this MCP to your Claude Desktop:
Clone the repo and set up the UV environment.
Create a
.envfile in the root directory and add the following env variable:UNSTRUCTURED_API_KEY.Run the MCP server:
uv run doc_processor.pyGo to
~/Library/Application Support/Claude/and create aclaude_desktop_config.json. In that file add:
{
"mcpServers": {
"unstructured_doc_processor": {
"command": "PATH/TO/YOUR/UV",
"args": [
"--directory",
"ABSOLUTE/PATH/TO/YOUR/unstructured-mcp/",
"run",
"doc_processor.py"
],
"disabled": false
}
}
}Restart Claude Desktop. You should now be able to use the MCP.
Available Tools
1 toolprocess_documentC
Sends document to process with Unstructured, return the content of the document
Args:
filepath: path to the document
| Name | Required | Description | Default |
|---|---|---|---|
| filepath | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions processing and returning content but lacks details on permissions, rate limits, error handling, or what 'process with Unstructured' entails (e.g., parsing, extraction). For a tool with no annotations, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: a clear purpose statement followed by a parameter explanation. It avoids unnecessary words and is front-loaded with the main functionality. The only minor inefficiency is the lack of formatting in the Args section, but overall it's efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and low schema coverage, the description is incomplete. It explains the basic operation and parameter but misses critical details like return format, error conditions, or what 'Unstructured' processing involves. For a tool that processes documents, more context is needed to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes an Args section explaining 'filepath: path to the document', which adds meaning beyond the schema's bare title 'Filepath'. However, with 0% schema description coverage and only one parameter, this provides basic but incomplete context (e.g., no format examples or constraints). It meets the baseline for minimal parameter explanation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Sends document to process with Unstructured, return the content of the document'. It specifies the verb ('process'), resource ('document'), and technology ('Unstructured'), though it doesn't differentiate from siblings since none exist. The purpose is specific and actionable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, prerequisites, or typical use cases. It simply states what the tool does without context about when it's appropriate. Since there are no sibling tools, this is less critical but still a gap in usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
With only one tool, there is no possibility of ambiguity or confusion between tools. The single tool has a clear, distinct purpose of processing documents with Unstructured.
The single tool name 'process_document' follows a clear verb_noun pattern. Since there is only one tool, consistency is inherently perfect with no deviations to evaluate.
A single tool is too few for a server named 'Unstructured Document Processor MCP', which suggests broader document processing capabilities. This minimal set feels thin and under-scoped for the apparent domain.
The tool surface is severely incomplete for document processing. It only provides a basic processing function, lacking essential operations like document listing, metadata retrieval, format conversion, or batch processing, which are typical in such domains.
Maintenance
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