> ## Documentation Index > Fetch the complete documentation index at: https://docs.unsiloed.ai/docs/llms.txt > Use this file to discover all available pages before exploring further. # Documentation for Coding Agents > Machine-readable documentation entry points for agents integrating the Unsiloed document-processing APIs. Coding agents can read the Unsiloed documentation without rendering the website. Start with the focused documentation index, then open only the raw Markdown pages needed for the task. ## Start With the Focused Documentation Index Use [`llms.txt`](https://www.unsiloed.ai/docs/llms.txt) to discover documentation pages and their raw Markdown URLs. The index is approximately 10 KB, so it provides a lower-context starting point than loading the complete documentation corpus. Use [`llms-full.txt`](https://www.unsiloed.ai/docs/llms-full.txt) only when the task requires searching across the entire documentation set. Every documentation page is also available as raw Markdown. For example: | Documentation resource | Machine-readable URL | | - | - | | Introduction | [`/docs/index.md`](https://www.unsiloed.ai/docs/index.md) | | Parsing quickstart | [`/docs/quickstart.md`](https://www.unsiloed.ai/docs/quickstart.md) | | Parse overview | [`/docs/document-processing/parsing/parsing.md`](https://www.unsiloed.ai/docs/document-processing/parsing/parsing.md) | | Extract overview | [`/docs/document-processing/extraction/extraction.md`](https://www.unsiloed.ai/docs/document-processing/extraction/extraction.md) | | Classification overview | [`/docs/document-processing/classification/classification.md`](https://www.unsiloed.ai/docs/document-processing/classification/classification.md) | | Splitting overview | [`/docs/document-processing/splitting/splitting.md`](https://www.unsiloed.ai/docs/document-processing/splitting/splitting.md) | ## Choose the Document Operation Unsiloed separates document processing into four operations. Choose the operation from the result your application needs: | Goal | Start here | | - | - | | Convert the complete document into ordered Markdown chunks with layout metadata | [Parse overview](https://www.unsiloed.ai/docs/document-processing/parsing/parsing.md) | | Pull named fields into a JSON schema with confidence scores and citations | [Extract overview](https://www.unsiloed.ai/docs/document-processing/extraction/extraction.md) | | Assign a document to one of your predefined categories | [Classification overview](https://www.unsiloed.ai/docs/document-processing/classification/classification.md) | | Separate a bundled PDF into documents by category | [Splitting overview](https://www.unsiloed.ai/docs/document-processing/splitting/splitting.md) | For a first parsing integration, follow the [parsing quickstart](https://www.unsiloed.ai/docs/quickstart.md). It provides Python, JavaScript, and cURL examples for submitting a document, polling the job, and reading the result. The Python and JavaScript examples save both JSON and Markdown output. ## Use the API Endpoints Send authenticated requests to `https://prod.visionapi.unsiloed.ai` with your API key in the `api-key` header. Use these routes for new integrations: | Operation | Submit | Retrieve the result | Reference | | - | - | - | - | | Parse | `POST /parse` | [`GET /parse/{job_id}`](https://www.unsiloed.ai/docs/api-reference/parser/get-parse-job-status.md) | [Parse API](https://www.unsiloed.ai/docs/api-reference/parser/parse-document.md) | | Parse a large file | `POST /v2/parse/upload`, then `PUT` to the returned URL | [`GET /parse/{job_id}`](https://www.unsiloed.ai/docs/api-reference/parser/get-parse-job-status.md) | [Large-file upload API](https://www.unsiloed.ai/docs/api-reference/parser/parse-document-v2.md) | | Parse Excel | `POST /parse/excel` | [`GET /parse/{job_id}`](https://www.unsiloed.ai/docs/api-reference/parser/get-parse-job-status.md) | [Excel API](https://www.unsiloed.ai/docs/api-reference/parser/parse-excel.md) | | Extract | `POST /v2/extract` | [`GET /extract/{job_id}`](https://www.unsiloed.ai/docs/api-reference/jobs/results.md) | [Extract API](https://www.unsiloed.ai/docs/api-reference/extraction/extract-data.md) | | Classify | `POST /classify` | [`GET /classify/{job_id}`](https://www.unsiloed.ai/docs/api-reference/classification/get-classification-status.md) | [Classification API](https://www.unsiloed.ai/docs/api-reference/classification/classify-document.md) | | Split | `POST /splitter` | [`GET /splitter/{job_id}`](https://www.unsiloed.ai/docs/api-reference/splitting/get-split-status.md) | [Splitting API](https://www.unsiloed.ai/docs/api-reference/splitting/split-document.md) | Accepted jobs return a `job_id` for polling. Parse jobs finish with `Succeeded`, `Failed`, or `Cancelled`. Extraction results are available when the status is `completed` or `review`, and extraction can end with `failed`. Classification and splitting jobs finish with `completed` or `failed`. Use `POST /parse` for standard parsing unless the file needs the large-file upload flow or is an Excel workbook. For the large-file upload, send the file to `upload_url` with the returned `upload_headers`; the presigned `PUT` does not use the `api-key` header. Poll the resulting job through `GET /parse/{job_id}`. When extraction has personally identifiable information (PII) detection enabled, it can instead return `status: "pii_blocked"` with no job. Check the submit response before polling. ## Treat OpenAPI as Supplementary Reference Use the human-readable guides and API references linked above as the source of truth for current integrations. The aggregate OpenAPI specification still uses older Parse field names and requires a file upload, so it does not fully describe URL-only Parse requests. Verify generated clients against the relevant endpoint reference before using them: * [Aggregate API specification](https://www.unsiloed.ai/docs/api-reference/openapi.json) ## Distinguish Documentation Access From Product Tools The [Unsiloed Document Processing MCP server](https://www.unsiloed.ai/docs/integrations/mcp-server.md) gives an agent tools for parsing, classification, and structured extraction. It processes documents and does not search the documentation. For documentation research, use `llms.txt` and raw Markdown pages. For document-processing actions, use the MCP server or REST API. This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.