Algodocs API

Name: Algodocs API API
Brand: Algodocs API
Availability: InStock

★ Only Publicly Available SpecData EnrichmentData TransformationapiKey10 EndpointsREST

For Agents

Upload PDFs and images to Algodocs, route them to an extractor, and retrieve structured JSON data for invoices, receipts, and other documents.

Quickstart

Get started with Algodocs API in minutes using your preferred integration method.

# Add to your MCP client config (Claude Desktop, Cursor, Windsurf)
{
  "jentic": {
    "url": "https://api.jentic.com/mcp",
    "auth": "oauth"
  }
}

# Then ask your agent:
"extract data from a document"

# → Jentic returns the GET /events tool with parameter schema, agent executes.

Capabilities

What an agent can do with Algodocs API API.

List the configured extractors in an Algodocs account with /extractors

Upload a document file via multipart with /documents/upload or as base64 with /documents/upload-base64

Inspect documents and their processing status with /documents and /documents/{id}

Retrieve extracted data for a single document via /documents/{id}/extracted-data

GET STARTED

Start building with Algodocs API API

Explore with Jentic

View OpenAPI Spec

Use for: I need to upload an invoice PDF for data extraction, Get the structured JSON data extracted from a document, List every extractor configured in my Algodocs account, Pull all extracted data for an extractor for a nightly export

Not supported: Does not handle document signing, e-signature workflows, or generic file storage — use for routing documents to configured extractors and retrieving structured JSON only.

Jentic publishes the only available OpenAPI specification for Algodocs API, keeping it validated and agent-ready.

Jentic publishes the only available OpenAPI specification for Algodocs API, keeping it validated and agent-ready. Algodocs is an intelligent document data extraction service for invoices, receipts, and other structured documents. The REST API lets users upload documents (file or base64), route them to a configured extractor, list and inspect documents, organise them into folders, and retrieve the extracted JSON for downstream automation. Authentication uses an API key in the Authorization header.

Use Cases

Patterns agents use Algodocs API API for, with concrete tasks.

★ Invoice ingestion into accounting

An AP automation flow uploads supplier invoice PDFs to Algodocs by POSTing to /documents/upload with the chosen extractor id, polls /documents/{id} for completion, then pulls the structured JSON via /documents/{id}/extracted-data and writes line items into the accounting system. The integration replaces manual data entry with a controlled, auditable pipeline.

POST /documents/upload with the invoice file and extractor id, poll GET /documents/{id} for status, then GET /documents/{id}/extracted-data and post line items to the accounting system

Receipt capture from a mobile app

A receipt capture mobile app sends base64-encoded images to /documents/upload-base64 alongside the receipt extractor id. Algodocs returns a document id, and the app polls /documents/{id}/extracted-data once processing completes, displaying the parsed merchant, total, and date back to the user.

POST /documents/upload-base64 with the encoded image and extractor id, then GET /documents/{id}/extracted-data once status reports completion

Bulk extracted-data export to a warehouse

A data team exports all extracted data for a given extractor into a warehouse table once a day by calling /extractors/{extractorId}/extracted-data. Because the endpoint already returns structured JSON, the team avoids per-document polling for historical loads.

GET /extractors/{extractorId}/extracted-data with the date range and append the rows to the warehouse table

Agent-driven document parsing through Jentic

A Jentic agent receives an intent like 'extract data from this invoice' along with a file, uploads it to Algodocs, and returns the parsed JSON to the user. The agent never needs to handle the Authorization header — Jentic manages the credential and resolves the right extractor id from the user's account.

Search Jentic for 'extract data from a document', execute POST /documents/upload with the chosen extractor id, then chain GET /documents/{id}/extracted-data to return the structured JSON

Key Endpoints

10 endpoints — jentic publishes the only available openapi specification for algodocs api, keeping it validated and agent-ready.

METHOD

PATH

DESCRIPTION

GET

/extractors

List all extractors

POST

/documents/upload

Upload a document for extraction

POST

/documents/upload-base64

Upload a base64-encoded document

GET

/documents/{id}

Retrieve a document and its status

GET

/documents/{id}/extracted-data

Retrieve extracted data for a document

GET

/extractors/{extractorId}/extracted-data

Retrieve all extracted data for an extractor

GET

/extractors

List all extractors

POST

/documents/upload

Upload a document for extraction

POST

/documents/upload-base64

Upload a base64-encoded document

GET

/documents/{id}

Retrieve a document and its status

GET

/documents/{id}/extracted-data

Retrieve extracted data for a document

Why though Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

The Algodocs Authorization key is stored encrypted in the Jentic credential vault and injected at call time. The agent never sees the raw key in its prompt or response.

Intent-based discovery

Agents search Jentic by intent (e.g. 'upload an invoice for extraction'), and Jentic returns the matching Algodocs operation with its input schema, including the extractor id parameter.

Time to first call

Direct Algodocs integration: 1-2 days for upload handling, polling, and extracted-data parsing. Through Jentic: under an hour with search, load, and execute.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Alternative

Hugging Face Inference API

Use Hugging Face hosted document understanding models when a fully managed extractor service is not required

Choose Hugging Face for custom model inference; choose Algodocs for a managed extractor with prebuilt invoice and receipt templates

Alternative

OpenAI API

Use OpenAI vision-capable models for ad-hoc document parsing without configuring extractors

Choose OpenAI for one-off parsing where structure is loose; choose Algodocs when consistent fields per document type matter

Complementary

Airtable API

Pair with Algodocs to land extracted invoice rows into an Airtable base for review

Use Airtable alongside Algodocs when the downstream review workflow lives in an Airtable base

FAQs

Specific to using Algodocs API API through Jentic.

Why is there no official OpenAPI spec for Algodocs API?

Algodocs does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call Algodocs API via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.

What authentication does the Algodocs API use?

Algodocs uses an API key sent in the Authorization request header. Jentic stores the key encrypted in its credential vault and injects the header at execution time so the raw key never enters the agent's prompt or response context.

Can I upload an invoice PDF for extraction with the Algodocs API?

Yes. POST /documents/upload as multipart with the file and the extractor id. Algodocs returns a document id you can poll with GET /documents/{id}; once processing completes, GET /documents/{id}/extracted-data returns the structured JSON.

What are the rate limits for the Algodocs API?

The OpenAPI spec does not declare rate limits. Algodocs enforces plan-based limits server-side, so throttle high-volume document uploads and consider the bulk extracted-data endpoint instead of per-document polling for backfills.

How do I extract data from a document through Jentic?

Search Jentic for 'extract data from a document', load the schema for POST /documents/upload, and execute it with the file and extractor id. Jentic chains the call to GET /documents/{id}/extracted-data once the document completes processing.

Can I send a base64-encoded document instead of a file upload?

Yes. POST /documents/upload-base64 with the encoded payload and the extractor id. This is useful for mobile clients that already hold the file bytes in memory and prefer not to write to disk.