Install Jentic One Beta

Connect the PerfectParser Public API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the PerfectParser Public API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.

Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.

Step 1: Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fperfectparser.com%2Fperfectparser" | sh

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fperfectparser.com%2Fperfectparser" | sh
jentic register       # connects your agent to your Jentic One instance

Jentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.

Capabilities

What an agent can do with PerfectParser Public API.

Create a parser with a name, result_mode of one_per_file or one_per_page, and schema fields for the data to extract

Auto-detect a parser's schema fields from a sample_file_id with an optional prompt, replacing or extending the existing schema

Submit one or more files to a parser_id as a bulk extraction and list extractions by parser_id, status, or since date

Read structured results for a whole extraction or for one document within it

GET STARTED

Start building with PerfectParser Public API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use PerfectParser Public API for, with concrete tasks.

★ Agent document extraction through Jentic

An agent handling incoming invoices or forms finds the PerfectParser extraction operations through Jentic, submits the files to an existing parser_id, polls the extraction status, and reads the structured results back into its workflow. Jentic injects the X-API-Key header at call time, so the agent works with extracted fields and never sees the pp_live_ key.

POST /v1/extractions with parser_id for the invoice parser and the two uploaded PDF files, poll GET /v1/extractions/{extraction_id} until status is completed, then GET /v1/extractions/{extraction_id}/results

Build a parser from a sample document

Instead of defining every field by hand, create a parser with POST /v1/parsers and a name, then call POST /v1/parsers/{id}/detect-fields with a sample_file_id and an optional prompt such as 'extract PO number, supplier, and line items'. Set replace_existing_schema to choose whether detected fields replace or add to the current schema, and refine the result with PATCH /v1/parsers/{id}.

POST /v1/parsers with name 'Purchase Order Parser' and result_mode 'one_per_file', then POST /v1/parsers/{id}/detect-fields with sample_file_id from a sample upload and prompt 'extract PO number, supplier, and line items'

Bulk results to spreadsheets

Finance and operations teams export extraction batches for review. GET /v1/extractions/{extraction_id}/export with format csv or xlsx returns the whole batch, and the per-document export returns a single file's results. GET /v1/extractions filtered by status such as failed or partial finds batches that need attention.

List GET /v1/extractions with parser_id for invoices and since '2026-11-01T00:00:00Z', then call GET /v1/extractions/{extraction_id}/export with format 'xlsx' for each completed batch

Push results with webhooks

POST /v1/webhooks registers a callback URL for extraction.document_completed and extraction.job_completed events, with an optional secret that PerfectParser sends in the X-Webhook-Secret header. POST /v1/webhooks/{id}/test sends a test delivery, and PATCH can pause a subscription with is_active.

POST /v1/webhooks with url 'https://example.com/hooks/parsed', events extraction.document_completed and extraction.job_completed, and a secret, then POST /v1/webhooks/{id}/test

Key Endpoints

21 endpoints — the perfectparser public api extracts structured data from documents using parsers you define: each parser has a name, a result mode of one object per file or per page, and a list of schema fields, which it can also detect automatically from a sample file and an optional prompt.

METHOD

PATH

DESCRIPTION

POST

/v1/parsers

Create a parser

POST

/v1/parsers/{id}/detect-fields

Auto-detect schema fields

POST

/v1/extractions

Submit documents for extraction

GET

/v1/extractions/{extraction_id}

Get extraction status

GET

/v1/extractions/{extraction_id}/results

Get extraction results

GET

/v1/extractions/{extraction_id}/export

Export batch results

POST

/v1/webhooks

Create a webhook subscription

POST

/v1/parsers

Create a parser

POST

/v1/parsers/{id}/detect-fields

Auto-detect schema fields

POST

/v1/extractions

Submit documents for extraction

GET

/v1/extractions/{extraction_id}

Get extraction status

GET

/v1/extractions/{extraction_id}/results

Get extraction results

GET

/v1/extractions/{extraction_id}/export

Export batch results

POST

/v1/webhooks

Create a webhook subscription

Why Jentic?

What agents get from Jentic-routed access to this vendor.

Setup

Wiring PerfectParser by hand means sending the X-API-Key header, uploading files as multipart form data, polling extraction status, and following cursor pagination yourself. Through Jentic you install once, import PerfectParser from the API Directory, store the key once, and your agent calls it.

Permission scoping

PerfectParser puts the parser id and extraction id in the URL path (/v1/parsers/{id} and /v1/extractions/{extraction_id}/...), so a rule can pin your agent to one parser's configuration or one extraction's results. You choose the operations it may call, so destructive ones like deleting a parser or a webhook subscription are not included unless you add them.

Credential isolation

Your PerfectParser API key is stored once, encrypted, by your own Jentic One instance and injected at execution time. It never enters the agent's prompt, logs, or context.

Intent-based discovery

Agents search Jentic by intent such as 'extract data from documents' or 'export extraction results', and Jentic returns the matching PerfectParser operation with its input schema so the agent calls the right endpoint without browsing the reference docs.

FAQs

Specific to using PerfectParser Public API through Jentic.

What authentication does the PerfectParser Public API use?

Per its OpenAPI spec, the PerfectParser Public API takes an API access key in the `X-API-Key` header, for example a key beginning `pp_live_`. Through Jentic the key is stored encrypted by your own Jentic One instance and injected at call time, so it never enters the agent's context.

Can PerfectParser work out which fields to extract by itself?

Yes. POST /v1/parsers/{id}/detect-fields takes a required sample_file_id and an optional prompt, and proposes schema fields for the parser. replace_existing_schema controls whether the detected fields replace the current ones. You can still edit fields afterwards with PATCH /v1/parsers/{id}.

How do I extract data from documents through Jentic?

Search Jentic for 'extract data from documents', load the schema for POST /v1/extractions, and send the parser_id with your files as multipart form data. Poll GET /v1/extractions/{extraction_id} for status, then read the results endpoint. To run it on your own infrastructure, install Jentic One from its GitHub repo.

What are the rate limits for the PerfectParser Public API?

The OpenAPI spec does not specify rate limits. It states that credits are deducted by total page count, and GET /v1/credits returns your remaining balance. Check https://perfectparser.com for current limits.

Is there a PerfectParser MCP server?

You don't need an MCP server to give your agent the PerfectParser Public API. Jentic connects it directly from the API Directory: import it, store your API key once, and your agent calls it. Operations are discovered on demand, so no extra tool definitions sit in the agent's context.

Can I limit what my agent is allowed to do with the PerfectParser Public API?

Yes. For example, write a rule that allows only POST /v1/extractions, GET /v1/extractions/{extraction_id}, and GET /v1/extractions/{extraction_id}/results, so the agent can submit files and read results but cannot change or delete parsers or webhook subscriptions. Every call it makes is logged by your Jentic One instance.

PerfectParser Public API

AI ReadinessFoundational (D)44/100

See full scorecard

Official vendor OpenAPI document · agent-readyAI/MLVisionapiKey21 EndpointsREST

For Agents

Define document parsers with schema fields or auto-detect them from a sample, submit files for bulk extraction, poll status, and fetch or export structured results as JSON, CSV, or XLSX.

Use for: I need to extract vendor, line items, and totals from these invoices, Create a parser for purchase orders from a sample file, Check whether my extraction batch has finished, Export last week's extraction results as a CSV

Not supported: Does not generate or sign documents, store files as a document library, or run accounting workflows on the extracted data. Use for defining parsers and extracting structured data from documents only.

The PerfectParser Public API extracts structured data from documents using parsers you define: each parser has a name, a result mode of one object per file or per page, and a list of schema fields, which it can also detect automatically from a sample file and an optional prompt. You submit one or more files to a parser as a bulk extraction, follow its status from queued through processing to completed, failed, or partial, and read the results per extraction or per document, exporting them as JSON, CSV, or XLSX. Webhook subscriptions deliver document-completed and job-completed events to your server, and account endpoints report your profile and remaining credits, which are deducted by page count.

Jentic One on Github View OpenAPI Document

Show dimension breakdown

Foundational Compliance

Base layer of spec validity and structural soundness.

Grade: C-Signals: 4

87%

Lint Results

Aggregated quality score from linter diagnostics, weighted by severity.

100%

Resolution Completeness

Percentage of `$ref` references that resolve successfully.

Specification Validity

Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).

21%

Structural Integrity

Structural correctness score based on schema issues using logarithmic dampening.

Developer Experience & Jentic Compatibility

Clarity, completeness, and ingestion readiness for developers and tooling.

Grade: B+Signals: 4

28%

Example Density

How richly the API is illustrated with examples.

100%

Example Validity

Percentage of examples that conform to their schemas.

45%

Response Coverage

Percentage of operations with complete response definitions (success, client error, server error).

100%

Tooling Readiness

Health of API ingestion, bundling, and resolution within Jentic pipelines.

AI-Readiness & Agent Experience

Semantic breadth, depth, and agent comprehension for AI systems.

Grade: FSignals: 4

24%

Description Coverage

Coverage of descriptions across API elements.

Error Standardization

Coverage of RFC 9457 Problem Details for error responses.

OperationId Quality

Coverage, uniqueness, and casing consistency of operationIds for AI inference.

60%

Summary Coverage

Coverage of summaries across operations/tags/info.

Agent Usability

Functional utility, complexity comfort, and AI orchestration readiness.

Grade: A+Signals: 1

94%

Complexity Comfort

Agent comfort level based on API operational and structural complexity.

Security

Trust, risk posture, and security compliance.

Grade: C-Signals: 1

50%

Authentication Strength

Average quality of security schemes based on authentication method strength (weakest link for OAuth2).

AI Discoverability

Findability, semantic richness, and reasoning readiness.

Grade: ASignals: 1

82%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the PerfectParser Public API to your agent

Capabilities

Start building with PerfectParser Public API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

PerfectParser Public API

Jentic AI Readiness Score

PerfectParser Public API

Foundational Compliance

Lint Results

Resolution Completeness

Specification Validity

Structural Integrity

Developer Experience & Jentic Compatibility

Example Density

Example Validity

Response Coverage

Tooling Readiness

AI-Readiness & Agent Experience

Description Coverage

Error Standardization

OperationId Quality

Summary Coverage

Agent Usability

Complexity Comfort

Security

Authentication Strength

AI Discoverability

Descriptive Richness