Install Jentic One Beta

Connect the ChartQuery API Reference to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the ChartQuery API Reference, 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%2Fchartquery.com%2Fchartquery" | 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%2Fchartquery.com%2Fchartquery" | 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 ChartQuery API Reference API.

Render a Chart.js chart such as bar, line, pie, radar, or scatter from labels and datasets as a PNG or SVG

Generate a chart or diagram from a plain-English prompt with the AI endpoints

Render a diagram from Mermaid, D2, PlantUML, Graphviz, BPMN, or other diagram source

Generate styled QR codes for URLs, text, vCards, or WiFi with colors, dot styles, and custom corners

GET STARTED

Start building with ChartQuery API Reference API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use ChartQuery API Reference API for, with concrete tasks.

★ Agent-generated charts through Jentic

An AI agent summarising data for a user wants to show a chart, not a table. Through Jentic the agent searches for 'render a bar chart', receives the ChartQuery POST /v1/chart operation with its input schema, and sends type 'bar' with data labels and datasets and format 'png'. The image comes back ready to display, or with share set to true the agent gets a public URL to embed.

Call POST /v1/chart with type 'bar', title 'Q1 revenue', format 'png', and data with labels ['Jan','Feb','Mar'] and one dataset [12,15,9], then return the image

Diagrams from source or prompt

A developer documenting a system wants diagrams rendered without installing Mermaid or PlantUML locally. POST /v1/diagram takes diagram_type and diagram_source and returns PNG, SVG, JPEG, or PDF via output_format. When only a description exists, POST /v1/diagram/ai takes a prompt and an optional diagram_type such as mermaid or d2 and returns the rendered diagram.

Call POST /v1/diagram with diagram_type 'mermaid', diagram_source 'graph TD; Start-->Review-->Done', and output_format 'png', then return the image

QR codes and barcodes for products

A shop preparing packaging needs scannable codes. POST /v1/barcode takes data and a type such as ean13 or code128 and returns SVG or PNG, with options for bar_width, height, colors, and text position. POST /v1/qrcode encodes URLs, text, vCards, or WiFi credentials with colors, dot_type, and margin controls.

Call POST /v1/barcode with data '4006381333931', type 'ean13', and format 'png', then call POST /v1/qrcode with data 'https://example.com/product' and format 'png'

Thermal label printing workflows

A warehouse moving between printer brands needs labels in a different command language. POST /v1/label/convert translates printer commands from one language to another (for example zpl to tsc), POST /v1/label/validate checks source before printing, and POST /v1/label/compile turns width and elements into printer commands for a chosen language. POST /v1/label previews the label as an image first.

Call POST /v1/label/validate with the ZPL source and language 'zpl', then POST /v1/label/convert with the same source, from 'zpl', and to 'tsc', and return the converted commands

Key Endpoints

27 endpoints — the chartquery api renders charts, diagrams, qr codes, barcodes, and thermal printer labels as png, svg, jpeg, or pdf images from a json config or a plain-english prompt.

METHOD

PATH

DESCRIPTION

POST

/v1/chart

Render a Chart.js image

POST

/v1/chart/ai

Generate a chart from a prompt

POST

/v1/diagram

Render a diagram from source

POST

/v1/diagram/ai

Generate a diagram from a prompt

POST

/v1/qrcode

Generate a QR code

POST

/v1/barcode

Generate a barcode

POST

/v1/label/convert

Convert printer commands between languages

GET

/v1/chart/view/{id}

View a saved chart

POST

/v1/chart

Render a Chart.js image

POST

/v1/chart/ai

Generate a chart from a prompt

POST

/v1/diagram

Render a diagram from source

POST

/v1/diagram/ai

Generate a diagram from a prompt

POST

/v1/qrcode

Generate a QR code

POST

/v1/barcode

Generate a barcode

POST

/v1/label/convert

Convert printer commands between languages

GET

/v1/chart/view/{id}

View a saved chart

Why Jentic?

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

Setup

Wiring ChartQuery by hand means knowing which operations take the x-api-key header, which fields go in a POST body versus a GET query (diagram_type versus type, output_format versus format), and polling jobs for slow renders. Through Jentic you install once, import ChartQuery from the API Directory, store the key once, and your agent calls it.

Permission scoping

ChartQuery puts each tool in its own URL path (/v1/chart, /v1/diagram, /v1/label/convert), and saved renders sit under an id in the path, so a rule can limit your agent to the tools it needs. You choose the operations it may call, so higher-cost AI endpoints like POST /v1/chart/ai are not included unless you add them.

Credential isolation

Your ChartQuery 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 'render a bar chart' or 'generate an EAN-13 barcode', and Jentic returns the matching ChartQuery operation with its input schema so the agent sends the right fields without browsing the reference docs.

FAQs

Specific to using ChartQuery API Reference API through Jentic.

What authentication does the ChartQuery API use?

The ChartQuery API declares one scheme, an API key in the `x-api-key` header (ApiKeyAuth). Per its OpenAPI spec the key is attached to the AI endpoints (GET and POST /v1/chart/ai and /v1/diagram/ai), GET /v1/usage, GET /v1/stats, and GET /v1/jobs/{id}. The chart, diagram, QR code, barcode, label, and saved-view operations are marked public in the spec, though their descriptions list credit costs, so check the ChartQuery docs for how those are billed.

Which diagram languages does the ChartQuery API support?

POST /v1/diagram accepts a diagram_type including mermaid, d2, plantuml, graphviz, bpmn, c4plantuml, dbml, excalidraw, nomnoml, structurizr, and svgbob, among others in its enum. The AI endpoint POST /v1/diagram/ai picks between mermaid, d2, plantuml, and graphviz, or uses the one you set.

Can I convert ZPL labels to another printer language with the ChartQuery API?

Yes. POST /v1/label/convert takes source, from, and to. The from language can be tsc, zpl, epl, cpcl, dpl, sbpl, or ipl, and the to language adds escpos and starprnt. Use POST /v1/label/validate first to check the source, and POST /v1/label to preview the result as an image.

What are the rate limits for the ChartQuery API?

The OpenAPI spec does not specify rate limits; it lists credit costs per endpoint instead. Check the ChartQuery documentation at https://chartquery.com for current limits and plan details.

How do I render a Mermaid diagram through Jentic?

Search Jentic for 'render a Mermaid diagram', load the POST /v1/diagram operation, and execute it with diagram_type 'mermaid', your diagram_source, and output_format 'png'. Set share to true if you want public view and embed URLs instead of the image. To run it on your own infrastructure, install Jentic One from its GitHub repo.

Is there a ChartQuery MCP server?

You don't need an MCP server to give your agent ChartQuery. Jentic connects it directly from the API Directory: import it, store your API key once, and your agent finds the chart, diagram, QR, barcode, or label operation it needs on demand instead of carrying every tool definition in its context.

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

Yes. For an agent that only draws charts and diagrams from data you give it, write a rule that allows POST /v1/chart and POST /v1/diagram. It can render those images, but the AI generation endpoints, which cost more credits, and the label tools stay outside its reach, and every call it makes is logged.

ChartQuery API Reference

AI ReadinessFoundational (C+)58/100

See full scorecard

Official vendor OpenAPI document · agent-readyMediaImage ProcessingapiKey27 EndpointsREST

For Agents

Render Chart.js charts, Mermaid or PlantUML diagrams, QR codes, barcodes, and thermal printer labels as images, or generate a chart or diagram from a plain-English prompt.

Use for: Make a bar chart of Q1 revenue: Jan 12, Feb 15, Mar 9, Render this Mermaid flowchart as a PNG, Generate a QR code for https://example.com, Create an EAN-13 barcode for 4006381333931

Not supported: Does not store datasets, host dashboards, or send jobs to physical printers. Use for rendering charts, diagrams, QR codes, barcodes, and label commands only.

The ChartQuery API renders charts, diagrams, QR codes, barcodes, and thermal printer labels as PNG, SVG, JPEG, or PDF images from a JSON config or a plain-English prompt. Charts use Chart.js types such as bar, line, pie, radar, and scatter, and diagrams accept source in languages including Mermaid, D2, PlantUML, and Graphviz. Label endpoints compile, preview, parse, validate, and convert printer commands across languages such as ZPL, TSC, EPL, and CPCL. Any render can be saved with share to return view, render, and embed URLs that are public.

Jentic One on Github View OpenAPI Document

Show dimension breakdown

Foundational Compliance

Base layer of spec validity and structural soundness.

Grade: C-Signals: 4

89%

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).

17%

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

12%

Example Density

How richly the API is illustrated with examples.

84%

Example Validity

Percentage of examples that conform to their schemas.

75%

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: DSignals: 4

56%

Description Coverage

Coverage of descriptions across API elements.

Error Standardization

Coverage of RFC 9457 Problem Details for error responses.

93%

OperationId Quality

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

24%

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: BSignals: 1

66%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the ChartQuery API Reference to your agent

Capabilities

Start building with ChartQuery API Reference API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

ChartQuery API Reference

Jentic AI Readiness Score

ChartQuery API Reference

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