Install Jentic One Beta

Connect the LatLng API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the LatLng 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%2Flatlng.work%2Flatlng" | 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%2Flatlng.work%2Flatlng" | 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 LatLng API.

Convert a free-text address or place name into coordinates with forward geocoding, biased toward a lat and lon when given

Resolve a lat and lon pair into nearby street addresses with reverse geocoding

Find restaurants, cafes, or other places within a radius of a point using the nearby places search

Search places by name and narrow results by type, category, or country

GET STARTED

Start building with LatLng API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use LatLng API for, with concrete tasks.

★ Agent-driven location lookups through Jentic

An AI agent that answers questions like 'what is near this address' chains two LatLng calls: forward geocoding to turn the address into a lat and lon, then the nearby places search with a radius and category to list what is around it. Through Jentic the agent finds both operations by intent and calls them with the X-Api-Key credential injected at execution time, so the key never sits in the agent's context.

Call GET /api with q='221B Baker Street, London' and limit=1, take the returned coordinates, then call GET /v1/places/nearby with that lat and lon, radius=500, and category='cafe'

Address-to-coordinate conversion for logistics

Delivery and field-service apps need coordinates for every stop before they can plan anything. The LatLng forward geocoding operation accepts a free-text query, an optional lang for localized results, and optional lat and lon to prefer matches near a known area, which helps disambiguate common street names. Reverse geocoding handles the opposite direction when a driver's device reports a GPS fix that needs a readable address.

Call GET /reverse with lat=40.7484 and lon=-73.9857 and limit=1 to return the street address for the delivery driver's current position

Static map images for emails and reports

Order confirmations, incident reports, and listings often need a map image rather than an interactive widget. The LatLng static map operation renders an image from a center, zoom, width, height, and markers, and the POST variant accepts a GeoJSON FeatureCollection so routes or service areas can be drawn on the image directly.

Call GET /v1/static with center='51.5074,-0.1278', zoom=13, width=600, height=400, and markers for the two store locations, then attach the returned image to the report

Custom map datasets for service areas

Teams that maintain their own geographic data, such as delivery zones or franchise territories, can upload it to LatLng as a GeoJSON FeatureCollection. Each uploaded dataset gets a datasetId that can be listed, fetched, or deleted later, and powers custom dataset map tiles.

Call POST /v1/datasets with a FeatureCollection of three delivery-zone polygons, then call GET /v1/datasets/{datasetId} with the returned id to confirm the upload

Key Endpoints

12 endpoints — the latlng api turns place names and addresses into coordinates and back again, using openstreetmap data.

METHOD

PATH

DESCRIPTION

GET

/api

Forward geocode a text query

GET

/reverse

Reverse geocode coordinates

GET

/v1/places/nearby

Find places near a point

GET

/v1/places/search

Search places by name

GET

/v1/static

Render a static map image

POST

/v1/datasets

Upload a GeoJSON dataset

GET

/api

Forward geocode a text query

GET

/reverse

Reverse geocode coordinates

GET

/v1/places/nearby

Find places near a point

GET

/v1/places/search

Search places by name

GET

/v1/static

Render a static map image

POST

/v1/datasets

Upload a GeoJSON dataset

Why Jentic?

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

Setup

Wiring the LatLng API by hand means picking between the X-Api-Key header and the api_key query parameter, remembering which operations are open, and building query strings for each geocoding and places call. Through Jentic you install once, import LatLng from the API Directory, store the key once, and your agent calls it.

Permission scoping

Most LatLng operations take their inputs as query parameters, so rules bound which operations your agent may call rather than which places it looks up. Datasets are the exception: the datasetId sits in the URL path (/v1/datasets/{datasetId}), so a rule can pin your agent to one dataset. You choose the operations it may call, so destructive ones like dataset deletion are not included unless you add them.

Credential isolation

Your LatLng 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 'geocode an address' or 'find cafes near a point', and Jentic returns the matching LatLng operation with its input schema so the agent calls the right endpoint without browsing the reference docs.

FAQs

Specific to using LatLng API through Jentic.

Is there a LatLng MCP server?

You don't need an MCP server to give your agent the LatLng 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 your agent's context is not filled with tool definitions it will not use.

What authentication does the LatLng API use?

Per its OpenAPI spec, the LatLng API accepts an API key either in the X-Api-Key header or in the api_key query parameter. The place categories list and the health check are declared open and need no key. Through Jentic, the key is stored encrypted by your own Jentic One instance and injected at execution time.

Can I find places near a coordinate with the LatLng API?

Yes. GET /v1/places/nearby takes a required lat and lon plus optional radius, type, category, and limit. Call GET /v1/places/categories first to see which category values are available for filtering.

What are the rate limits for the LatLng API?

The OpenAPI spec does not specify rate limits. LatLng describes a free daily quota on its site; check https://www.latlng.work/docs for current limits.

How do I geocode an address with the LatLng API through Jentic?

Install Jentic One with `curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh`, import the LatLng API from the directory, and store your API key. Your agent then searches for 'geocode an address' and Jentic returns the GET /api operation, which takes the address in the q parameter. To run it on your own infrastructure, install Jentic One from its GitHub repo.

Can I draw GeoJSON on a LatLng static map?

Yes. POST /v1/static accepts a GeoJSON FeatureCollection in the request body, with type and features required, and returns a rendered map image. For simple pins, GET /v1/static takes center, zoom, width, height, and markers as query parameters instead.

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

Yes. For a lookup assistant, write a rule that allows only GET /api, GET /reverse, and GET /v1/places/nearby: the agent can geocode and search nearby places, while dataset uploads and deletions stay out of reach, and every call it makes is logged.

Latlng Work LatLng API

AI ReadinessAI-Aware (B-)61/100

See full scorecard

Official vendor OpenAPI document · agent-readyMaps GeolocationGeocodingapiKey (X-Api-Key header or api_key query parameter)12 EndpointsREST

For Agents

Geocode addresses, reverse geocode coordinates, search or find nearby places by category, and render static map images with markers or GeoJSON overlays, all backed by OpenStreetMap data.

Use for: I need to geocode a customer's shipping address into latitude and longitude, Find all cafes within 500 meters of these coordinates, Get the street address for a GPS point from a delivery driver, Search for a place called Central Park in the United States

Not supported: Does not handle turn-by-turn routing, travel-time matrices, IP geolocation, or live traffic. Use for geocoding, places search, static maps, and GeoJSON dataset hosting only.

The LatLng API turns place names and addresses into coordinates and back again, using OpenStreetMap data. Forward geocoding takes a free-text query in the q parameter with optional lat and lon to bias results, while reverse geocoding resolves a lat and lon pair into the nearest addresses. Beyond geocoding it searches places by name or category, finds places near a point within a radius, renders static map images from a center point or a posted GeoJSON FeatureCollection, and stores custom GeoJSON datasets for map tiles.

Jentic One on Github View OpenAPI Document

Show dimension breakdown

100

Foundational Compliance

Base layer of spec validity and structural soundness.

Grade: A+Signals: 4

99%

Lint Results

Aggregated quality score from linter diagnostics, weighted by severity.

100%

Resolution Completeness

Percentage of `$ref` references that resolve successfully.

100%

Specification Validity

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

100%

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

24%

Example Density

How richly the API is illustrated with examples.

100%

Example Validity

Percentage of examples that conform to their schemas.

50%

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: D+Signals: 4

32%

Description Coverage

Coverage of descriptions across API elements.

Error Standardization

Coverage of RFC 9457 Problem Details for error responses.

100%

OperationId Quality

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

57%

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: FSignals: 1

33%

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: A-Signals: 1

75%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the LatLng API to your agent

Capabilities

Start building with LatLng API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

Latlng Work LatLng API

Jentic AI Readiness Score

LatLng 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