Install Jentic One Beta

Connect the CloudCrane API to your agent

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

Call a deployed tool and read its own input schema before calling it

Search a tool's records and retrieve a single record by id

Look up value set entries to filter or exclude results by

Report a returned value that looks wrong

Build datasets, fields, and value sets inside a workspace

GET STARTED

Start building with CloudCrane API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use CloudCrane API for, with concrete tasks.

★ Agent Calls a Deployed Tool

An AI agent connected to the CloudCrane API can use a deployed tool as a first-class data source. It reads the tool's input schema so it knows exactly what the tool accepts, then searches the tool's records and retrieves the matching record by id. Because the tool key opens one tool and nothing else, the agent's reach is bounded to that single tool.

Read the schema for the tool named lookup, search its records for the query term, and return the top matching record

Value-Constrained Record Search

Many lookups need to be bounded by an allowed set of values. The CloudCrane API lets an agent fetch a tool's value set entries first, then search the tool's records filtering or excluding by those values, so results stay within the categories the tool defines. This keeps an agent's query aligned with the data the tool actually holds rather than guessing filter values.

Fetch the value set entries for a tool, then search its records excluding any entry in the deprecated value set

Data Correction Feedback Loop

When a deployed tool returns a value that looks wrong, the CloudCrane API accepts a report on that record so the issue is captured for review. An agent that notices an inconsistency can file the report inline instead of silently passing bad data downstream, feeding the workspace's accuracy process that gates future publishes.

Report the record returned for a query as incorrect, including the record id and why the value looks wrong

Build and Publish a Tool

The CloudCrane API's build interface lets a workspace owner create datasets, fields, and value sets, start runs, and publish a tool once its accuracy gate passes, then deploy it for agents to call. This turns tool creation into an API-driven pipeline where a build agent can assemble a dataset and ship a callable tool without a manual console step.

Through the build interface, create a dataset and its fields, start a run, and publish the tool when the accuracy gate passes

Key Endpoints

7 endpoints — the cloudcrane api calls deployed tools over rest and reads a tool's records as you search, filter, and retrieve them.

METHOD

PATH

DESCRIPTION

GET

/v1/tools/{name}/schema

Read what a tool is and what it takes

POST

/v1/tools/{name}/search

Search the tool's records

POST

/v1/tools/{name}/values

Look up value set entries to filter or exclude by

POST

/v1/tools/{name}/report

Report a returned value that looks wrong

GET

/v1/tools/{name}/items/{recordId}

Get one record by id

POST

/mcp/{name}

Call the tool over its MCP endpoint

POST

/build/mcp

Read and build in the workspace over the build MCP endpoint

GET

/v1/tools/{name}/schema

Read what a tool is and what it takes

POST

/v1/tools/{name}/search

Search the tool's records

POST

/v1/tools/{name}/values

Look up value set entries to filter or exclude by

POST

/v1/tools/{name}/report

Report a returned value that looks wrong

GET

/v1/tools/{name}/items/{recordId}

Get one record by id

POST

/mcp/{name}

Call the tool over its MCP endpoint

POST

/build/mcp

Read and build in the workspace over the build MCP endpoint

Why Jentic?

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

Setup

Wiring the CloudCrane API by hand means handling two bearer key types, reading each tool's own input schema before you can call it, and threading the traceparent header to join your traces. Through Jentic you install once, import CloudCrane from the API Directory, store the key once, and your agent calls it.

Permission scoping

CloudCrane puts the tool name in the URL path (/v1/tools/{name}/...), and a tool key opens one tool and nothing else, so a rule can pin your agent to one tool: it can read that tool's schema, search its records, and fetch a record by id and reach no other tool or the build surface. You choose the operations it may call, so the report and build operations are not included unless you add them.

Credential isolation

Your CloudCrane 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 'call a deployed CloudCrane tool' or 'search a tool's records', and Jentic returns the matching CloudCrane operation with its input schema so the agent calls the right endpoint without browsing the reference docs.

FAQs

Specific to using CloudCrane API through Jentic.

What authentication does the CloudCrane API use?

The CloudCrane API uses bearer tokens per its OpenAPI spec: a tool key (prefixed cc_live_) that opens one tool and nothing else, and a build key (prefixed cc_build_) that reads one workspace and can create datasets, value sets, and fields, start runs, publish, and deploy tools. Through Jentic the key is stored once by your own self-hosted instance and injected at call time, so it never sits in your agent's prompt or logs.

Is there a CloudCrane MCP server?

Yes - CloudCrane exposes each deployed tool over an MCP endpoint, and a workspace over a build MCP endpoint. You can also connect CloudCrane directly through Jentic: your agent gets the full 7-endpoint surface, including the REST search and record endpoints, without loading another server's tool definitions into its context, your tool key is injected at call time by your self-hosted instance, and your rules decide which operations the agent may call.

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

Yes. Write a rule that allows only the schema, search, and get-record operations for one tool, so the agent can read and query that tool but cannot report values or touch the build interface. Combined with a tool key that opens a single tool, the agent's reach is bounded twice over, and every call it makes is logged.

Can I search a deployed tool's records with the CloudCrane API?

Yes. Search a tool with POST /v1/tools/{name}/search and retrieve a single record with GET /v1/tools/{name}/items/{recordId}. You can read the tool's input schema first at /v1/tools/{name}/schema and look up the value set entries to filter by at /v1/tools/{name}/values, so an agent queries with the exact shape the tool expects.

What are the rate limits for the CloudCrane API?

The OpenAPI spec does not specify rate limits for the CloudCrane API. Check the documentation at https://cloudcrane.ai for current limits, and use the X-Request-Id returned on every reply when reporting an issue so support can trace the exact call.

How do I call a deployed tool with the CloudCrane API through Jentic?

Search Jentic for 'call a deployed CloudCrane tool' and it returns the POST /v1/tools/{name}/search operation with its input schema. Pass the tool name and your query and the agent gets back the matching records. To run it on your own infrastructure, install Jentic One from its GitHub repo.

CloudCrane API

AI ReadinessAI-Aware (B)65/100

See full scorecard

Official vendor OpenAPI document · agent-readyDeveloper ToolsCi Cdbearer7 EndpointsREST

For Agents

Call deployed tools over REST, search and retrieve their records, read each tool's input schema, and report a wrong value. A build interface creates datasets and value sets, starts runs, and publishes a tool once its accuracy gate passes.

Use for: Call a deployed CloudCrane tool to look something up, Search a tool's records for a matching entry, Get a single record from a tool by its id, Read a tool's input schema so I know what it accepts

Not supported: Does not host language models, store vector embeddings, or run arbitrary code. Use for calling and building deployed CloudCrane data tools only.

The CloudCrane API calls deployed tools over REST and reads a tool's records as you search, filter, and retrieve them. Each tool exposes its own input schema, returns a record by id, and accepts a report when a returned value looks wrong, while a build interface lets you create datasets, fields, and value sets, start runs, and publish a tool once its accuracy gate passes. Calls can join your own distributed trace through the W3C traceparent header, and every reply carries an X-Request-Id.

Jentic One on Github View OpenAPI Document

Show dimension breakdown

Foundational Compliance

Base layer of spec validity and structural soundness.

Grade: A-Signals: 4

98%

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).

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

Example Density

How richly the API is illustrated with examples.

100%

Example Validity

Percentage of examples that conform to their schemas.

71%

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

35%

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.

48%

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: B-Signals: 1

60%

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

73%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the CloudCrane API to your agent

Capabilities

Start building with CloudCrane API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

CloudCrane API

Jentic AI Readiness Score

CloudCrane 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