Install Jentic One Beta
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the RAG Service 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%2Fswaggerhub.hmcts-dts%2Frag-service-api" | shStep 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%2Fswaggerhub.hmcts-dts%2Frag-service-api" | sh
jentic register # connects your agent to your Jentic One instanceJentic 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.
What an agent can do with RAG Service API.
Initiate upload process by submitting document metadata
Get status for given document reference
Generate response for user query synchronously
Check status of asynchronous request to provide summarised answer for user query
Monitor RAG Service API operational status and events
GET STARTED
Patterns agents use RAG Service API for, with concrete tasks.
★ Developer Tools Operations
Use the RAG Service API to perform developer tools operations programmatically. The API provides 6 endpoints covering core functionality including initiate upload process by submitting document metadata, get status for given document reference, get document status.
Call POST /document-upload to initiate upload process by submitting document metadata
Automated Document information summarised asynchronously Management
Automate document information summarised asynchronously operations by combining multiple RAG Service API endpoints. Agents can get status for given document reference and then get document status in a single workflow.
Call GET /document-upload/{documentReference} to get status for given document reference, then verify the result
AI Agent Integration via Jentic
AI agents discover and call RAG Service API endpoints through Jentic without managing credentials directly. An agent searches for the required operation by intent, receives the matching endpoint schema, and executes the call with Jentic-managed authentication. This eliminates the need to read API documentation or handle none tokens manually.
Search Jentic for 'initiate upload process by submitting document metadata', load the operation schema, and execute with Jentic-managed credentials
6 endpoints — api for rag service for document ingestion and answer retrieval.
METHOD
PATH
DESCRIPTION
/document-upload
Initiate upload process by submitting document metadata
/document-upload/{documentReference}
Get status for given document reference
/document-status
Get document status
/answer-user-query
Generate response for user query synchronously
/answer-user-query-async
Generate response for user query asynchronously
/answer-user-query-async-status/{transactionId}
Check status of asynchronous request to provide summarised answer for user query
/document-upload
Initiate upload process by submitting document metadata
/document-upload/{documentReference}
Get status for given document reference
/document-status
Get document status
/answer-user-query
Generate response for user query synchronously
/answer-user-query-async
Generate response for user query asynchronously
/answer-user-query-async-status/{transactionId}
Check status of asynchronous request to provide summarised answer for user query
What agents get from Jentic-routed access to this vendor.
Setup
Wiring the RAG Service API by hand means coding its document upload, status, and query calls against the service host and handling the async query polling and retries yourself, even though it declares no auth scheme. Through Jentic you install once, import the RAG Service API from the API Directory, and your agent calls it.
Permission scoping
This API puts the document reference and transaction id in the URL path (/document-upload/{documentReference}, /answer-user-query-async-status/{transactionId}), so a rule can pin your agent to one document or query transaction: it can check that item's status and nothing else. You choose the operations it may call, so writes like uploading a document are not included unless you add them.
Credential isolation
This RAG Service API declares no credential, so there is nothing to store. If your deployment later requires one, your own Jentic One instance stores it encrypted and injects it at execution time so it never enters the agent's prompt, logs, or context.
Intent-based discovery
Agents search Jentic by intent such as 'answer a user query from documents' or 'check document upload status', and Jentic returns the matching RAG Service API operation with its input schema so the agent calls the right endpoint without browsing the reference docs.
Alternatives and complements available in the Jentic catalogue.
Specific to using RAG Service API through Jentic.
What authentication does the RAG Service API use?
The RAG Service API uses no authentication. Through Jentic, these credentials are stored encrypted in your Jentic One instance and injected at execution time, so raw secrets never enter the agent context.
Can I initiate upload process by submitting document metadata with the RAG Service API?
Yes. Use the POST /document-upload endpoint. The API returns structured JSON responses that agents can parse and act on directly.
What are the rate limits for the RAG Service API?
Rate limits are not specified in the OpenAPI spec. Check the vendor documentation for current limits. Through Jentic, rate limiting is handled automatically with retry logic built into the execution layer.
How do I initiate upload process by submitting document metadata through Jentic?
Install the Jentic SDK with pip install jentic, authenticate through Jentic One, the self-hosted execution layer, then search for 'initiate upload process by submitting document metadata'. Jentic returns the matching RAG Service API operation with its input schema. Load the schema and execute the call - credentials are injected automatically.
How many endpoints does the RAG Service API have?
The RAG Service API exposes 6 endpoints covering document information summarised asynchronously, document information summarised synchronously, document ingestion initiation operations.
Can I limit what my agent is allowed to do with the RAG Service API?
Yes. Jentic One is self-hosted, so your own rules decide which of the RAG Service API operations your agent may call and which credentials it may use. Because this API carries the document reference and transaction id in the URL path (GET /document-upload/{documentReference}, GET /answer-user-query-async-status/{transactionId}), a rule can pin the agent to one document or query transaction and let it only check that item's status. You choose the operations it may call, so writes like POST /document-upload or POST /answer-user-query stay off unless you add them.
Know of an official OpenAPI document? Contribute it →
For Agents
Programmatically initiate upload process by submitting document metadata, get status for given document reference. Covers 6 operations.
Use for: I need to initiate upload process by submitting document metadata, I want to status for given document reference, Search for document status, Find all generate response for user query synchronously
Not supported: Does not handle payments, communications, or crm - use for developer tools only.
API for RAG service for document ingestion and answer retrieval. The API exposes 6 endpoints.
This API is usable in Jentic One now. Its AI-readiness score against Jentic's framework shows where it stands today and where improvements would make it even easier for agents to use.
Base layer of spec validity and structural soundness.
Aggregated quality score from linter diagnostics, weighted by severity.
Percentage of `$ref` references that resolve successfully.
Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).
Structural correctness score based on schema issues using logarithmic dampening.
Clarity, completeness, and ingestion readiness for developers and tooling.
How richly the API is illustrated with examples.
Percentage of examples that conform to their schemas.
Percentage of operations with complete response definitions (success, client error, server error).
Health of API ingestion, bundling, and resolution within Jentic pipelines.
Semantic breadth, depth, and agent comprehension for AI systems.
Coverage of descriptions across API elements.
Coverage of RFC 9457 Problem Details for error responses.
Coverage, uniqueness, and casing consistency of operationIds for AI inference.
Coverage of summaries across operations/tags/info.
Functional utility, complexity comfort, and AI orchestration readiness.
Agent comfort level based on API operational and structural complexity.
Trust, risk posture, and security compliance.
Average quality of security schemes based on authentication method strength (weakest link for OAuth2).
Findability, semantic richness, and reasoning readiness.
Clarity and depth of descriptions across API elements.
Score it yourself
Every API in the directory is allowlisted, so you can re-score it with no key required.
npx @jentic/api-scorecard-cli score <openapi-url>