Install Jentic One Beta

Connect the Vectara API to your agent

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

Create a corpus

List corpora

Get a corpus

Update a corpus

Delete a corpus

GET STARTED

Start building with Vectara API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use Vectara API for, with concrete tasks.

★ Developer Tools Operations

Use the Vectara API to perform developer tools operations programmatically. The API provides 12 endpoints covering core functionality including create a corpus, list corpora, get a corpus.

Call POST /corpora to create a corpus

Automated Chat Management

Automate chat operations by combining multiple Vectara API endpoints. Agents can list corpora and then get a corpus in a single workflow.

Call GET /corpora to list corpora, then verify the result

AI Agent Integration via Jentic

AI agents discover and call Vectara 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 bearer tokens manually.

Search Jentic for 'create a corpus', load the operation schema, and execute with Jentic-managed credentials

Key Endpoints

12 endpoints — vectara is a genai platform providing retrieval augmented generation (rag) as a service.

METHOD

PATH

DESCRIPTION

POST

/corpora

Create a corpus

GET

/corpora

List corpora

GET

/corpora/{corpus_key}

Get a corpus

PATCH

/corpora/{corpus_key}

Update a corpus

DELETE

/corpora/{corpus_key}

Delete a corpus

POST

/corpora/{corpus_key}/documents

Add a document to a corpus

GET

/corpora/{corpus_key}/documents

List documents in a corpus

GET

/corpora/{corpus_key}/documents/{document_id}

Get a document

POST

/corpora

Create a corpus

GET

/corpora

List corpora

GET

/corpora/{corpus_key}

Get a corpus

PATCH

/corpora/{corpus_key}

Update a corpus

DELETE

/corpora/{corpus_key}

Delete a corpus

POST

/corpora/{corpus_key}/documents

Add a document to a corpus

GET

/corpora/{corpus_key}/documents

List documents in a corpus

GET

/corpora/{corpus_key}/documents/{document_id}

Get a document

Why Jentic?

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

Setup

Wiring the Vectara API by hand means handling its bearer JWT auth against api.vectara.io and coding each corpus and document operation yourself. Through Jentic you install once, import the Vectara API from the API Directory, store the token once, and your agent calls it.

Permission scoping

Vectara puts the corpus key and document id in the URL path (/corpora/{corpus_key}, /corpora/{corpus_key}/documents/{document_id}), so a rule can pin your agent to one corpus. You choose the operations it may call, so destructive ones like deleting a corpus or a document are not included unless you add them.

Credential isolation

Your Vectara bearer token 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 'create a corpus' or 'add a document to a corpus', and Jentic returns the matching Vectara operation with its input schema so the agent calls the right endpoint without browsing the reference docs.

FAQs

Specific to using Vectara API through Jentic.

What authentication does the Vectara API use?

The Vectara API uses a Bearer token in the Authorization header. 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 create a corpus with the Vectara API?

Yes. Use the POST /corpora endpoint. The API returns structured JSON responses that agents can parse and act on directly.

What are the rate limits for the Vectara 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 create a corpus through Jentic?

Install the Jentic SDK with pip install jentic, authenticate through Jentic One, the self-hosted execution layer, then search for 'create a corpus'. Jentic returns the matching Vectara API operation with its input schema. Load the schema and execute the call - credentials are injected automatically.

How many endpoints does the Vectara API have?

The Vectara API exposes 12 endpoints covering chat, chats, corpora operations.

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

Yes. Because you run Jentic One yourself, your own rules decide which Vectara operations and credentials the agent may use. Vectara puts the corpus key and document id in the URL path (/corpora/{corpus_key} and /corpora/{corpus_key}/documents/{document_id}), so you can pin the agent to a single corpus and grant only read operations like listing corpora and getting documents. Destructive calls such as deleting a corpus or a document stay off unless you explicitly add them.

Vectara API

AI ReadinessAI-Aware (B+)69/100

See full scorecard

Official vendor OpenAPI document · agent-readyDeveloper ToolsSource Controlbearer12 EndpointsREST

For Agents

Programmatically create a corpus, list corpora. Covers 12 operations with bearer authentication.

Use for: I need to a corpus, I want to corpora, Search for a corpus, Find all a corpus

Not supported: Does not handle payments, communications, or crm - use for developer tools only.

Vectara is a GenAI platform providing Retrieval Augmented Generation (RAG) as a service. The API enables corpus management, document indexing, and semantic search with grounded generation. The API exposes 12 endpoints secured with bearer authentication.

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

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).

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

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: DSignals: 4

28%

Description Coverage

Coverage of descriptions across API elements.

Error Standardization

Coverage of RFC 9457 Problem Details for error responses.

92%

OperationId Quality

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

63%

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: A-Signals: 1

75%

Authentication Strength

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

100

AI Discoverability

Findability, semantic richness, and reasoning readiness.

Grade: A+Signals: 1

100%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the Vectara API to your agent

Capabilities

Start building with Vectara API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

Vectara API

Jentic AI Readiness Score

Vectara 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