Install Jentic One Beta

Connect the Podsqueeze API to your agent

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

Process Episode

Access Podsqueeze API resources via REST API

Use Cases

Patterns agents use Podsqueeze API for, with concrete tasks.

★ AI and Machine Learning Operations

Use the Podsqueeze API to perform ai ml operations programmatically. The API provides 1 endpoints covering core functionality including process episode.

Call POST / to process episode

GET STARTED

Start building with Podsqueeze API

Explore with Jentic One

View OpenAPI Document

Data Retrieval and Monitoring

Query Podsqueeze API endpoints to retrieve structured data for monitoring, reporting, or downstream processing. The API returns JSON responses that agents can parse directly, enabling automated data collection workflows without manual intervention.

Query the Podsqueeze API API to retrieve current data and verify the response contains expected fields

AI Agent Integration via Jentic

AI agents discover and call Podsqueeze 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 'process episode', load the operation schema, and execute with Jentic-managed credentials

Key Endpoints

1 endpoints — podsqueeze is a repurposing tool for podcasters that uses ai to turn episodes into content like transcripts, summaries, and social media posts.

METHOD

PATH

DESCRIPTION

POST

Process Episode

POST

Process Episode

Why Jentic?

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

Setup

Wiring the Podsqueeze API by hand means setting up bearer auth against its Cloud Functions host and posting episode jobs to a single endpoint yourself. Through Jentic you install once, import the Podsqueeze API from the API Directory, store the token once, and your agent calls it.

Permission scoping

Podsqueeze exposes a single POST operation that takes the episode details in the request body rather than pinning a resource in the URL path, so scope the agent to just that process-episode operation. That one operation is the whole allowed set, so the agent can do nothing beyond what you grant it.

Credential isolation

Your Podsqueeze 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 'process a podcast episode', and Jentic returns the matching Podsqueeze operation with its input schema so the agent calls the right endpoint without browsing the reference docs.

FAQs

Specific to using Podsqueeze API through Jentic.

What authentication does the Podsqueeze API use?

The Podsqueeze 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 process episode with the Podsqueeze API?

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

What are the rate limits for the Podsqueeze 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 process episode through Jentic?

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

How many endpoints does the Podsqueeze API have?

The Podsqueeze API exposes 1 endpoints covering episodes operations.

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

Yes. The Podsqueeze API exposes a single POST operation that processes an episode, taking the episode details in the request body, so your rules in your self-hosted Jentic One instance can grant the agent only that process-episode operation. Because that one operation is the entire allowed set, the agent can do nothing beyond what you permit. Your Podsqueeze token is stored encrypted by your own Jentic One instance and injected only at execution time, so the agent never sees the raw credential.

Podsqueeze API

Name: Podsqueeze API
Brand: Podsqueeze API
Availability: InStock

AI ReadinessNon-Ready (F)0/100

See full scorecard

Official vendor OpenAPI document · agent-readyAI/MLLanguage Modelsbearer1 EndpointsREST

For Agents

Programmatically process episode. Covers 1 operations with bearer authentication.

Use for: I need to process episode, I need to access Podsqueeze API programmatically, I want to integrate Podsqueeze API into my workflow, Search for available ai ml operations

Not supported: Does not handle payments, communications, or crm - use for ai and machine learning only.

Podsqueeze is a repurposing tool for podcasters that uses AI to turn episodes into content like transcripts, summaries, and social media posts. The API exposes 1 endpoints secured with bearer authentication.

Jentic One on Github View OpenAPI Document

Show dimension breakdown

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).

75%

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

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.

50%

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: FSignals: 1

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the Podsqueeze API to your agent

Capabilities

Use Cases

Start building with Podsqueeze API

Key Endpoints

Why Jentic?

Related APIs

FAQs

Podsqueeze API

Jentic AI Readiness Score

Podsqueeze 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