Skip to content
Design & CreativeAuto-generatedScore: 34

ART19 Content API Documentation MCP Server

The ART19 Content API is a robust, read-only interface provided by ART19, a leading enterprise podcast hosting and analytics platform, designed for programmatic access to its comprehensive podcast content database.

Quick Start Summary

The ART19 Content API Documentation MCP server is a Model Context Protocol bridge that connects AI assistants — including Claude Desktop, Cursor, Windsurf, and VS Code Copilot — to the ART19 Content API Documentation API through natural language. It exposes 10 API endpoints as callable tools, such as Get ClassificationInclusion records, Get a specific classification inclusion, Get a list of classifications, and more. No authentication is required — setup takes approximately 30 seconds. The server uses STDIO transport and can be installed by running npx -y @mcp/art19-com. This integration is sourced from the auto ART19 Content API Documentation OpenAPI specification (v1.0.0) and has a quality score of 34/99 (fair documentation coverage).

10Endpointstools mapped
NoneAuthopen access
34/99Qualityfair
~30 secSetupno auth

Server Details

Category
Design & Creative
Authentication
None
Endpoints
10 operations
Transport
STDIO
Spec Version
v1.0.0
Install Command
npx -y @mcp/art19-com

Environment Variables

ART19_CONTENT_API_DOCUMENTATION_API_KEY

Example: your_art19_content_api_documentation_api_key

Top Endpoints

GET
/classification_inclusions

Get ClassificationInclusion records

GET
/classification_inclusions/{id}

Get a specific classification inclusion

GET
/classifications

Get a list of classifications

GET
/classifications/{id}

Get a specific classification

GET
/credits

Get a list of credits

Own this API?

Verify ownership of this listing to control the description, configuration details, and documentation links. Choose between free manual verification or instant premium placement.

Option 1: Free Verification

Slow manual review. Requires creating a GitHub issue with verified documentation or domain verification.

  • • Verified badge on page
  • • Standard search sorting
  • • 2-3 business days review
Start Free Claim →
Instant & Boosted

Option 2: Featured Upgrade($9/mo)

Instant verification plus premium styling, featured badges, and directory placement boost.

  • • ★ Featured star & amber highlight border
  • • Top of directory search placement
  • • Instant activation via claim token

📖 Detailed MCP Integration Guide

A technical breakdown of capabilities, agent workflows, and security/configuration best practices.

Capabilities & Use Cases
The ART19 Content API is a robust, read-only interface provided by ART19, a leading enterprise podcast hosting and analytics platform, designed for programmatic access to its comprehensive podcast content database. Its core capability is to deliver detailed metadata for podcasts, episodes, and associated organizational structures such as classifications and credits, adhering strictly to the standardized JSON:API specification. This enables developers, data engineers, and media companies to build custom integrations, perform bulk data analysis, sync content catalogs with other systems, or create sophisticated content management dashboards. Typical use cases include aggregating episode data for competitive intelligence, automating the generation of sitemaps for large podcast networks, verifying the publication order and sibling relationships within a series for editorial quality checks, and enriching internal databases with up-to-date credit and classification information. The API's structured endpoints for episodes, classifications, and credits facilitate granular queries, making it an essential tool for enterprises managing large-scale podcast portfolios or requiring reliable, machine-readable access to podcast content graphs.
🤖AI Agent Value
Exposing this API as a toolset via the Model Context Protocol (MCP) transforms it from a static documentation reference into a dynamic, queryable knowledge base for an AI coding assistant. An AI agent equipped with these MCP tools gains the ability to interact with the ART19 content graph as a living API reference, moving beyond code generation to perform real-time data retrieval and validation. This creates significant value by enabling the AI to ground its suggestions and outputs in the actual, current state of a user's podcast catalog. For instance, instead of generating boilerplate code for an API call, the AI can instantly fetch the real episode list for a specific series, understand the existing classification taxonomy, or verify the authentication requirements for a new endpoint, drastically reducing the cycle time between development, testing, and deployment. This integration effectively turns the AI into a context-aware pair programmer with direct, secure access to the necessary content data.
💬Example Workflows
A developer leveraging this MCP server can instruct the AI agent to perform a variety of dynamic, context-rich tasks that automate manual workflows. For example, a developer could ask the AI, "Using the ART19 tools, retrieve the episodes for series ID 'abc123' and then identify which episode is the third in the sequence and list its credits," prompting the agent to chain API calls to GET /episodes and GET /credits to compile a report. Another practical workflow could be, "Check if the episode with ID 'xyz789' has a next sibling, and if so, get its title and publication date," which would automate a publishing order verification task. Furthermore, the AI could be directed to "Enumerate all classifications available in the system and summarize them," providing an instant overview of the organizational structure without manual console queries. These examples illustrate how the MCP server enables the AI to act as an automation engine for data discovery, validation, and transformation tasks directly within the development environment.
🛡️Security & Auth
Critical configuration and security practices must be diligently followed when deploying this MCP server. Although the API uses token-based authentication via the HTTP Authorization header, the provided documentation note indicates a "None" authentication method for this specific API description, suggesting the tools may be intended for a sandboxed or public-data subset; however, in a production integration, valid tokens are mandatory. Developers must ensure that authentication tokens are stored securely as environment variables or in a dedicated secrets manager, never hardcoded into source files or MCP server configurations. Adherence to the principle of least privilege is paramount: tokens should be generated with the minimum required permissions, ideally read-only access scoped to specific podcast series or accounts where possible. All requests must include the correct Accept: application/vnd.api+json header to ensure proper API communication. It is also a best practice to implement rate limiting and request logging within the MCP server to monitor usage and prevent abuse, safeguarding both the integrity of the ART19 platform and the security of the consuming application's credentials.

Similar APIs

Other APIs in the Design & Creative category.

Figma API

Access Figma files, components, and styles for design-to-code workflows in your AI development environment.

Personal Access Token

EC2 Image Builder

EC2 Image Builder is a fully managed service provided by Amazon Web Services (AWS) that fundamentally streamlines the creation, maintenance, and distribution of secure, consistent, and production-ready server images, often referred to as "golden images." At its core, the service eliminates the manual, error-prone, and time-consuming processes traditionally associated with image management by providing a declarative, pipeline-based approach. Users define image recipes—specifying a source image, components (containing installation scripts, configuration steps, and tests), and infrastructure settings—and the service orchestrates the entire build process on AWS infrastructure. This includes launching temporary instances, applying customizations, running security and compliance validations, and finally, creating the image or container. The primary use cases span from enterprise IT teams standardizing hundreds of golden images for diverse workloads across global regions, to DevOps engineers rapidly provisioning secure, compliant base images for containerized microservices or scalable compute fleets, ensuring every deployment starts from a known, auditable, and up-to-date foundation.

Amazon Kinesis Video Streams Media

The Amazon Kinesis Video Streams Media API is a specialized streaming service provided by Amazon Web Services (AWS) that enables developers to reliably ingest, store, and retrieve media streams such as video and audio at scale. The core endpoint, POST /getMedia, facilitates the retrieval of media fragments from Kinesis Video Streams, allowing applications to pull continuous or on-demand video and audio data from cloud-hosted streams. This API is particularly powerful for enterprises and organizations dealing with large volumes of real-time or archival media content originating from cameras, microphones, drones, and other media-producing devices. Typical use cases span security and surveillance systems where footage must be accessed and analyzed on demand, media broadcasting platforms that require low-latency stream retrieval, healthcare applications involving remote patient monitoring video feeds, industrial inspection systems where drones capture inspection footage, and smart city infrastructure that processes live feeds from traffic and public safety cameras. By abstracting the complexity of managing massive media storage and delivery, Kinesis Video Streams Media allows developers to focus on building application logic rather than infrastructure.

Amazon Kinesis Video Streams Archived Media

The Amazon Kinesis Video Streams Archived Media API is a specialized service provided by Amazon Web Services (AWS) that enables programmatic access to retrieve and transform archived video and audio streams stored within Kinesis Video Streams. Its core capabilities center on on-demand data extraction, allowing users to pull specific clips, generate adaptive streaming manifests (HLS and DASH), extract individual image frames, and query the underlying fragment metadata of archived streams. This API is fundamental for enterprises that need to analyze historical video footage, such as for security and surveillance retrospectives, media asset management, industrial IoT inspection, and smart city analytics. Typical use cases include forensic investigation where an operator needs a precise clip of an incident, content creators repurposing raw footage from cloud-based cameras, or automated systems pulling frames for machine learning model training and validation. It serves as the critical data plane for unlocking the value of video data stored in the cloud.

Related MCP Server Integrations

Figma API MCP Setup

Access Figma files, components, and styles for design-to-code workflows in your AI development environment.

Design & CreativeConfigure →

EC2 Image Builder MCP Setup

EC2 Image Builder is a fully managed service provided by Amazon Web Services (AWS) that fundamentally streamlines the creation, maintenance, and distribution of secure, consistent, and production-ready server images, often referred to as "golden images." At its core, the service eliminates the manual, error-prone, and time-consuming processes traditionally associated with image management by providing a declarative, pipeline-based approach. Users define image recipes—specifying a source image, components (containing installation scripts, configuration steps, and tests), and infrastructure settings—and the service orchestrates the entire build process on AWS infrastructure. This includes launching temporary instances, applying customizations, running security and compliance validations, and finally, creating the image or container. The primary use cases span from enterprise IT teams standardizing hundreds of golden images for diverse workloads across global regions, to DevOps engineers rapidly provisioning secure, compliant base images for containerized microservices or scalable compute fleets, ensuring every deployment starts from a known, auditable, and up-to-date foundation.

Design & CreativeConfigure →

Amazon Kinesis Video Streams Media MCP Setup

The Amazon Kinesis Video Streams Media API is a specialized streaming service provided by Amazon Web Services (AWS) that enables developers to reliably ingest, store, and retrieve media streams such as video and audio at scale. The core endpoint, POST /getMedia, facilitates the retrieval of media fragments from Kinesis Video Streams, allowing applications to pull continuous or on-demand video and audio data from cloud-hosted streams. This API is particularly powerful for enterprises and organizations dealing with large volumes of real-time or archival media content originating from cameras, microphones, drones, and other media-producing devices. Typical use cases span security and surveillance systems where footage must be accessed and analyzed on demand, media broadcasting platforms that require low-latency stream retrieval, healthcare applications involving remote patient monitoring video feeds, industrial inspection systems where drones capture inspection footage, and smart city infrastructure that processes live feeds from traffic and public safety cameras. By abstracting the complexity of managing massive media storage and delivery, Kinesis Video Streams Media allows developers to focus on building application logic rather than infrastructure.

Design & CreativeConfigure →

Amazon Kinesis Video Streams Archived Media MCP Setup

The Amazon Kinesis Video Streams Archived Media API is a specialized service provided by Amazon Web Services (AWS) that enables programmatic access to retrieve and transform archived video and audio streams stored within Kinesis Video Streams. Its core capabilities center on on-demand data extraction, allowing users to pull specific clips, generate adaptive streaming manifests (HLS and DASH), extract individual image frames, and query the underlying fragment metadata of archived streams. This API is fundamental for enterprises that need to analyze historical video footage, such as for security and surveillance retrospectives, media asset management, industrial IoT inspection, and smart city analytics. Typical use cases include forensic investigation where an operator needs a precise clip of an incident, content creators repurposing raw footage from cloud-based cameras, or automated systems pulling frames for machine learning model training and validation. It serves as the critical data plane for unlocking the value of video data stored in the cloud.

Design & CreativeConfigure →

Amazon Kinesis Video Signaling Channels MCP Setup

The Amazon Kinesis Video Signaling Channels API, provided by Amazon Web Services (AWS) as an integral component of its Kinesis Video Streams service, acts as a critical infrastructure layer for establishing and managing real-time peer-to-peer connections using the WebRTC protocol. This managed signaling service abstracts the inherent complexity of peer discovery, NAT traversal, and session negotiation. Its core capabilities are exposed through two primary endpoints: POST /v1/get-ice-server-config, which provides developers with a list of ICE (Interactive Connectivity Establishment) servers, including STUN and TURN configurations, essential for establishing connections across restrictive networks; and POST /v1/send-alexa-offer-to-master, which facilitates the transmission of a WebRTC SDP (Session Description Protocol) offer to a designated master node in a master-viewer architecture. Enterprise use cases are vast, ranging from building scalable, low-latency video streaming solutions for security and monitoring systems, enabling real-time audio/video communication in telehealth or remote assistance platforms, and powering interactive live sports or event streaming where direct peer connections are paramount. For consumers, this API underpins the connectivity of smart home devices like video doorbells and baby monitors to companion apps, ensuring reliable, real-time interaction.

Design & CreativeConfigure →