YAML (YAML Ain't Markup Language) is a human-readable data serialization standard that can be used in conjunction with all programming languages and is often used for configuration files.
Why this server?
Leverages YAML for flexible configuration through configuration files, allowing customization of the time server's behavior
Why this server?
Supports loading and processing OpenAPI specifications in YAML format.
Why this server?
Enables working with document frontmatter (YAML metadata) for documentation files
Why this server?
Provides a configuration format for defining MCP tool mappings to HTTP APIs, allowing users to specify server settings and tool definitions through structured YAML files.
Why this server?
Supports parsing and handling YAML Swagger definition files to extract API information and generate compatible code.
Why this server?
Uses YAML for configuration of LLM environments, including resources, prompts, tools, and global settings.
Why this server?
Uses YAML configuration files to define tools and commands to be executed by the MCP server.
Why this server?
Supports token storage in YAML format (default), allowing credentials and authentication data to be saved and retrieved in YAML files.
Why this server?
Provides a template system for defining and managing prompt templates without coding knowledge
Why this server?
Supports OpenAPI specifications defined in YAML format
Why this server?
Supports YAML format for the server's configuration system, allowing users to provide API credentials and other settings.
Why this server?
Supports YAML as a configuration format for defining server settings, connection parameters, and authentication details.
Why this server?
Supports OpenAPI specs in YAML format
Why this server?
Supports working with Semgrep rules defined in YAML format, allowing for rule creation and management.
Why this server?
Supports returning query results in YAML format when interacting with the Cube semantic layers.
Why this server?
Uses YAML for defining extension context information, providing detailed knowledge about PostgreSQL extensions like PostGIS and pgvector.
Why this server?
Uses YAML configuration files to define custom cognitive frameworks and memory structures for the model.
Why this server?
The MCP server uses YAML configuration files for configuring txtai components during knowledge base building
Why this server?
Supports parsing and serialization of YAML for configuration and data exchange.
Why this server?
Supports structured data formatting for project management information, mentioned as an alternative format for organizing project data.
Why this server?
Allows defining prompt templates in YAML format with structured metadata, arguments, and message content.
Why this server?
Uses YAML files for configuring agents and tasks without writing custom code, supporting variable replacement in templates.
Why this server?
Used for the workspace configuration with pnpm-workspace.yaml mentioned in the project structure.
Why this server?
Processes OpenAPI schema files in YAML format and presents schema information in YAML format for better LLM comprehension.
Why this server?
The server uses YAML for Smithery configuration, defining required parameters and integration with Claude Desktop.
Why this server?
Handles compiled pipeline definitions that are stored in Google Cloud Storage and used to trigger Vertex AI training jobs.