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?
Provides support for reading and writing YAML files within permitted directories
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Allows managing tasks in YAML format, providing configuration-friendly representation for task data.
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Uses YAML frontmatter for document metadata in knowledge files, supporting properties like title and keywords for better organization
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Supports parsing of YAML-formatted OpenAPI specifications for tool generation
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Uses YAML frontmatter in Markdown files to store and manage note metadata
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Offers YAML formatting functionality for structured data
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Supports YAML format for the server's configuration system, allowing users to provide API credentials and other settings.
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Processes Swagger/OpenAPI documentation in YAML format, enabling the parsing and exploration of API definitions specified in YAML.
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Supports flexible configuration through YAML files, enabling customization of server behavior and settings.
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Supports structured metadata using YAML frontmatter in prompt files
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Validates Ilograph diagrams written in YAML syntax, providing detailed error messages and suggestions for correction.
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Leverages YAML for flexible configuration through configuration files, allowing customization of the time server's behavior
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Provides tools for working with OpenAPI specifications in YAML format, allowing splitting and extracting endpoints.
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Supports parsing and handling YAML Swagger definition files to extract API information and generate compatible code.
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Allows defining prompt templates in YAML format with structured metadata, arguments, and message content.
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Enables comparison of YAML data, generating diffs between YAML structures, and processing YAML content for difference analysis
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Supports loading and processing OpenAPI specifications in YAML format.
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Enables working with document frontmatter (YAML metadata) for documentation files
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Enables defining UI tests using YAML syntax, providing a declarative approach to creating mobile and web UI test scenarios.
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Supports parsing OpenAPI specifications in YAML format to generate mock API servers
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Analyzes YAML files for infrastructure as code misconfigurations and security vulnerabilities.
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Parses YAML frontmatter for rich metadata in IIA content, enabling advanced features like relevance scoring and standard number detection.
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Uses YAML for configuration, as indicated by the PyYAML dependency.
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Enables defining and configuring multiple API endpoints using YAML syntax, supporting various HTTP methods, parameter generation, and request configurations.
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Uses YAML frontmatter in journal entries for metadata storage and organization
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Uses YAML configuration files to manage service configurations and determine which third-party enrichment services are supported for observable lookups
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Processes and translates configuration files, enabling localization of task templates into different languages
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Supports creation of Kubernetes resources from YAML manifests, enabling deployment of complex resources through the createorUpdateResource tool.
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Supports parsing and processing of YAML-formatted Swagger/OpenAPI specifications for API client generation.
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Provides tools for validating, reading, and writing YAML-based range configurations, ensuring they comply with proper syntax and schema requirements.
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Supports OpenAPI specifications in YAML format, allowing the MCP server to process and serve API documentation from YAML files.
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Supports YAML-based configuration for specifying Signoz connection details and server settings as an alternative to environment variables.
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Format used for the OpenAPI/Swagger definition that enables integration with Microsoft Copilot Studio.
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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.
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Supports configuration through YAML files, allowing customization of the MCP server behavior
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Offers extraction and formatting of key-value pairs into YAML format with type safety and validation.
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The server uses YAML for Smithery configuration, defining required parameters and integration with Claude Desktop.
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Supports YAML as an output format for viewing OpenAPI specifications
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The MCP server uses YAML configuration files for configuring txtai components during knowledge base building
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Uses YAML configuration files to define custom cognitive frameworks and memory structures for the model.
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Supports YAML as a configuration format for defining server settings, connection parameters, and authentication details.
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Used for bridge and tool definitions through YAML files in the bridges directory
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Uses YAML files for policy definition and configuration, allowing customizable policy rules that can be enforced through the server's policy compliance tool
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Uses YAML for configuration of reasoning strategies and model orchestration settings
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Supports OpenAPI specifications defined in YAML format
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Uses YAML for configuration of LLM environments, including resources, prompts, tools, and global settings.
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Supports parsing and serialization of YAML for configuration and data exchange.
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Uses YAML for configuration files including hosts, groups, and defaults, allowing structured definition of network devices and their properties.
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Supports token storage in YAML format (default), allowing credentials and authentication data to be saved and retrieved in YAML files.
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Implements YAML-based configuration system for setup and management of the server's security controls and feature settings
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Provides a template system for defining and managing prompt templates without coding knowledge
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Uses YAML configuration files to define tools and commands to be executed by the MCP server.
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Used for the workspace configuration with pnpm-workspace.yaml mentioned in the project structure.
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Supports OpenAPI specs in YAML format
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Supports working with Semgrep rules defined in YAML format, allowing for rule creation and management.
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Supports returning query results in YAML format when interacting with the Cube semantic layers.
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Supports output formatting in YAML format as an alternative to JSON for command responses.
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Supports YAML configuration files for server setup, allowing detailed configuration of transport options, function filtering, performance settings, and more
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Used for configuration and data serialization within the weather server implementation
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Uses YAML for configuration files, including server definitions and connection settings.
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Enables management of YAML frontmatter in Markdown documents, supporting getting, setting, updating, and removing metadata
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Uses YAML for configuration through the smithery.yaml file, which defines the MCP client settings and parameter schemas.
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Used for MCP client configuration through the smithery.yaml file, which defines startup parameters and configuration schema for the Careerjet job search functionality.
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Uses YAML for configuration management of the MCP server, enabling customization of API keys, logging levels, and connection settings.
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Leverages YAML frontmatter for rich prompt metadata including categories, tags, and argument definitions
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Enables working with YAML files through conversion workflows, commonly used with static site generators like Hugo and Jekyll.
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Uses YAML for the MCP discovery file (model_context.yaml) which enables API discovery and interaction through the provided agent.
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Utilizes YAML for pretty printing Bible data responses, making the verse and chapter text more readable when returned from the API.
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Supports YAML-formatted configuration files for defining multiple Datasette instances, their connection details, and global server settings.
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Supports configuration through YAML files, allowing customization of server settings including port, host, logging level, and enabled plugins.
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Integrates with an OpenAPI YAML specification (cirro-data-latest.yml) to provide access to the Cirro Bio data platform API.
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Employs YAML configuration files to manage tool registration and server settings, allowing users to easily extend the server with additional tools.
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Connects to the PokeAPI which is defined using an OpenAPI specification in YAML format, allowing structured access to Pokémon data.
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Supports parsing OpenAPI specifications in YAML format, enabling the dynamic conversion of YAML-defined APIs into MCP tools.
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Supports structured data formatting for project management information, mentioned as an alternative format for organizing project data.
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Includes specialized loaders for YAML files, enabling proper chunking and indexing of YAML configuration documents
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Implements configuration via YAML files to determine which third-party enrichment services should be used for observable lookups
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Uses YAML for defining extension context information, providing detailed knowledge about PostgreSQL extensions like PostGIS and pgvector.
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Uses YAML files for configuring agents and tasks without writing custom code, supporting variable replacement in templates.
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Processes OpenAPI schema files in YAML format and presents schema information in YAML format for better LLM comprehension.
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Handles compiled pipeline definitions that are stored in Google Cloud Storage and used to trigger Vertex AI training jobs.