danielscholl/agile-team-mcp-server

prompt_tool

Send a text prompt to multiple LLM models and return their responses.

Args: text: The prompt text to send to the models models_prefixed_by_provider: List of models in format "provider:model" (e.g., "openai:gpt-4"). If None, defaults to ["openai:gpt-4o-mini"]

Returns: List of responses, one from each specified model

prompt_from_file_tool

Read a prompt from a file and send it to multiple LLM models.

Args: file_path: Path to the file containing the prompt text models_prefixed_by_provider: List of models in format "provider:model" (e.g., "openai:gpt-4"). If None, defaults to ["openai:gpt-4o-mini"]

Returns: List of responses, one from each specified model

prompt_from_file2file_tool

Read a prompt from a file, send it to multiple LLM models, and write responses to files.

Args: file_path: Path to the file containing the prompt text models_prefixed_by_provider: List of models in format "provider:model" (e.g., "openai:gpt-4"). If None, defaults to ["openai:gpt-4o-mini"] output_dir: Directory where response files should be saved (defaults to input file's directory/responses) output_extension: File extension for output files (e.g., 'py', 'txt', 'md') If None, defaults to 'md' (default: None) output_path: Optional full output path with filename. If provided, the extension from this path will be used (overrides output_extension).

Returns: List of file paths where responses were written

list_providers_tool

List all supported LLM providers.

Returns: Dictionary with main providers and their shortcuts clearly formatted

list_models_tool

List all available models for a specific provider.

Args: provider: The provider to list models for (e.g., "openai", "anthropic")

Returns: List of model names available for the specified provider

persona_dm_tool

Generate responses from multiple LLM models and use a decision maker model to choose the best direction.

This tool first sends a prompt from a file to multiple models, then uses a designated decision maker model to evaluate all responses and provide a final decision.

Args: from_file: Path to the file containing the prompt text models_prefixed_by_provider: List of team member models in format "provider:model" (if None, defaults to ["openai:gpt-4.1", "anthropic:claude-3-7-sonnet", "gemini:gemini-2.5-pro"]) output_dir: Directory where response files should be saved (defaults to input file's directory/responses) output_extension: File extension for output files (e.g., 'py', 'txt', 'md') output_path: Optional full output path with filename for the persona document persona_dm_model: Model to use for making the decision (defaults to DEFAULT_DECISION_MAKER_MODEL) persona_prompt: Custom persona prompt template (if None, uses the default)

Returns: Path to the persona output file

persona_ba_tool

Generate business analysis using a specialized Business Analyst persona, with optional decision making.

This tool uses a specialized Business Analyst prompt to analyze business requirements from a file. It can either use a single model or leverage the team decision-making functionality to get multiple perspectives and consolidate them.

Args: from_file: Path to the file containing the business requirements models_prefixed_by_provider: List of models in format "provider:model" (if None, defaults to DEFAULT_MODEL) output_dir: Directory where response files should be saved (defaults to input file's directory/responses) output_extension: File extension for output files (e.g., 'py', 'txt', 'md') output_path: Optional full output path with filename for the output document use_decision_maker: Whether to use the decision maker functionality decision_maker_models: Models to use if use_decision_maker is True (if None, defaults to DEFAULT_TEAM_MODELS) ba_prompt: Custom business analyst prompt template decision_maker_model: Model to use for decision making (defaults to DEFAULT_DECISION_MAKER_MODEL) decision_maker_prompt: Custom persona prompt template for decision making

Returns: Path to the business analysis output file

persona_pm_tool

Generate product management plans using a specialized Product Manager persona, with optional decision making.

This tool uses a specialized Product Manager prompt to create comprehensive product plans from a file. It can either use a single model or leverage the team decision-making functionality to get multiple perspectives and consolidate them.

Args: from_file: Path to the file containing the product requirements models_prefixed_by_provider: List of models in format "provider:model" (if None, defaults to DEFAULT_MODEL) output_dir: Directory where response files should be saved (defaults to input file's directory/responses) output_extension: File extension for output files (e.g., 'py', 'txt', 'md') output_path: Optional full output path with filename for the output document use_decision_maker: Whether to use the decision maker functionality decision_maker_models: Models to use if use_decision_maker is True (if None, defaults to DEFAULT_TEAM_MODELS) pm_prompt: Custom product manager prompt template decision_maker_model: Model to use for decision making (defaults to DEFAULT_DECISION_MAKER_MODEL) decision_maker_prompt: Custom persona prompt template for decision making

Returns: Path to the product plan output file

persona_sw_tool

Generate specification documents using a specialized Spec Writer persona, with optional decision making.

This tool uses a specialized Spec Writer prompt to create comprehensive specification documents from a file. It can either use a single model or leverage the team decision-making functionality to get multiple perspectives and consolidate them.

Args: from_file: Path to the file containing the requirements or PRD models_prefixed_by_provider: List of models in format "provider:model" (if None, defaults to DEFAULT_MODEL) output_dir: Directory where response files should be saved (defaults to input file's directory/responses) output_extension: File extension for output files (e.g., 'py', 'txt', 'md') output_path: Optional full output path with filename for the output document use_decision_maker: Whether to use the decision maker functionality decision_maker_models: Models to use if use_decision_maker is True (if None, defaults to DEFAULT_TEAM_MODELS) sw_prompt: Custom spec writer prompt template decision_maker_model: Model to use for decision making (defaults to DEFAULT_DECISION_MAKER_MODEL) decision_maker_prompt: Custom persona prompt template for decision making

Returns: Path to the specification output file