// MCP TOOL REFERENCE

AZURE AI AGENT SERVICE MCP SERVER TOOLS

28 tools from the Azure AI Agent Service MCP Server MCP Server, categorised by risk level.

View the Azure AI Agent Service MCP Server policy →

// ALL 28 AZURE AI AGENT SERVICE MCP SERVER TOOLS

READ 18 tools

Read fetch_finetuning_status Fetches the status of a fine-tuning job using Azure OpenAI API. Parameters: - job_id: The ID of t... Read format_evaluation_report Format evaluation results into a readable report with metrics and Studio URL. Parameters: - evalua... Read get_agent_evaluator_requirements Get the required input fields for a specific agent evaluator or all agent evaluators. Parameters: ... Read get_finetuning_job_events MCP-compatible function to retrieve all events for a specific finetuning job. It also returns the billi... Read get_finetuning_metrics Retrieves fine-tuning metrics if the job has succeeded. Calls fetch_finetuning_status to confirm job co... Read get_model_details_and_code_samples Retrieves detailed information for a specific model from the Azure AI Foundry catalog. This function i... Read get_model_quotas Get model quotas for a specific Azure location. Args: subscription_id: The ID of the Azure sub... Read get_prototyping_instructions_for_github_and_labs Provides comprehensive instructions and setup guidance for starting to work with models from Azure AI Found... Read get_text_evaluator_requirements Get the required input fields for a specific text evaluator or all text evaluators. Parameters: - ... Read list_agent_evaluators Returns a list of available agent evaluator names for evaluating agent behaviors. Read list_agents List available agents in the Azure AI Agent Service. Read list_azure_ai_foundry_labs_projects Retrieves a list of state-of-the-art AI models from Microsoft Research available in Azure AI Foundry Labs. ... Read list_deployments_from_azure_ai_services Retrieves a list of deployments from Azure AI Services. This function is used when a user requests inf... Read list_dynamic_swagger_tools list_dynamic_swagger_tools Read list_finetuning_files list_finetuning_files Read list_finetuning_jobs MCP-compatible function to list all finetuning jobs using Azure OpenAI API. Returns: List o... Read list_models_from_model_catalog Retrieves a list of supported models from the Azure AI Foundry catalog. This function is useful when a... Read list_text_evaluators Returns a list of available text evaluator names for evaluating text outputs.

WRITE 3 tools

Write create_azure_ai_services_account create_azure_ai_services_account Write create_foundry_project create_foundry_project Write update_model_deployment update_model_deployment

EXECUTE 7 tools

Execute deploy_model_on_ai_services deploy_model_on_ai_services Execute execute_dynamic_swagger_action Execute a dynamically generated tool from the Swagger specification. Args: tool_name: Name... Execute run_agent_eval Run agent evaluation on agent data. Accepts both plain text and JSON strings. Parameters: - evalua... Execute run_text_eval run_text_eval Execute agent_query_and_evaluate Query an agent and evaluate its response in a single operation. Parameters: - agent_id: ID of the ... Execute query_default_agent Send a query to the default configured Azure AI Agent. Parameters: - query: Text query to send to ... Execute connect_agent Connect to a specific Azure AI Agent and run a query. Parameters: - agent_id: ID of the agent to c...

// FAQ

How many tools does the Azure AI Agent Service MCP Server MCP server have? +

The Azure AI Agent Service MCP Server MCP server exposes 28 tools across 3 categories: Read, Write, Execute.

How do I enforce policies on Azure AI Agent Service MCP Server tools? +

Route the Azure AI Agent Service MCP Server server through the PolicyLayer gateway. Define allow, deny, or approval rules per tool in the dashboard; they are enforced on every call before it reaches the server.

What risk categories do Azure AI Agent Service MCP Server tools fall into? +

Azure AI Agent Service MCP Server tools are categorised as Read (18), Write (3), Execute (7). Each category has a recommended default policy.

Enforce policy on every Azure AI Agent Service MCP Server tool call.

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