Initialize the research agent with research-specific tools.

Perform competitive analysis on a company. Args: company_name: Name of the company to analyze aspects: Speci

Perform basic sentiment analysis on text. Args: text: Text to analyze Returns: Dictionary with sentiment analysis resul

Multiply two numbers together. Args: a: First number b: Second number Returns: The product of a and b

Add two numbers together. Args: a: First number b: Second number Returns: The sum of a and b

Start an interactive chat session with the agent.

Compare two datasets and highlight differences. Args: dataset1: First dataset dataset2: Second dataset

Manage configuration settings.

Context manager to connect to MCP server and get tools. This is the recommended way to use MCP tools as it properly handles

Connect to all configured MCP servers and yield combined tools. Note: This connects to servers sequentially due to the context manag

Demonstrate different agent types.

Demonstrate browser automation capabilities.

Example of code execution with the agent.

Demonstrate content creation capabilities.

Demonstrate data analysis capabilities.

Example of data analysis with the agent.

Demonstrate market research capabilities.

Example of a task using multiple tools.

Example of news analysis.

Example of conducting research with the Research Agent.

Run a simple task with the agent.

Demonstrate technical support capabilities.

Example of web scraping with the agent.

Fill and submit a form on a website. Args: url: The URL containing the form form_data: Dictionary of field n

Execute Exa search and return formatted results.

Execute Exa find_similar and return formatted results.

Execute web search and return results.

Search for news articles.

Execute Python code and return the output.

Perform data analysis.

Execute Google search with advanced parameters

Search Google Shopping with filters

Search Google Maps for local businesses

Search Google Scholar for academic content

Search multiple engines and optionally compare results

Execute the agent with the given task

Provide mock dataset information. Args: dataset_name: Name of the dataset Returns: Dataset information

Get a server configuration by name.

Provide server configuration information. Returns: Server configuration dictionary

Get the list of loaded tools (after entering context).

Get mock weather information for a city. Args: city: Name of the city Returns: Dictionary with weather information

Number of worker LLM roles in this use case.

Show MCP integration status and information.

List available MCP servers configured in environment.

Run a task using MCP tools from a server.

Test connection to an MCP server and list available tools.

Ensure cache directory exists.

List and manage available AI models.

Monitor a website for specific changes or content. Args: url: The URL to monitor check_for: What to look for

Run a task using the multi-model orchestration system.

Search and analyze news articles.

Execute complex tasks using model orchestration.

Prepare context-aware search parameters based on query and history

Conduct research on a specific topic.

Run a single task with the agent.

Search for items based on a query (mock data). Args: query: Search query limit: Maximum number of results to return Ret

Skip test if MCP is not available.

Skip test if MCP is not available.

Skip test if MCP is not available.

Skip test if MCP is not available.