Hanzo MCP enables AI assistants to interact with codebases through tools for file operations, command execution, project analysis, and Jupyter notebook management. Built with Python and FastMCP, it provides secure access to local files and commands through a permission system that validates paths and operations. The implementation is designed for developers who want to use Claude for code understanding, modification, and project management tasks while maintaining security through explicit path allowlisting and operation validation.
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Highlight AIFile system operations. Takes an 'action' argument to specify the operation.
Execute shell commands. Takes an 'action' argument to specify the operation.
Code-related operations. Takes an 'action' argument to specify the operation.
Git-related operations. Takes an 'action' argument to specify the operation.
Fetch resources over HTTP. Takes an 'action' argument to specify the operation.
Workspace-related operations. Takes an 'action' argument to specify the operation.
UI operations. Takes a 'method' argument to specify the UI action.
Optional tool for decision-making tasks. Takes an 'action' argument to specify the operation.
Optional tool for memory-related operations. Takes an 'action' argument to specify the operation.
Access Hanzo Cloud subsystems. Requires 'resource' and 'action' arguments.
Optional tool for planning tasks. Takes an 'action' argument to specify the operation.
Optional tool for task-related operations. Takes an 'action' argument to specify the operation.
Search for code within the repository. Calls the Hanzo API.
Retrieve context about code. Calls the Hanzo API.
Ask questions about the code. Calls the Hanzo API.
Index code for better retrieval. Calls the Hanzo API.
Manage tracker boards. Calls the Hanzo API.
Manage tracker issues. Calls the Hanzo API.
Create new tracker items. Calls the Hanzo API.
Update existing tracker items. Calls the Hanzo API.
Ask Kai for a decision based on the provided input.
Choose a label based on the provided criteria.
Get an ordinal score based on the provided input.
Determine the probability of a statement holding true.
Select a named tool based on the context.
Determine the next action based on predefined conditions.
Control the execution of commands based on rules.
Utilize rules and Kai's planted capability for decision-making.
Extract typed fields from input.
Analyze failure signatures for decision-making.
Handle failure scenarios by breaking loops and processing failures.
Step through agent actions based on Kai's logic.
