Renamify

Intelligently renames code symbols (variables, functions, classes) across a codebase while automatically transforming the name across all detected naming conventions (camelCase, snake_case, PascalCase, SCREAMING_SNAKE_CASE). The system analyzes identifier usage patterns to determine which convention applies in each context, then applies the transformation consistently. For example, renaming 'user_name' to 'account_id' automatically generates 'userName' in camelCase contexts and 'USER_NAME' in constant contexts.

Renames files and directories in a codebase with built-in conflict detection and atomic transaction semantics — all changes succeed or none are applied. The system scans for references to the old file/directory name across the codebase (imports, requires, relative paths, configuration files) and updates them in a single atomic operation. If conflicts are detected (e.g., target name already exists, circular references), the entire operation is rejected before any changes are written.

Searches for identifiers (variables, functions, classes, file names) across the entire codebase using pattern matching that understands code structure. The search tool can locate all occurrences of a symbol, filter by context (e.g., function definitions vs. usages), and return results with file paths, line numbers, and surrounding code context. This enables AI assistants to understand the scope and impact of a rename operation before planning it.

Creates a detailed execution plan for a rename operation before applying it, showing exactly which files will be modified, which lines will change, and how case transformations will be applied. The plan includes a preview of the changes in multiple formats (diff, side-by-side, summary) so AI assistants and developers can review the impact before execution. The plan object can then be passed to the apply tool to execute all changes atomically.

Executes a previously-planned rename operation atomically, applying all file modifications, symbol renames, and reference updates in a single transaction. If any part of the operation fails (e.g., file write error, conflict detected), the entire operation is rolled back and no changes are persisted. The execution returns a detailed result object with the status of each modified file and any errors encountered.

Maintains a complete history of all rename and replace operations performed on the codebase, allowing unlimited undo and redo of any previous operation. Each operation is tracked with metadata (timestamp, old name, new name, files affected) and can be individually undone or redone. The history is accessible via the renamify_history tool, and undo/redo operations are themselves atomic and reversible.

Performs straightforward find-and-replace operations using regex patterns or literal strings, without applying case-aware transformations. This tool is useful for bulk replacements that don't require convention-aware logic (e.g., replacing a hardcoded string, updating a configuration value, or applying a simple regex pattern). Unlike the case-aware rename tool, this operates on exact pattern matches without analyzing naming conventions.

Exposes all Renamify capabilities as MCP (Model Context Protocol) tools that AI assistants can call directly. The MCP server runs as a Node.js process and communicates with AI assistants via the standard MCP protocol, allowing assistants to search, plan, preview, and apply rename operations without requiring manual CLI invocation. The server handles tool invocation, parameter validation, and result serialization according to MCP specifications.

Optionally integrates with Git to automatically create commits after rename operations are applied. When enabled, each rename operation can be automatically committed with a generated or custom commit message, creating an audit trail of refactoring changes. The Git integration is optional and can be configured at the MCP server level, but specific configuration options and behavior are undocumented.

Provides a status endpoint that reports the current state of the Renamify server, including any pending rename plans that have been created but not yet applied, the current operation history depth, and the state of any in-progress operations. This allows AI assistants and developers to understand what operations are pending and avoid conflicts or unexpected state changes.