Graphify-Labs/graphify
Graphify transforms codebases, documentation, and other files into queryable knowledge graphs, enhancing developer productivity with local AST parsing and detailed edge explanations.
Awesome MCP › Software Development
mcp-text-editor is a Model Context Protocol server that exposes line-based text file reading and editing through a standard API, designed so LLM tools can work on large files without loading them whole. Its central idea is partial access: a client asks for specific line ranges instead of an entire file, which keeps token consumption down, and it can request multiple ranges across multiple files in a single call. The get_text_file_contents tool accepts either a single file with line_start and line_end, or a list of files each with several ranges, plus an optional encoding; responses carry the content, the line bounds, a SHA-256 hash of the content, the total line count and the size. The patch_text_file_contents tool applies patches to one or more files, each patch giving a start line, an end line (null means end of file), the hash of the range being replaced and the replacement content. The file-level hash and per-range hashes obtained from a prior read are checked before writing, so an edit against content that has changed underneath fails with a hash mismatch error that suggests re-reading rather than overwriting. Patches are applied bottom to top so earlier edits do not shift later line numbers, and patches within a file must not overlap; line numbers are 1-based. Encodings beyond utf-8 are supported, including shift_jis and latin1, and must match between read and patch. Multi-file operations are atomic and errors are raised as typed custom errors. It runs on Python 3.11 or newer via uvx, pip or Docker, is installable through Smithery, and is documented for Claude Desktop. It fits collaborative editing and automated text processing where several processes may touch the same files.
https://github.com/tumf/mcp-text-editor
Graphify transforms codebases, documentation, and other files into queryable knowledge graphs, enhancing developer productivity with local AST parsing and detailed edge explanations.
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