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text_file_read_and_refactor_mcp

text_file_read_and_refactor_mcp

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text_file_read_and_refactor_mcp MCP server

Text File Read And Refactor MCP

Token-efficient Python stdio MCP server exposing safe text-file search, reading, and refactoring tools. Tools automatically resolve the file BOM and codepage; edit tools save files with their original encoding and BOM.

Glama.AI

text_file_read_and_refactor_mcp MCP server

Github repository

Github repository is a curated public mirror of the project. Active development (including experimental code and private research notes) happens in a private repository; selected snapshots are published here periodically.

Installation

  1. Install uv: https://docs.astral.sh/uv/getting-started/installation/

  2. Configure your MCP client to run the server via uvx:

{
  "mcpServers": {
    "text-file-read-and-refactor": {
      "command": "uvx",
      "args": [
        "text-file-read-and-refactor-mcp"
      ]
    }
  }
}

Related MCP server: MCP File Context Server

Tools

Slice concept: an analog of the slice(start: integer, stop: integer) - stores the start and end indices of a range.

Boundary concept: an analog of the Boundary(text: string, type: Enum[text, word, dev_word, regex])

Span concept: an analog of the Span(left_boundary: Boundary, right_boundary: Boundary). It allows for search/replace operations such as give me the text between "my_config_param:" and ";" or replace the text between "%my_regex_1%" and "%my_regex_2%" with "my_text".

Read-only tools:

  • text_file__list_allowed_directories - in pseudocode: "text_file__list_allowed_directories() -> List[directory_path]"

  • text_file__file_content_length - in pseudocode: "text_file__file_content_length() -> integer_characters_num"

  • text_file__read_slice - in pseudocode: "text_file__read_slice(characters_slice) -> text"

  • text_file__file_lines_num - in pseudocode: "text_file__file_lines_num() -> integer_lines_num"

  • text_file__read_content_by_line_range - in pseudocode: "text_file__read_content_by_line_range(lines_slice) -> text"

  • text_file__find_text - in pseudocode: "text_file__find_text(text, type: Enum[text, word, dev_word, regex]) -> {found, result?: {slice, lines, text}}"

  • text_file__find_all_text_occurrences - in pseudocode: "text_file__find_all_text_occurrences(text, type: Enum[text, word, dev_word, regex], result_index_start, result_index_stop) -> List[{found, result: {slice, lines, text}}]"

  • text_file__expand_slice_to_lines - in pseudocode: "text_file__expand_slice_to_lines(characters_slice) -> lines_slice"

  • text_file__find_span_boundaries - in pseudocode: "text_file__find_span_boundaries(left_boundary, right_boundary) -> Tuple[left_boundary_characters_slice, right_boundary_characters_slice]"

  • text_file__find_span_between_boundaries - in pseudocode: "text_file__find_span_between_boundaries(left_boundary, right_boundary) -> text". Example: text_file__find_span_between_boundaries("my_config_param:", ";") will return string " my_value".

  • text_file__find_span_with_boundaries - in pseudocode: "text_file__find_span_with_boundaries(left_boundary, right_boundary) -> text". Example: text_file__find_span_with_boundaries("my_config_param:", ";") will return string "my_config_param: my_value;".

Edit tools:

  • text_file__replace_content_by_line_range - in pseudocode: "text_file__replace_content_by_line_range(text, lines_slice)"

  • text_file__replace_slice - in pseudocode: "text_file__replace_slice(text, characters_slice)"

  • text_file__replace_text - in pseudocode: "text_file__replace_slice(old_text, new_text)"

  • text_file__replace_span_between_boundaries - in pseudocode: "text_file__replace_span_between_boundaries(text, left_boundary, right_boundary)".

  • text_file__replace_span_with_boundaries - in pseudocode: "text_file__replace_span_with_boundaries(text, left_boundary, right_boundary)".

  • text_file__patch_spans_by_boundary_patterns - in pseudocode: "text_file__patch_spans_by_boundary_patterns(List[Tuple[text, left_boundary, right_boundary]])".

Cengal

Based on Cengal

Projects using Cengal

  • InterProcessPyObjects - High-performance package delivers blazing-fast inter-process communication through shared memory, enabling Python objects to be shared across processes with exceptional efficiency.

  • cengal_app_dir_path_finder - A Python module offering a unified API for easy retrieval of OS-specific application directories, enhancing data management across Windows, Linux, and macOS

  • cengal_cpu_info - Extended, cached CPU info with consistent output format.

  • cengal_memory_barriers - Fast cross-platform memory barriers for Python.

  • flet_async - wrapper which makes Flet async and brings booth Cengal.coroutines and asyncio to Flet (Flutter based UI)

  • justpy_containers - wrapper around JustPy in order to bring more security and more production-needed features to JustPy (VueJS based UI)

  • Bensbach - decompiler from Unreal Engine 3 bytecode to a Lisp-like script and compiler back to Unreal Engine 3 bytecode. Made for a game modding purposes

  • Realistic-Damage-Model-mod-for-Long-War - Mod for both the original XCOM:EW and the mod Long War. Was made with a Bensbach, which was made with Cengal

  • SmartCATaloguer.com - TagDB based catalog of images (tags), music albums (genre tags) and apps (categories)

License

Copyright © 2026 ButenkoMS. All rights reserved.

Licensed under the Apache License, Version 2.0.

Available Tools

16 tools
text_file__expand_slice_to_linesA

Opens the text file, automatically resolving the BOM and codepage. Expands a character slice to cover complete lines and returns both the expanded character slice and selected line-number slice. Provide slices as JSON objects matching Python slice(start, stop, step); omit fields for None, and never use step 0. Token-efficient: targets specific file content or returns compact structured results to reduce unnecessary context.

Inputs: place (required), source_file_path (required).

text_file__file_content_lengthA

Opens the text file, automatically resolving the BOM and codepage. Returns the number of characters in the decoded file content. Token-efficient: targets specific file content or returns compact structured results to reduce unnecessary context.

Inputs: source_file_path (required).

text_file__file_lines_numA

Opens the text file, automatically resolving the BOM and codepage. Returns the number of lines in the decoded file content. Token-efficient: targets specific file content or returns compact structured results to reduce unnecessary context.

Inputs: source_file_path (required).

text_file__find_span_between_boundariesB

Opens the text file, automatically resolving the BOM and codepage. Finds content between matching boundary markers described by the boundary_span object and returns the inner slice, or null if not found. Token-efficient: targets specific file content or returns compact structured results to reduce unnecessary context.

Inputs: boundary_span (required), source_file_path (required), stop, start, +2 more.

text_file__find_span_boundariesA

Opens the text file, automatically resolving the BOM and codepage. Finds matching left and right boundary markers described by the boundary_span object and returns their slices. Token-efficient: targets specific file content or returns compact structured results to reduce unnecessary context.

Inputs: boundary_span (required), source_file_path (required), stop, start, +2 more.

text_file__find_span_with_boundariesB

Opens the text file, automatically resolving the BOM and codepage. Finds content plus its surrounding matching boundary markers and returns the full slice, or null if not found. Token-efficient: targets specific file content or returns compact structured results to reduce unnecessary context.

Inputs: boundary_span (required), source_file_path (required), stop, start, +2 more.

text_file__find_textA

Opens the text file, automatically resolving the BOM and codepage. Finds the first or last exact text, whole-word, or identifier-style word match within optional start/stop character offsets and returns its slice, or null if not found. Token-efficient: targets specific file content or returns compact structured results to reduce unnecessary context.

Inputs: text (required), source_file_path (required), stop, type, +7 more.

text_file__list_allowed_directoriesA

Returns the filesystem directories this server is allowed to access. File paths used by other tools must be inside one of these directories. Token-efficient: targets specific file content or returns compact structured results to reduce unnecessary context.

Inputs: no named parameters.

text_file__patch_spans_by_boundary_patternsB

Opens the text file, automatically resolving the BOM and codepage. Applies one boundary-span replacement or an ordered list of boundary-span replacements, then writes the modified content back. Token-efficient: targets specific file content or returns compact structured results to reduce unnecessary context. The file is saved with its original encoding and BOM.

Inputs: source_file_path (required), text, count, patch, +1 more.

text_file__read_content_by_line_rangeA

Opens the text file, automatically resolving the BOM and codepage. Reads complete lines selected by a Python-style line-number slice. Provide slices as JSON objects matching Python slice(start, stop, step); omit fields for None, and never use step 0. Token-efficient: targets specific file content or returns compact structured results to reduce unnecessary context.

Inputs: line_range (required), source_file_path (required).

text_file__read_sliceA

Opens the text file, automatically resolving the BOM and codepage. Allows you to read any section of the file content (or the entire content) using Python-style slicing. Provide slices as JSON objects matching Python slice(start, stop, step); omit fields for None, and never use step 0. Token-efficient: targets specific file content or returns compact structured results to reduce unnecessary context.

Inputs: slice (required), source_file_path (required).

text_file__replace_content_by_line_rangeA

Opens the text file, automatically resolving the BOM and codepage. Replaces complete lines selected by a Python-style line-number slice, then writes the modified content back. Provide slices as JSON objects matching Python slice(start, stop, step); omit fields for None, and never use step 0. Token-efficient: targets specific file content or returns compact structured results to reduce unnecessary context. The file is saved with its original encoding and BOM.

Inputs: text (required), line_range (required), source_file_path (required).

text_file__replace_sliceA

Opens the text file, automatically resolving the BOM and codepage. Replaces the content selected by a Python-style character slice, then writes the modified content back. Provide slices as JSON objects matching Python slice(start, stop, step); omit fields for None, and never use step 0. Token-efficient: targets specific file content or returns compact structured results to reduce unnecessary context. The file is saved with its original encoding and BOM.

Inputs: text (required), place (required), source_file_path (required).

text_file__replace_span_between_boundariesA

Opens the text file, automatically resolving the BOM and codepage. Replaces only the content between matching boundary markers, preserves the boundary markers, then writes the modified content back. Token-efficient: targets specific file content or returns compact structured results to reduce unnecessary context. The file is saved with its original encoding and BOM.

Inputs: text (required), boundary_span (required), source_file_path (required), count.

text_file__replace_span_with_boundariesB

Opens the text file, automatically resolving the BOM and codepage. Replaces matching boundary markers together with the content between them, then writes the modified content back. Token-efficient: targets specific file content or returns compact structured results to reduce unnecessary context. The file is saved with its original encoding and BOM.

Inputs: text (required), boundary_span (required), source_file_path (required), count.

text_file__replace_textA

Opens the text file, automatically resolving the BOM and codepage. Replaces exact substring, whole-word, or identifier-style word matches within optional start/stop character offsets, then writes the modified content back. Token-efficient: targets specific file content or returns compact structured results to reduce unnecessary context. The file is saved with its original encoding and BOM.

Inputs: new_text (required), old_text (required), source_file_path (required), stop, +8 more.

Tool Schema Changelog

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    Deploy Server
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    TDQS

    A3.8/5.0

    Scored across 16 tools

    Disambiguation4/5

    Most tools have distinct purposes, but some pairs like find_span_between_boundaries and find_span_with_boundaries could be confused. Descriptions help disambiguate.

    Naming Consistency5/5

    All tools follow a consistent `text_file__verb_phrase` pattern with snake_case, making the naming predictable and uniform.

    Tool Count5/5

    With 16 tools, the set is well-scoped for reading and refactoring text files, covering various operations without being overwhelming.

    Completeness4/5

    Core operations like reading, finding, and replacing are covered. However, missing tools for creating or deleting files limit full lifecycle management.

    Maintenance

    ActivityNo data
    ResponsivenessOutdated data

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