Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MCP Local File Reader read the contents of the document project_proposal.pdf"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
A Model Context Protocol (MCP) server that provides comprehensive file system operations with support for multiple document formats. Works with Claude Desktop and other MCP-compatible AI tools.
📁 File System Operations: List directories, read files, get file metadata
🔍 Search Capabilities: Grep-like content search and file name pattern matching
📄 Multi-Format Support:
PDF text extraction
Excel (.xlsx, .xls) with sheet listing and per-sheet reading
Word documents (.docx)
PowerPoint presentations (.pptx)
CSV files
Text files with automatic encoding detection (Shift-JIS/UTF-8)
🌐 Character Encoding: Automatic detection and conversion of Shift-JIS and UTF-8
🔒 Security: Path validation to prevent access outside designated root directory
Related MCP server: MCP File Browser Server
No installation needed! Just configure Claude Desktop to use npx:
{
"mcpServers": {
"localfile-reader": {
"command": "npx",
"args": [
"-y",
"github:yryuu/mcp-localfile-all-read"
],
"env": {
"MCP_ROOT_PATH": "/path/to/your/directory"
}
}
}
}npx github:yryuu/mcp-localfile-all-readEdit your Claude Desktop configuration file:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
Add the server configuration:
{
"mcpServers": {
"localfile-reader": {
"command": "npx",
"args": ["-y", "github:yryuu/mcp-localfile-all-read"],
"env": {
"MCP_ROOT_PATH": "/Users/yourname/Documents"
}
}
}
}Or if installed globally:
{
"mcpServers": {
"localfile-reader": {
"command": "mcp-localfile-reader",
"env": {
"MCP_ROOT_PATH": "/Users/yourname/Documents"
}
}
}
}MCP_ROOT_PATH: Root directory for file access (defaults to current working directory)
Windows Example:
{
"env": {
"MCP_ROOT_PATH": "C:\\Users\\YourName\\Documents"
}
}macOS/Linux Example:
{
"env": {
"MCP_ROOT_PATH": "/Users/yourname/Documents"
}
}Note: On Windows, use double backslashes (
\\) or forward slashes (/) in paths. See WINDOWS.md for detailed Windows compatibility information.
list_directoryList contents of a directory.
Parameters:
path (string): Relative path from root directory. Use "." for root.
Example:
List the contents of the current directoryread_fileRead file content with automatic format detection.
Parameters:
path (string): Relative path to the file.
Supported formats:
Text files (.txt, .md, .json, .xml, etc.)
PDF (.pdf)
Excel (.xlsx, .xls)
Word (.docx)
PowerPoint (.pptx)
CSV (.csv)
Example:
Read the contents of report.pdfget_file_infoGet metadata about a file or directory.
Parameters:
path (string): Relative path to the file or directory.
Example:
Get information about data.xlsxsearch_contentSearch for text patterns in files. Returns a list of file paths that contain the pattern.
Parameters:
path (string): Relative path to search in.
pattern (string): Text pattern or regex to search for.
max_results (number): Optional. Maximum number of files to return (default: 1000).
file_pattern (string, optional): Filter files by name pattern.
case_sensitive (boolean, optional): Case sensitive search. Default: false.
Example:
Search for "TODO" in all JavaScript filesfind_filesFind files by name pattern.
Parameters:
path (string): Relative path to search in.
name_pattern (string): File name pattern or regex.
case_sensitive (boolean, optional): Case sensitive search. Default: false.
Example:
Find all PDF files in the current directorylist_excel_sheetsList all sheet names in an Excel file.
Parameters:
path (string): Relative path to the Excel file.
Example:
List all sheets in budget.xlsxread_excel_sheetRead a specific sheet from an Excel file.
Parameters:
path (string): Relative path to the Excel file.
sheet_name (string): Name of the sheet to read.
Example:
Read the "Sales" sheet from budget.xlsxgit clone https://github.com/yryuu/mcp-localfile-all-read.git
cd mcp-localfile-all-read
npm installnpm run buildUse the MCP Inspector to test the server:
npx @modelcontextprotocol/inspector node dist/index.jsOr set the root path:
MCP_ROOT_PATH=/path/to/test/directory npx @modelcontextprotocol/inspector node dist/index.jsAfter configuration, you can ask Claude:
"List all files in the current directory"
"Read the contents of report.pdf"
"Search for 'error' in all log files"
"Find all Excel files"
"List the sheets in budget.xlsx and read the Sales sheet"
"Read the Word document proposal.docx"
import { Server } from '@modelcontextprotocol/sdk/server/index.js';
// The server runs on stdio transport
// See src/index.ts for implementation detailsExtracts all text content from PDF files
Handles multi-page documents
Uses pdf-parse library
Supports .xlsx and .xls formats
List all sheet names
Read specific sheets or all sheets
Returns data as JSON arrays
Supports .docx format
Extracts plain text content
Uses mammoth library
Supports .pptx format
Extracts text from all slides
Returns slide-by-slide content
Automatic delimiter detection
Character encoding detection (Shift-JIS/UTF-8)
Returns structured JSON data
Automatic character encoding detection
Supports Shift-JIS and UTF-8
Handles various text-based formats
Path validation prevents access outside the configured root directory
All paths are resolved and validated before file operations
Error handling for permission issues and invalid paths
MIT
Contributions are welcome! Please feel free to submit a Pull Request.
yryuu
Find files by name pattern. Returns list of matching file paths. Recursively searches all subdirectories by default.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Relative path to search in. Use "." for root directory. | |
| name_pattern | Yes | Regex pattern to match file names. IMPORTANT: Use regex syntax, not glob. Examples: ".*\.pdf$" for PDF files, "^report.*" for files starting with "report", ".*\.(jpg|png)$" for images. Do NOT use "*" alone. | |
| case_sensitive | No | Whether search should be case sensitive. Default: false. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the recursive search behavior and output format ('list of matching file paths'), which is useful. However, it lacks details on permissions, rate limits, error handling, or pagination, leaving gaps for a tool that performs file system operations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose, followed by output details and a key behavioral trait (recursive search). It uses three concise sentences with zero wasted words, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description provides basic purpose and behavior but is incomplete. It doesn't cover error cases, performance implications of recursive searches, or format of the returned list, which could be important for an AI agent to use this tool effectively in varied contexts.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all parameters. The description adds no additional parameter semantics beyond what's in the schema, such as explaining 'name_pattern' further or providing context for 'path'. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Find files by name pattern') and resource ('files'), distinguishing it from siblings like 'list_directory' (which lists all files) and 'search_content' (which searches within file contents). The mention of 'Returns list of matching file paths' further clarifies the output.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage through 'Recursively searches all subdirectories by default,' suggesting it's for deep searches, but it doesn't explicitly state when to use this tool versus alternatives like 'list_directory' (for listing without pattern matching) or 'search_content' (for content-based searches). No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get metadata about a file or directory including size, type, and modification date.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Relative path to the file or directory from root directory. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a 'Get' operation, implying read-only behavior, but doesn't clarify permissions needed, error handling, rate limits, or whether it works on both files and directories. The description adds minimal behavioral context beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose and includes key metadata attributes. There's no wasted wording, and it directly communicates the tool's function without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read operation with one parameter and no output schema, the description covers the basic purpose adequately. However, given the lack of annotations and sibling tools that might overlap, it could benefit from more context about when to use it and what metadata is returned. The description is minimally complete but leaves gaps in usage and behavioral details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the 'path' parameter fully documented. The description doesn't add any parameter-specific details beyond what the schema provides, such as path format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('metadata about a file or directory'), and lists key metadata attributes (size, type, modification date). However, it doesn't explicitly differentiate from sibling tools like 'find_files' or 'list_directory', which might also provide metadata in different contexts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'find_files' or 'list_directory'. It doesn't mention prerequisites, exclusions, or specific scenarios where this tool is preferred, leaving the agent to infer usage from the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List contents of a directory. Returns file and directory information including names, types, sizes, and modification dates.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Relative path from root directory. Use "." for root directory. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the return format (file/directory information with specific attributes) which is helpful, but doesn't address important behavioral aspects like pagination, rate limits, error conditions, permissions required, or whether it recursively lists subdirectories.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured in two sentences: the first states the core function, the second specifies the return format. Every word serves a purpose with zero waste or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with good schema coverage but no output schema, the description provides adequate context about what the tool does and what it returns. However, it lacks important behavioral details that would be expected for a directory listing tool, such as whether it includes hidden files, recursion behavior, or sorting options.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the 'path' parameter clearly documented. The description doesn't add any parameter-specific information beyond what's in the schema, so it meets the baseline of 3 where the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('List contents') and resource ('directory'), and specifies what information is returned. However, it doesn't explicitly distinguish this from sibling tools like 'find_files' or 'search_content', which might also list directory contents with different filtering approaches.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'find_files' or 'search_content'. It doesn't mention any prerequisites, exclusions, or specific contexts where this tool is preferred over its siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List all sheet names in an Excel file (.xlsx or .xls).
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Relative path to the Excel file from root directory. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but doesn't mention error handling (e.g., what happens if the file doesn't exist or isn't an Excel file), performance characteristics, or output format details. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core functionality without unnecessary words. It's appropriately sized for a simple tool and front-loads the essential information. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with one parameter and no output schema, the description is minimally adequate. It covers the basic purpose but lacks details about return values, error conditions, and behavioral context that would be helpful given the absence of annotations. The description meets minimum requirements but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'path' fully documented in the schema. The description doesn't add any parameter-specific information beyond what's already in the schema (e.g., no examples of valid paths or format requirements). Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List all sheet names') and resource ('in an Excel file'), specifying supported formats (.xlsx or .xls). It distinguishes from siblings like 'read_excel_sheet' by focusing on metadata listing rather than content reading. However, it doesn't explicitly differentiate from 'get_file_info' which might provide similar information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for Excel files only, but doesn't provide explicit guidance on when to use this tool versus alternatives like 'get_file_info' (which might list sheets) or 'list_directory' (which lists files, not sheets). No exclusions or prerequisites are mentioned, leaving usage context somewhat implied rather than clearly defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Read a specific sheet from an Excel file. Returns data as JSON.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Relative path to the Excel file from root directory. | |
| sheet_name | Yes | Name of the sheet to read. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the read operation and JSON output but fails to cover critical aspects like error handling (e.g., for invalid paths or sheet names), performance implications (e.g., for large files), or security considerations (e.g., file permissions). This leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded, consisting of just two sentences that directly convey the core functionality and output. Every word earns its place, with no redundant or vague language, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (reading Excel sheets) and the absence of annotations and output schema, the description is minimally adequate. It covers the basic purpose and output format but lacks details on behavior, error handling, and usage context. This results in a score that meets the minimum viable threshold but with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with clear documentation for both parameters ('path' and 'sheet_name'). The description adds no additional semantic details beyond what the schema provides, such as examples or constraints. However, since the schema is comprehensive, a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Read') and resource ('a specific sheet from an Excel file'), and it distinguishes the output format ('Returns data as JSON'). However, it doesn't explicitly differentiate from sibling tools like 'read_file' or 'list_excel_sheets', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'read_file' (for general file reading) or 'list_excel_sheets' (for sheet enumeration). It lacks context about prerequisites, such as file accessibility or format requirements, leaving usage decisions unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Read file content with automatic format detection. Supports text files, PDF, Excel, Word, PowerPoint, and CSV with automatic encoding detection (Shift-JIS/UTF-8).
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Relative path to the file from root directory. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context about automatic format and encoding detection, which goes beyond the basic 'read' action. However, it doesn't cover other behavioral traits like error handling (e.g., for unsupported formats), performance considerations, or output format details, leaving gaps in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose ('Read file content with automatic format detection') and efficiently lists supported formats and encoding detection in a single, well-structured sentence. Every element adds value without redundancy, making it appropriately sized and zero waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (reading various file types) and no annotations or output schema, the description is adequate but incomplete. It covers what the tool does and supported formats, but lacks details on return values (e.g., content format, errors) and behavioral nuances. This leaves gaps for an agent to fully understand the tool's operation in context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the 'path' parameter clearly documented. The description adds no additional meaning beyond what the schema provides, as it doesn't elaborate on parameter usage or constraints. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't need to given the schema's completeness.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Read file content') and resource ('file'), distinguishing it from siblings like 'find_files' (searching), 'get_file_info' (metadata), and 'list_directory' (listing). It specifies the core functionality with format detection, making the purpose explicit and distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by listing supported formats (text, PDF, Excel, etc.), suggesting it's for reading content from those file types. However, it lacks explicit guidance on when to use this tool versus alternatives like 'read_excel_sheet' (specific to Excel) or 'search_content' (searching within files), providing only implied context without clear exclusions or named alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search for text pattern in files (grep-like functionality). Returns list of unique file paths containing the pattern. Recursively searches all subdirectories by default. Automatically skips node_modules, .git, dist, build directories and binary files for performance.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Relative path to search in. Use "." for root directory. | |
| pattern | Yes | Text pattern or regex to search for. | |
| file_pattern | No | Optional: Regex pattern to filter files by name. IMPORTANT: Use regex syntax, not glob. Examples: ".*\.txt$" for .txt files, ".*\.xlsx?$" for Excel files, ".*\.(js|ts)$" for JS/TS files. To search ALL files, OMIT this parameter entirely (do not use "*" or ".*"). | |
| case_sensitive | No | Whether search should be case sensitive. Default: false. | |
| max_results | No | Optional: Maximum number of results to return. Default: 1000. Use lower values for faster searches in large codebases. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does well by disclosing key behavioral traits: it returns a list of unique file paths, recursively searches subdirectories by default, automatically skips certain directories and binary files for performance, and implies read-only operation. It lacks details on error handling or performance limits beyond the max_results parameter.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first sentence, followed by essential behavioral details in concise sentences. Every sentence earns its place by adding value without redundancy, making it efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (5 parameters, no output schema, no annotations), the description is largely complete: it covers purpose, behavior, and key constraints. However, it lacks explicit information on output format details (e.g., structure of the returned list) and potential errors, which could be useful for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema, such as mentioning 'grep-like functionality' which relates to the pattern parameter, but doesn't provide additional syntax or format details. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Search for text pattern in files'), the resource ('files'), and distinguishes it from siblings by mentioning 'grep-like functionality' and returning 'unique file paths containing the pattern', which differentiates it from tools like find_files or list_directory that don't search content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool (searching text patterns recursively) and implicitly contrasts with siblings by specifying its unique functionality. However, it doesn't explicitly name alternatives or state when not to use it, such as for file metadata searches versus content searches.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Most tools have distinct purposes, but there is some overlap between find_files and search_content, as both involve searching files, which could cause minor confusion. However, their descriptions clarify that find_files searches by name pattern while search_content searches by text pattern, helping to differentiate them.
All tool names follow a consistent verb_noun pattern (e.g., find_files, get_file_info, list_directory), with no deviations in style or convention. This predictability makes the tool set easy to navigate and understand.
With 7 tools, the count is well-scoped for a local file reader server, covering essential operations like listing, reading, and searching files. Each tool serves a clear purpose without redundancy, making the set appropriately sized for the domain.
The tool set covers core file operations including listing, reading, and searching, with good support for various file formats. A minor gap is the lack of write or update operations, but this is reasonable for a read-focused server, and agents can still perform common workflows without dead ends.
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Securely search and manage workspace context files for AI agents and teams.
Manage files and folders directly from your workspace. Read and write files, list directories, cre…
Search, fetch (with provenance), scan, and convert AI instruction files for agents.
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