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 Smart Filesystem Server search for all async functions in the src directory"
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.
An LLM-optimized Model Context Protocol (MCP) filesystem server with intelligent features designed for effective AI agent interaction.
Automatically chunks large files (>500 lines) into manageable pieces
Simple start_line parameter for easy navigation
Clear indicators when more content is available
Prevents context overflow in LLM conversations
Lightning-fast code searching across entire codebase
Regex pattern support with helpful examples
File-specific searching (like Ctrl+F with regex)
Flexible filtering by file type, path, and more
Strict directory access control
Symlink attack prevention
Path traversal protection
Only accesses files within allowed directories
Helpful suggestions in responses
Examples for common search patterns
Reading strategy recommendations for large files
Clear error messages with actionable guidance
Related MCP server: Local Explorer MCP
List directory contents with metadata.
{
"path": "src"
}Returns: Files, directories, sizes, line counts, and summary statistics.
Read file contents with automatic pagination for large files.
{
"path": "src/large-file.ts",
"start_line": 0
}For files >500 lines, returns first 500 lines with hasMore: true and nextStartLine.
Read next chunk with start_line: 500, then 1000, etc.
Search for code patterns using ripgrep (very fast).
Examples:
Find any type declaration (class/struct/interface/enum):
{
"pattern": "\\b(class|struct|interface|enum)\\s+ServiceName\\b",
"filePattern": "*.ts"
}Find method with any access modifier:
{
"pattern": "\\b(public|private|protected).*\\s+methodName\\s*\\(",
"path": "src/directory"
}Find all async functions:
{
"pattern": "async\\s+.*\\s*\\(",
"caseInsensitive": true,
"contextLines": 3
}Options:
pattern (required): Regex pattern
path: Limit to specific directory
filePattern: File glob (e.g., *.js, *.{ts,tsx}, !*test*)
caseInsensitive: Ignore case
contextLines: Lines of context (default: 2)
maxResults: Max results (default: 50)
literalString: Treat as literal, not regex
wordBoundary: Match whole words only
Search within a specific file (like Ctrl+F with regex).
{
"path": "src/server.ts",
"pattern": "app\\.use\\(",
"contextLines": 3
}Find files by name pattern.
{
"pattern": "*Handler*.ts"
}Pattern examples:
config.json - Exact name
*.config - Wildcard
*Service* - Contains "Service"
*.{ts,tsx,js} - Multiple extensions
Get file metadata without reading contents.
{
"path": "src/large-file.ts"
}Returns: Size, line count, language, binary status, and reading strategy for large files.
Show accessible directories (security boundaries).
{}# Build image
docker build -t mcp-filesystem-smart .
# Run with workspace mounted
docker run -i --rm \
-v /path/to/your/project:/workspace:ro \
mcp-filesystem-smartThe :ro flag makes the directory read-only for extra security.
Customize behavior with environment variables:
docker run -i --rm \
-e MCP_LINES_PER_PAGE=1000 \
-e MCP_MAX_SEARCH_RESULTS=200 \
-v /path/to/your/project:/workspace:ro \
mcp-filesystem-smartAvailable Variables:
MCP_LINES_PER_PAGE - Lines per page when reading files (default: 500)
MCP_MAX_SEARCH_RESULTS - Search results per page (default: 100)
npm install
npm run build
node dist/index.js /path/to/allowed/directory{
"mcpServers": {
"filesystem-smart": {
"command": "docker",
"args": [
"run", "-i", "--rm",
"-v", "/home/user/projects/myapp:/workspace:ro",
"mcp-filesystem-smart"
]
}
}
}# Local
node dist/index.js /path/to/dir1 /path/to/dir2
# Docker (mount multiple volumes)
docker run -i --rm \
-v /path/to/dir1:/workspace1:ro \
-v /path/to/dir2:/workspace2:ro \
mcp-filesystem-smart /workspace1 /workspace2When you don't know if something is a class, struct, interface, or record:
search_code({
pattern: "\\b(class|struct|record|interface|enum)\\s+MyType\\b",
filePattern: "*.cs"
})Search for what you need: search_code(pattern="functionName")
Get file info: get_file_info(path="src/module.ts")
Read strategically: read_file(path="src/module.ts", start_line=0)
Check size: get_file_info(path="big-file.ts") → "1500 lines"
Search within: search_in_file(path="big-file.ts", pattern="export class")
Read around matches: Use line numbers from search to read specific chunks
Find files: find_files(pattern="*Service*.ts")
Search within results: search_code(pattern="constructor", path="src/services")
// Find any type
"\\b(class|struct|record|interface|enum)\\s+TypeName\\b"
// Find method
"\\b(public|private|protected|internal).*\\s+MethodName\\s*\\("
// Find async methods
"async\\s+(Task|ValueTask)<.*>\\s+\\w+\\s*\\("// Find function/method
"(function|const|let|var)\\s+\\w+\\s*=.*=>|function\\s+\\w+\\s*\\("
// Find class/interface
"(class|interface)\\s+\\w+"
// Find async functions
"async\\s+(function|\\w+\\s*=>|\\(.*\\)\\s*=>)"// Find class
"class\\s+\\w+.*:"
// Find function
"def\\s+\\w+\\s*\\("
// Find async function
"async\\s+def\\s+\\w+"Node.js: 22 or higher
ripgrep: Must be installed and available in PATH
Alpine Linux: apk add ripgrep
Ubuntu/Debian: apt install ripgrep
macOS: brew install ripgrep
Windows: choco install ripgrep
This server implements multiple security layers:
Directory Sandboxing: Only accesses files within allowed directories
Symlink Resolution: Prevents symlink attacks by checking real paths
Path Validation: Blocks path traversal attempts (../, etc.)
Read-Only Docker: Mount volumes as :ro for read-only access
# Install dependencies
npm install
# Build
npm run build
# Watch mode
npm run watch
# Test locally
node dist/index.js $(pwd)MIT
Built on top of the Model Context Protocol (MCP) SDK and ripgrep.
Find files by name using fast pattern matching.
PATTERN EXAMPLES:
Exact name: "config.json"
Wildcard: "*.config" or "Handler"
Multiple extensions: "*.{ts,tsx,js}"
TIPS:
Use * for any characters
Use ? for single character
Use {a,b,c} for alternatives
| Name | Required | Description | Default |
|---|---|---|---|
| pattern | Yes | Filename pattern. Examples: 'Component.tsx', '*.json', '*Handler*', '*.{ts,tsx}' | |
| path | No | Limit search to specific 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 mentions 'fast pattern matching' which hints at performance, but doesn't cover critical aspects like permissions needed, whether it's read-only or has side effects, rate limits, error conditions, or what the output looks like. The pattern examples are helpful but insufficient for full 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 well-structured with clear sections (purpose, examples, tips) and efficiently communicates key information. The pattern examples and tips are valuable additions. However, the 'TIPS' section could be more concise, and some information (like wildcard syntax) is somewhat redundant with the schema description.
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 2-parameter tool with no annotations and no output schema, the description provides adequate basic information about what the tool does and how to use patterns. However, it lacks important context about behavioral aspects (permissions, side effects), output format, and differentiation from sibling tools. The pattern examples help but don't fully compensate for missing behavioral transparency.
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 both parameters thoroughly. The description adds pattern examples and wildcard syntax that complement the schema's 'pattern' parameter description, but doesn't provide additional semantic meaning beyond what's in the structured fields. 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 tool's purpose: 'Find files by name using fast pattern matching.' It specifies the verb ('find'), resource ('files'), and method ('pattern matching'), but doesn't explicitly differentiate from sibling tools like 'search_code' or 'search_in_file' that might have overlapping functionality.
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 'search_code' or 'search_in_file'. It includes pattern examples and tips, but these are syntax instructions rather than usage context. There's no mention of prerequisites, limitations, or comparative scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get file metadata without reading contents. Useful to check size/line count before reading. For large files, provides reading strategy recommendations.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | File path to get info about |
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 effectively describes key traits: it's a read-only operation ('get'), non-destructive, provides metadata only, and offers performance guidance for large files. However, it doesn't mention potential errors (e.g., file not found) or rate limits.
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 usage context and behavioral details. Every sentence adds value without redundancy, and the structure efficiently communicates essential information in just three clauses.
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 tool with one parameter and no output schema, the description is mostly complete: it covers purpose, usage, and key behaviors. However, it lacks details on return values (e.g., what metadata fields are included) and doesn't mention error handling, which would be helpful given the absence of annotations and output schema.
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' well-documented in the schema. The description doesn't add any parameter-specific details beyond what the schema provides, such as path format examples or constraints, so it 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 tool's purpose with specific verbs ('get file metadata') and distinguishes it from sibling tools like 'read_file' by emphasizing it doesn't read contents. It also specifies the resource ('file') and scope ('metadata').
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 explicit guidance on when to use this tool ('to check size/line count before reading') and when not to use it ('without reading contents'). It also implicitly suggests alternatives like 'read_file' for actual content reading and addresses large file scenarios with strategy recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Show which directories this server can access (security boundaries). No parameters required.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'security boundaries,' which hints at access control or permissions, but does not elaborate on behavioral traits such as whether this is a read-only operation, potential rate limits, authentication needs, or what the output format might be. For a tool with zero annotation coverage, this is a significant gap 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 appropriately sized and front-loaded: it consists of two concise sentences that directly state the purpose and parameter requirement without any waste. Every sentence earns its place by providing essential information efficiently.
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 complexity is low (0 parameters, no output schema), the description is somewhat complete but has gaps. It covers the purpose and parameter aspect well, but without annotations or an output schema, it lacks details on behavioral traits and return values. For a simple tool, this is adequate but with clear gaps in transparency and output information.
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 0 parameters with 100% coverage, meaning no parameters are documented in the schema. The description adds value by explicitly stating 'No parameters required,' which clarifies that no inputs are needed. This compensates for the lack of parameters and provides useful semantics, though it doesn't add meaning beyond the schema since there are no parameters to describe.
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: 'Show which directories this server can access (security boundaries).' It specifies the verb 'show' and the resource 'directories this server can access,' with added context about security boundaries. However, it does not explicitly differentiate from sibling tools like 'list_directory' or 'find_files,' which might also involve directory operations, so it lacks sibling differentiation for 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 implies usage by stating 'No parameters required,' suggesting it's a straightforward retrieval tool without input constraints. However, it does not provide explicit guidance on when to use this tool versus alternatives like 'list_directory' or 'search_code,' nor does it mention any prerequisites or exclusions. The usage is implied but not clearly articulated relative to siblings.
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 with metadata including file sizes and line counts
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Directory path to list. Use '.' for workspace root |
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 mentions metadata output (file sizes, line counts) which is useful, but doesn't cover important aspects like pagination behavior, error conditions (e.g., non-existent paths), permission requirements, or rate limits. For a read operation with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.
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 states the core purpose and key output details. Every word earns its place with no redundancy or unnecessary elaboration. It's appropriately sized and front-loaded with the essential information.
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 1 parameter and 100% schema coverage, the description covers the basic purpose and output format. However, with no annotations and no output schema, it should ideally provide more behavioral context about error handling, permissions, or result format. The description is minimally adequate but leaves gaps in understanding the tool's complete behavior.
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 a single 'path' parameter well-documented in the schema. The description adds no additional parameter information beyond what the schema provides. With high schema coverage, the baseline is 3 even without parameter details in the description.
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 verb 'list' and resource 'contents of a directory' with specific metadata details (file sizes and line counts). It distinguishes from siblings like 'find_files' (search) and 'get_file_info' (single file), but doesn't explicitly name alternatives. Purpose is specific but sibling differentiation is implicit rather than explicit.
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 directory listing with metadata, but provides no explicit guidance on when to use this versus alternatives like 'list_allowed_directories' or 'find_files'. The schema description suggests using '.' for workspace root, which gives some context, but no when-not-to-use or prerequisite information is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Read file contents. For large files (>500 lines), use start_line to read in chunks (e.g., 0, 500, 1000). Each call returns up to 500 lines. Binary files return metadata only.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | File path to read | |
| start_line | No | Line number to start reading from (0-indexed). For large files, read in chunks: start_line=0 (first 500), start_line=500 (next 500), etc. |
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 and does so effectively. It describes key behaviors: chunked reading for large files (up to 500 lines per call), handling of binary files (metadata only), and the 0-indexed line numbering. It doesn't cover all possible behaviors (e.g., error cases or permissions), but provides substantial operational context.
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 and efficiently structured into three sentences that each add critical information: basic function, chunking guidance, and binary file handling. There is no wasted text, and it's appropriately sized for the tool's complexity.
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 (2 parameters, no output schema, no annotations), the description is largely complete. It covers the main use cases, limitations (binary files, chunking), and operational details. However, it doesn't address potential error conditions or return format specifics, leaving minor gaps in contextual understanding.
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 both parameters thoroughly. The description adds minimal value beyond the schema by reinforcing the chunking logic for 'start_line' with an example, but doesn't provide additional semantic context or clarify parameter interactions beyond what's in the schema descriptions.
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 contents') and resource ('file'), distinguishing it from siblings like 'get_file_info' (metadata only) or 'search_in_file' (content search). It precisely defines the tool's function beyond just reading by specifying handling of large files and binary files.
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 explicit guidance on when to use this tool vs. alternatives: it specifies to use 'start_line' for large files (>500 lines) to read in chunks, and notes that binary files return metadata only (implying other tools might be needed for binary content). It directly addresses usage scenarios without being misleading.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search for code patterns using ripgrep (very fast). Supports regex patterns and advanced filtering.
PATTERN EXAMPLES:
Exact text: "functionName"
Multiple options: "\b(class|struct|record|interface|enum)\s+TypeName\b" (finds: class TypeName, record TypeName, interface TypeName, etc.)
Regex: "async.*Promise<.*>" (finds async functions returning Promise)
Any declaration: "\b(public|private|protected)\s+\w+\s+methodName"
COMMON USE CASES:
Find type declaration: "\b(class|struct|interface|record|enum)\s+TypeName\b"
Find method: "\b(public|private|protected|internal).\s+methodName\s\("
Find property: "\bpublic\s+\w+\s+propertyName\s*\{"
Find async methods: "async.*Task<"
Find implementations: ":\s*IInterfaceName\b"
TIPS:
Use \b for word boundaries
Use \s+ for whitespace
Combine alternatives with (opt1|opt2|opt3)
Escape special chars: \( \) \{ \}
| Name | Required | Description | Default |
|---|---|---|---|
| pattern | Yes | Regex pattern to search. For multiple alternatives use: (class|struct|interface) to match any | |
| path | No | Limit search to specific directory (e.g., 'src/components'). Omit to search entire workspace. | |
| filePattern | No | File glob pattern (ripgrep -g flag). Examples: '*.js', '*.{ts,tsx}', '!*test*' (exclude). Can specify multiple patterns separated by comma. | |
| caseInsensitive | No | Ignore case in search (ripgrep -i). Default: true for LLM-friendly searching | |
| contextLines | No | Lines of context before/after match (ripgrep -C) | |
| maxResults | No | Maximum number of results to return (per page). Default: 100. Configure via MCP_MAX_SEARCH_RESULTS env var. | |
| page | No | Page number for paginated results (1-based). Use to get more results beyond maxResults. | |
| literalString | No | Treat pattern as literal string, not regex (ripgrep -F) | |
| wordBoundary | No | Match whole words only (ripgrep -w) |
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 effectively adds context beyond the schema by explaining that ripgrep is 'very fast,' providing pattern examples, tips for regex usage, and common use cases. This helps the agent understand how to formulate searches and what to expect, though it doesn't cover aspects like error handling or performance limits.
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 well-structured with clear sections (PATTERN EXAMPLES, COMMON USE CASES, TIPS) and front-loaded with key information. It's appropriately sized for a complex tool, though some redundancy exists (e.g., regex tips partially overlap with schema descriptions). Every sentence adds value, making it efficient but not minimal.
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 complexity (9 parameters, no annotations, no output schema), the description does a good job of providing context. It covers behavioral aspects, usage examples, and tips, compensating for the lack of annotations and output schema. However, it doesn't fully address all potential agent needs, such as detailed error scenarios or pagination behavior beyond the 'page' parameter.
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 9 parameters thoroughly. The description adds value through pattern examples and tips that indirectly relate to parameters like 'pattern' and 'wordBoundary', but it doesn't explicitly enhance parameter semantics beyond what the schema provides. Baseline 3 is appropriate given 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 tool searches for code patterns using ripgrep, which is a specific verb+resource combination. It distinguishes from siblings like 'find_files' or 'search_in_file' by emphasizing regex patterns and advanced filtering capabilities. However, it doesn't explicitly contrast with all siblings in the list.
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 the 'COMMON USE CASES' section (e.g., 'Find type declaration', 'Find method'), which suggests when this tool is appropriate. However, it doesn't explicitly state when to use this versus alternatives like 'search_in_file' or 'find_files', nor does it provide exclusions or prerequisites for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search for patterns within a specific file using ripgrep. Like Ctrl+F but with regex support. Useful for finding specific sections in a known file.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | File path to search within | |
| pattern | Yes | Regex pattern to search for | |
| caseInsensitive | No | Ignore case in search. Default: true | |
| contextLines | No | Lines of context before/after match | |
| literalString | No | Treat pattern as literal string, not regex | |
| wordBoundary | No | Match whole words only |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool uses ripgrep and supports regex, which adds some context, but it doesn't describe what happens on errors (e.g., if the file doesn't exist), the output format, performance characteristics, or any limitations. For a tool with no annotation coverage, this is a significant gap.
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 concise and front-loaded: the first sentence states the core purpose, followed by analogies and usage hints. Every sentence adds value without redundancy, 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 (6 parameters, no output schema, no annotations), the description is minimally adequate. It covers the purpose and basic usage but lacks details on behavior, error handling, and output format. Without annotations or an output schema, more context would be helpful for safe and effective use.
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 6 parameters. The description doesn't add any parameter-specific details beyond what's in the schema (e.g., it doesn't explain regex syntax or path requirements). With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
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: 'Search for patterns within a specific file using ripgrep.' It specifies the verb (search), resource (file), and method (ripgrep with regex support). However, it doesn't explicitly differentiate from sibling tools like 'search_code' or 'find_files' beyond mentioning it's for 'a specific file'.
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 some usage context: 'Useful for finding specific sections in a known file' and 'Like Ctrl+F but with regex support.' This implies it's for targeted searches within a single file, but it doesn't explicitly state when to use this versus alternatives like 'search_code' or 'find_files,' nor does it mention any exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v1.0.0find_filesget_file_infolist_allowed_directorieslist_directoryread_filesearch_codesearch_in_fileMost tools have distinct purposes: find_files locates files by name, get_file_info provides metadata, list_allowed_directories shows accessible directories, list_directory enumerates directory contents, read_file reads file contents, search_code searches across files with regex, and search_in_file searches within a single file. However, search_code and search_in_file could be slightly confused as both involve regex-based searching, though their scopes differ (global vs. file-specific).
All tool names follow a consistent snake_case pattern with clear verb_noun structures: find_files, get_file_info, list_allowed_directories, list_directory, read_file, search_code, and search_in_file. The naming is predictable and readable throughout the set.
With 7 tools, the server is well-scoped for a filesystem domain, covering key operations like finding, listing, reading, and searching files. Each tool serves a specific function without redundancy, making the count appropriate for the intended purpose.
The toolset covers essential filesystem operations such as discovery, metadata retrieval, directory listing, reading, and searching, with good support for large files and regex patterns. A minor gap is the lack of write or modify operations (e.g., create, update, delete files), which might limit full lifecycle management, but the provided tools handle read-only workflows effectively.
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