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grep

Search file contents for specific patterns within virtual filesystem workspaces to locate information efficiently.

Instructions

Search file contents for a pattern.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestYes

Implementation Reference

  • The main handler function for the 'grep' tool. It recursively searches files under the specified path for lines containing the given pattern, collecting matches with file path, line number, and content. Supports truncation for large result sets.
    async def grep(self, request: GrepRequest) -> GrepResponse:
        """
        Search file contents for a pattern.
    
        Args:
            request: GrepRequest with pattern, path, and max_results
    
        Returns:
            GrepResponse with matches
        """
        vfs = self.workspace_manager.get_current_vfs()
        resolved_path = self.workspace_manager.resolve_path(request.path)
    
        matches: list[GrepMatch] = []
        truncated = False
    
        async def search_file(file_path: str) -> None:
            nonlocal truncated
            if len(matches) >= request.max_results:
                truncated = True
                return
    
            try:
                content = await vfs.read_file(file_path)
                if content is None:
                    return
    
                if isinstance(content, bytes):
                    content_str = content.decode("utf-8", errors="ignore")
                else:
                    content_str = content
    
                for line_num, line in enumerate(content_str.splitlines(), start=1):
                    if request.pattern in line:
                        matches.append(
                            GrepMatch(
                                file=file_path, line=line_num, content=line.strip()
                            )
                        )
                        if len(matches) >= request.max_results:
                            truncated = True
                            break
            except Exception:
                # Skip files that can't be read
                pass
    
        async def search_dir(current_path: str) -> None:
            nonlocal truncated
            if len(matches) >= request.max_results:
                truncated = True
                return
    
            filenames = await vfs.ls(current_path)
            for name in filenames:
                if len(matches) >= request.max_results:
                    truncated = True
                    break
    
                # Construct full path
                if current_path == "/":
                    full_path = f"/{name}"
                else:
                    full_path = f"{current_path}/{name}"
    
                node_info = await vfs.get_node_info(full_path)
                if not node_info:
                    continue
    
                if node_info.is_dir:
                    await search_dir(full_path)
                else:
                    await search_file(full_path)
    
        node = await vfs.get_node_info(resolved_path)
        if not node:
            raise ValueError(f"Path not found: {resolved_path}")
    
        if node.is_dir:
            await search_dir(resolved_path)
        else:
            await search_file(resolved_path)
    
        return GrepResponse(
            pattern=request.pattern, matches=matches, truncated=truncated
        )
  • Pydantic models defining the input (GrepRequest), output (GrepResponse), and match structure (GrepMatch) for the grep tool.
    class GrepMatch(BaseModel):
        """A grep match result"""
    
        file: str
        line: int
        content: str
    
    
    class GrepRequest(BaseModel):
        """Request to grep files"""
    
        pattern: str
        path: str = "."
        max_results: int = Field(default=100, ge=1, le=1000)
    
    
    class GrepResponse(BaseModel):
        """Response from grep operation"""
    
        pattern: str
        matches: list[GrepMatch]
        truncated: bool = False
  • Registration of the 'grep' tool in the MCP server using the @server.tool decorator, which delegates to the VFSTools.grep method.
    @server.tool
    async def grep(request: GrepRequest):
        """Search file contents for a pattern."""
        return await vfs_tools.grep(request)
Behavior2/5

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 but only states the basic action. It doesn't reveal whether this is a read-only or mutating operation, what permissions are needed, how results are returned (e.g., line-by-line matches), or any error conditions, which is insufficient for a tool with potential file system interactions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with a single, clear sentence that front-loads the essential action. There is no wasted verbiage, making it efficient and easy to parse, though this brevity contributes to gaps in other dimensions.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (searching file contents) and lack of annotations or output schema, the description is incomplete. It doesn't cover behavioral aspects like safety, output format, or error handling, nor does it address parameters adequately, making it insufficient for reliable agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage, so the description must compensate but adds no parameter details. It doesn't explain what the 'request' parameter represents (e.g., a regex pattern), its format, or examples, leaving the single required parameter undocumented beyond its name in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

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 ('search') and resource ('file contents'), making it easy to understand what it does. However, it doesn't explicitly differentiate from sibling tools like 'find' (which might search file names) or 'read' (which reads file contents without searching), missing full sibling distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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. It doesn't mention when to choose 'grep' over 'find' (for content vs. name searches) or 'read' (for direct file access), nor does it specify prerequisites or exclusions, leaving usage context unclear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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