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MCP Git Server

by MementoRC

github_get_pr_files

Retrieve files changed in a GitHub pull request with pagination support. Specify repository owner, name, and PR number to fetch file details, including optional patch data, for efficient review.

Instructions

Get files changed in a pull request with pagination support

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
include_patchNo
pageNo
per_pageNo
pr_numberYes
repo_nameYes
repo_ownerYes

Implementation Reference

  • Main handler function that implements the github_get_pr_files tool. Fetches changed files from GitHub PR API endpoint, formats output with status emojis, change counts, optional patches with memory management via PatchMemoryManager to prevent token overflow.
    async def github_get_pr_files(
        repo_owner: str,
        repo_name: str,
        pr_number: int,
        per_page: int = 30,
        page: int = 1,
        include_patch: bool = False,
    ) -> str:
        """Get files changed in a pull request with memory-aware patch handling"""
        try:
            async with github_client_context() as client:
                params = {"per_page": per_page, "page": page}
    
                response = await client.get(
                    f"/repos/{repo_owner}/{repo_name}/pulls/{pr_number}/files",
                    params=params,
                )
                if response.status != 200:
                    return f"❌ Failed to get PR files: {response.status}"
    
                files = await response.json()
    
                if not files:
                    return f"No files found for PR #{pr_number}"
    
                output = [f"Files changed in PR #{pr_number}:\n"]
    
                total_additions = 0
                total_deletions = 0
    
                # Initialize memory manager for patch processing
                patch_manager = PatchMemoryManager(
                    max_patch_size=1000, max_total_memory=50000
                )
    
                for file in files:
                    status_emoji = {
                        "added": "➕",
                        "modified": "📝",
                        "removed": "➖",
                        "renamed": "📝",
                    }.get(file.get("status"), "❓")
    
                    additions = file.get("additions", 0)
                    deletions = file.get("deletions", 0)
                    total_additions += additions
                    total_deletions += deletions
    
                    output.append(
                        f"{status_emoji} {file['filename']} (+{additions}, -{deletions})"
                    )
    
                    if include_patch and file.get("patch"):
                        # Use memory manager to safely process patch content
                        processed_patch, was_truncated = patch_manager.process_patch(
                            file["patch"]
                        )
                        output.append(processed_patch)
    
                        if was_truncated:
                            logger.info(
                                f"Patch for {file['filename']} was truncated or skipped for memory management"
                            )
    
                    output.append("")
    
                output.append(f"Total: +{total_additions}, -{total_deletions}")
    
                # Add memory usage summary if patches were included
                if include_patch:
                    output.append(
                        f"\nMemory usage: {patch_manager.current_memory_usage}/{patch_manager.max_total_memory} bytes"
                    )
                    output.append(f"Patches processed: {patch_manager.patches_processed}")
    
                return "\n".join(output)
    
        except ValueError as auth_error:
            logger.error(f"Authentication error getting PR files: {auth_error}")
            return f"❌ {str(auth_error)}"
        except ConnectionError as conn_error:
            logger.error(f"Connection error getting PR files: {conn_error}")
            return f"❌ Network connection failed: {str(conn_error)}"
        except Exception as e:
            logger.error(
                f"Unexpected error getting PR files for PR #{pr_number}: {e}", exc_info=True
            )
            return f"❌ Error getting PR files: {str(e)}"
  • Pydantic input schema/model for validating parameters to the github_get_pr_files tool.
    class GitHubGetPRFiles(BaseModel):
        repo_owner: str
        repo_name: str
        pr_number: int
        per_page: int = 30
        page: int = 1
        include_patch: bool = False
  • ToolDefinition registration in the default GitHub tools list within ToolRegistry.initialize_default_tools(), associating name, description, schema, and metadata.
        name=GitTools.GITHUB_GET_PR_FILES,
        category=ToolCategory.GITHUB,
        description="Get files changed in a pull request",
        schema=GitHubGetPRFiles,
        handler=placeholder_handler,
        requires_repo=False,
        requires_github_token=True,
    ),
  • Handler wrapper registration in CallToolHandler._get_github_handlers(), creating a decorated async handler wrapper that calls the actual github_get_pr_files function from github.api.
    "github_get_pr_files": self._create_github_handler(
        github_get_pr_files,
        [
            "repo_owner",
            "repo_name",
            "pr_number",
            "per_page",
            "page",
            "include_patch",
        ],
    ),
  • Supporting class used by the handler for memory-aware management of patch content to avoid exceeding token limits when including large diffs.
    class PatchMemoryManager:
        """Memory-aware patch content manager with configurable limits and streaming support."""
    
        def __init__(self, max_patch_size: int = 1000, max_total_memory: int = 50000):
            self.max_patch_size = max_patch_size
            self.max_total_memory = max_total_memory
            self.current_memory_usage = 0
            self.patches_processed = 0
    
        def can_include_patch(self, patch_size: int) -> bool:
            """Check if patch can be included within memory constraints."""
            return (self.current_memory_usage + patch_size) <= self.max_total_memory
    
        def process_patch(self, patch_content: str) -> tuple[str, bool]:
            """Process patch content with memory management and truncation.
    
            Returns:
                tuple[str, bool]: (processed_content, was_truncated)
            """
            patch_size = len(patch_content)
            self.patches_processed += 1
    
            # Check memory budget first
            if not self.can_include_patch(patch_size):
                logger.warning(
                    f"Patch #{self.patches_processed} skipped: exceeds memory budget ({patch_size} bytes, {self.current_memory_usage}/{self.max_total_memory} used)"
                )
                return (
                    f"[Patch skipped - memory limit reached ({self.current_memory_usage}/{self.max_total_memory} bytes used)]",
                    True,
                )
    
            # Apply individual patch size limit
            if patch_size > self.max_patch_size:
                truncated_patch = patch_content[: self.max_patch_size]
                self.current_memory_usage += self.max_patch_size
                logger.info(
                    f"Patch #{self.patches_processed} truncated: {patch_size} -> {self.max_patch_size} bytes"
                )
                return (
                    f"```diff\n{truncated_patch}\n... [truncated {patch_size - self.max_patch_size} chars]\n```",
                    True,
                )
            else:
                self.current_memory_usage += patch_size
                return f"```diff\n{patch_content}\n```", False
Behavior2/5

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 'pagination support', which is useful, but fails to describe critical behaviors such as rate limits, authentication requirements, error handling, or the format of returned data (e.g., file paths, change types). For a read operation with multiple parameters, this leaves significant gaps.

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 a single, well-structured sentence that efficiently conveys the core functionality and key feature (pagination). It's front-loaded with the main purpose and avoids unnecessary details, making it highly concise and easy to parse.

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 complexity (6 parameters, no annotations, no output schema), the description is incomplete. It lacks details on authentication, rate limits, error cases, and the structure of returned data (e.g., list of files with changes). For a tool that interacts with GitHub's API and handles pagination, this omission makes it inadequate for safe and effective use by an AI agent.

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?

Schema description coverage is 0%, meaning none of the 6 parameters have descriptions in the schema. The description only implies pagination-related parameters ('page', 'per_page') and hints at 'include_patch' but doesn't explain what these mean or how they affect results. It doesn't cover required parameters like 'repo_owner', 'repo_name', and 'pr_number', leaving their purpose unclear.

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 verb ('Get') and resource ('files changed in a pull request'), making the purpose specific and understandable. However, it doesn't explicitly distinguish this tool from sibling tools like 'github_get_pr_details' or 'github_get_pr_status', which reduces clarity about its unique role in the GitHub PR toolset.

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 scenarios where this tool is preferred over other GitHub PR tools (e.g., 'github_get_pr_details' for metadata or 'github_get_pr_checks' for status checks), nor does it specify prerequisites like needing a valid PR number or repository access.

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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