MCP server that enables LLMs to navigate large diff files efficiently. Instead of reading entire diffs sequentially, LLMs can jump directly to relevant changes using pattern-based navigation.
Large diffs exceed LLM context limits and waste tokens on irrelevant changes. A 50k+ line diff can't be processed directly and manual splitting loses file relationships.
MCP server with 4 navigation tools:
load_diff
- Parse diff file with custom settings (optional)list_chunks
- Show chunk overview with file mappings (auto-loads)get_chunk
- Retrieve specific chunk content (auto-loads)find_chunks_for_files
- Locate chunks by file patterns (auto-loads)
Prerequisite: Install uv (an extremely fast Python package manager) which provides the uvx
command.
Add to your MCP client configuration:
{
"mcpServers": {
"diffchunk": {
"command": "uvx",
"args": ["--from", "diffchunk", "diffchunk-mcp"]
}
}
}
Your AI assistant can now handle massive changesets that previously caused failures in Cline, Roocode, Cursor, and other tools.
Once configured, your AI assistant can analyze large commits, branches, or diffs using diffchunk.
Here are some example use cases:
Branch comparisons:
- "Review all changes in develop not in the main branch for any bugs"
- "Tell me about all the changes I have yet to merge"
- "What new features were added to the staging branch?"
- "Summarize all changes to this repo in the last 2 weeks"
Code review:
- "Use diffchunk to check my feature branch for security vulnerabilities"
- "Use diffchunk to find any breaking changes before I merge to production"
- "Use diffchunk to review this large refactor for potential issues"
Change analysis:
- "Use diffchunk to show me all database migrations that need to be run"
- "Use diffchunk to find what API changes might affect our mobile app"
- "Use diffchunk to analyze all new dependencies added recently"
Direct file analysis:
- "Use diffchunk to analyze the diff at /tmp/changes.diff and find any bugs"
- "Create a diff of my uncommitted changes and review it"
- "Compare my local branch with origin and highlight conflicts"
Add to your AI assistant's custom instructions for automatic usage:
When reviewing large changesets or git commits, use diffchunk to handle large diff files.
Create temporary diff files and tracking files as needed and clean up after analysis.
When you ask your AI assistant to analyze changes, it uses diffchunk's tools strategically:
- Creates the diff file (e.g.,
git diff main..develop > /tmp/changes.diff
) based on your question - Uses
list_chunks
to get an overview of the diff structure and total scope - Uses
find_chunks_for_files
to locate relevant sections when you ask about specific file types - Uses
get_chunk
to examine specific sections without loading the entire diff into context - Tracks progress systematically through large changesets, analyzing chunk by chunk
- Cleans up temporary files after completing the analysis
This lets your AI assistant handle massive diffs that would normally crash other tools, while providing thorough analysis without losing context.
Overview first:
list_chunks("/tmp/changes.diff")
# → 5 chunks across 12 files, 3,847 total lines
Target specific files:
find_chunks_for_files("/tmp/changes.diff", "*.py")
# → [1, 3, 5] - Python file chunks
get_chunk("/tmp/changes.diff", 1)
# → Content of first Python chunk
Systematic analysis:
# Process each chunk in sequence
get_chunk("/tmp/changes.diff", 1)
get_chunk("/tmp/changes.diff", 2)
# ... continue through all chunks
- Absolute paths only:
/home/user/project/changes.diff
- Cross-platform: Windows (
C:\path
) and Unix (/path
) - Home expansion:
~/project/changes.diff
Tools auto-load with optimized settings:
max_chunk_lines
: 1000skip_trivial
: true (whitespace-only)skip_generated
: true (lock files, build artifacts)
Use load_diff
for non-default behavior:
load_diff(
"/tmp/large.diff",
max_chunk_lines=2000,
include_patterns="*.py,*.js",
exclude_patterns="*test*"
)
- Git diff output (
git diff
,git show
) - Unified diff format (
diff -u
) - Multiple files in single diff
- Binary file change indicators
- Efficiently handles 100k+ line diffs
- Memory efficient streaming
- Auto-reload on file changes
- Design - Architecture and implementation details
- Contributing - Development setup and workflows