diffctx — smart diff context for LLM code review

diffctx selects the minimum code an LLM needs to review a git diff. Instead of pasting whole files, it walks the dependency graph outward from the changed lines and stops once more context stops paying for itself.

Formerly published as treemapper — every command, flag, and API call works unchanged.

How it compares

Whole-repo packers (repomix and friends) seed on the repository and export everything; persistent code-graph servers answer structural queries against a maintained index. diffctx is diff-seeded: the input is a change, the output is the fragments needed to understand it, packed under a hard token budget — local, deterministic, no index, no model calls. Measured results and when the other two families fit better: COMPARISON.md.

Install

uvx diffctx . --diff HEAD~1             # zero-install, run once via uv
pipx install diffctx                    # recommended: isolated CLI, no venv needed
pip install diffctx                     # or: into an active environment
pipx install 'diffctx[mcp]'             # + MCP server for AI assistants

Without Python:

cargo install diffctx                   # native CLI from crates.io
npx diffctx . --diff HEAD~1             # npm wrapper over the native binary
docker run --rm -v "$PWD:/repo" ghcr.io/nikolay-e/diffctx . --diff HEAD~1

On Windows, via Scoop (this repository is the bucket):

scoop bucket add diffctx https://github.com/nikolay-e/diffctx
scoop install diffctx/diffctx

Prebuilt binaries for linux (x86_64/aarch64), macOS (arm64) and Windows (x64) are attached to every release. The native binary and Docker image cover diff mode with YAML/JSON output and write to stdout (redirect to capture); tree mode, Markdown output, the graph subcommand and the MCP server live in the Python package.

Quick start

diffctx . --diff HEAD~1       # smart context for last commit → paste into Claude/ChatGPT
diffctx . -f md -c            # full codebase export → clipboard in Markdown

diffctx . --diff HEAD~1 selects only the fragments an LLM needs to review the last commit, instead of dumping every changed file in full.

Diff context mode

Finds the minimal set of fragments needed to understand a change — imports, callers, type definitions, config dependencies — across 50+ file types. It builds a code graph (imports, co-changes, type refs), propagates relevance outward from the changed lines, and stops when relevance drops below --tau or the --budget token cap is hit.

Flag	Default	Description
--scoring	ego	ego = bounded expansion around changed nodes (fast, predictable radius); ppr = Personalized PageRank (global, smoother decay, slower); bm25 = lexical retrieval against the diff hunks (baseline for sparse graphs)
--budget	auto	Hard cap in o200k_base tokens (see Token counting): N enforces a fixed cap, -1 disables it, 0 is a strict-zero floor (empty selection; use --full for changed files only)
--alpha	0.60	PPR damping; higher = context clusters tighter around changes (--scoring ppr only)
--tau	0.12	Relevance threshold for full fragment content; lower-scoring fragments are stubbed or dropped (lower = more context)
--full	false	Only the changed files, every fragment, no related-code context
--timeout	300	Wall-clock deadline in seconds; on expiry diffctx exits 124 instead of hanging
--with-raw-diff	false	Also embed git's raw unified diff ahead of the selected fragments — additive (selection unchanged), not charged to --budget, lock/ignored/secret-like sections omitted. Python CLI only
--mode	pack	locate emits the same ranked selection as compact diffctx.locate.v1 JSON — path, lines, score, provenance reasons, a blast-radius summary and per-item impact group (test/type/config), NO source bodies. diffctx . --diff --mode locate = impact of your uncommitted change. The MCP tool takes it as mode="locate"

graph subcommand

Explore the underlying dependency graph directly, without a diff:

diffctx graph .                                  # Mermaid graph of directory deps (default)
diffctx graph . --summary                        # cycles, hotspots, coupling metrics
diffctx graph . --level fragment -f json         # fragment-level graph as JSON
diffctx graph . --level file -f graphml -o g.xml # file-level graph as GraphML

Usage

<!-- BEGIN USAGE -->

# full codebase export:
diffctx .                                 # Markdown to stdout + token count
diffctx . -f md -c                        # Markdown → clipboard
diffctx . -f json -o tree.json            # JSON → file
diffctx . --no-content                    # structure only, no file contents
diffctx . --max-depth 3                   # limit depth
diffctx . -i custom.ignore                # custom ignore patterns

# diff context mode (requires git repo):
diffctx . --diff                          # uncommitted changes (working tree vs HEAD)
diffctx . --diff HEAD~1                   # context for last commit
diffctx . --diff main..feature            # context for feature branch
diffctx . --diff HEAD~1 --budget 30000    # limit to ~30k tokens
diffctx . --diff HEAD~1 -c                # diff context to clipboard
diffctx . --diff HEAD~1 --with-raw-diff   # raw patch + selected context
diffctx . --diff HEAD~1 --mode locate     # ranked navigation JSON, no source

<!-- END USAGE -->

Every run reports token count and size on stderr — 12,847 tokens (o200k_base), 52.3 KB. Counts are exact only for the GPT-4o family; Claude, Gemini and others tokenize differently, so treat --budget as an upper bound and leave headroom (details). Unreadable files become placeholders like <binary file: N bytes>.

Python API

from pathlib import Path
from diffctx import build_diff_context, map_directory, to_json, to_markdown, to_text, to_yaml

ctx = build_diff_context(
    Path("."),
    "HEAD~1..HEAD",
    budget_tokens=None,       # None = auto; 0 = strict-zero floor (empty); -1 = uncapped; N = hard cap
    alpha=0.6,
    tau=0.12,
    full=False,
    scoring_mode="ego",
    timeout=300,
    with_raw_diff=False,      # True also embeds the raw unified diff (not charged to budget)
)
print(to_markdown(ctx))

tree = map_directory(
    ".",
    max_depth=None,
    no_content=False,
    max_file_bytes=None,
    ignore_file=None,
    no_default_ignores=False,
    whitelist_file=None,
)
print(to_yaml(tree))

MCP server

diffctx includes an MCP server that lets AI assistants (Claude Code, Cursor, Windsurf, etc.) call diff context analysis automatically during code review. It is published in the official MCP registry as io.github.nikolay-e/diffctx. One-line setup (zero-install via uv):

# Claude Code
claude mcp add diffctx -- uvx --from 'diffctx[mcp]' diffctx-mcp
# Codex CLI
codex mcp add diffctx -- uvx --from 'diffctx[mcp]' diffctx-mcp
# Gemini CLI
gemini mcp add diffctx uvx -- --from 'diffctx[mcp]' diffctx-mcp
# VS Code
code --add-mcp '{"name":"diffctx","command":"uvx","args":["--from","diffctx[mcp]","diffctx-mcp"]}'

With pip install 'diffctx[mcp]' already done, replace the uvx --from 'diffctx[mcp]' diffctx-mcp tail with plain diffctx-mcp.

The server exposes three tools — get_diff_context, get_tree_map, and get_file_context — that assistants call when reviewing PRs, explaining changes, or investigating broken tests. Tool reference and JSON configs for Claude Desktop, Cursor, Continue, Windsurf, and Zed: src/diffctx/mcp/README.md.

Ignore patterns

Respects .gitignore and .diffctx/ignore automatically — hierarchically at every directory level, with full gitignore semantics (negation !important.log, anchored /root_only.txt). .diffctx/whitelist acts as an include-only filter, and the output file is always auto-ignored. --no-default-ignores disables the built-in patterns; --no-ignores disables all ignore rules (tree mode only).

An excluded path never appears in the output in any role: in diff mode it is dropped both from changed_files and from the candidate universe, so it cannot come back as a related-context fragment either (including under --full). The same guarantee covers secret-like paths (id_rsa, *.pem, *.key, ...), which are filtered even without an ignore entry.

Token cache

Diff mode caches per-blob tokenization in the OS cache directory (e.g. ~/Library/Caches/diffctx/token-cache) — a pure speedup, safe to delete. DIFFCTX_TOKEN_CACHE_DIR relocates it; DIFFCTX_TOKEN_CACHE_MAX_BYTES caps its size (default 512 MB, 0 disables eviction).

Exit codes

Code	Meaning
0	Success — output contains content
1	Runtime error (bad path, permission denied, etc.)
2	Usage error (invalid flags/arguments)
3	Environment error (--diff outside a git repo, git not installed, no commits yet)
4	--diff produced no semantic context (clean tree, binary-only, everything filtered); output is still emitted. Deletion/rename/lockfile-only diffs list deleted_files/renamed_files/lockfile_changes and exit 0
124	--diff exceeded the --timeout wall-clock deadline
130	Interrupted (Ctrl-C)
141	Broken pipe (e.g. piping into head)

License

Apache 2.0

<!-- mcp-name: io.github.nikolay-e/diffctx --> <!-- Ownership marker read from the PyPI description by the MCP registry. --> <!-- Must survive edits verbatim: one space after the colon, case-sensitive. -->

---

• Documentation site — the pipeline end to end: diff → fragments → graph → relevance → selection
• GitHub Action — diff context as a CI step for LLM review
• Token counting — which encoder, and what --budget means for non-GPT models
• Comparison — measured results, and when a whole-repo packer or a persistent code-graph server fits better
• Paper — budgeted typed-graph retrieval for diff-aware context selection (Zenodo, 2026)
• Changelog
• Security policy — threat model and vulnerability reporting
• Parameter strategy — how --alpha, --tau, and edge weights are calibrated