Install
$ agentstack add mcp-mariusei-file-scanner-mcp Open-source listing — not yet scanned by AgentStack. Follow the source repository for install instructions.
Security review
⚠ Flagged1 finding(s); flagged for manual review. · v0.1.0 How review works →
- • Prompt-injection patterns
- • Secret / credential exfiltration
- • Dangerous shell & filesystem operations
- • Untrusted network calls
- • Known-malicious package signatures
- high Pipes remote content directly into a shell (remote code execution).
What it can access
- ● Network access Used
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
Scantool: Code Analysis MCP Server for Claude
[](https://pypi.org/project/scantool/) [](https://opensource.org/licenses/MIT)
MCP server that hands an AI agent a codebase's structure — classes, functions, call graphs, imports, hot functions, all with exact line numbers — instead of raw file dumps. Works with Claude Code, Claude Desktop, Cursor, VS Code and any Model Context Protocol client. 20+ languages via tree-sitter — and code and documents (Markdown, HTML, CSS, SQL, config) through the same lens, which the code-only tools don't do.
What that buys, measured — not claimed:
"Where is the cache invalidated?" scantool 378 tokens / 1 call
grep 9,370 tokens / 4 calls -> 25x less
pytest skipif-caching bug scantool solved in 3 calls
grep gave up after 13,450 tokens
On real agent episodes, scantool agents answered with 88% fact coverage vs 73% for a grep-only agent — better-anchored answers, fewer wrong files. Honest scope: grep still wins plain literal lookups and top-level overviews. Scantool measures both axes and reports the losses too (experiments/benchmark/).
Zero infrastructure: no index to build, no API keys, no vector database, no model downloads. Point it at a directory and it scans on demand.
Quick Start
Requires uv (provides the uvx command). Install it first if you don't have it — without it, scantool will silently fail to start:
# macOS / Linux / WSL
curl -LsSf https://astral.sh/uv/install.sh | sh
Claude Code
# Available in all your projects (recommended)
claude mcp add --scope user scantool -- uvx scantool
# Or just for the current project
claude mcp add scantool -- uvx scantool
Restart Claude Code and you're ready to go.
Claude Desktop
Add to config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):
{
"mcpServers": {
"scantool": {
"command": "uvx",
"args": ["scantool"]
}
}
}
Restart Claude Desktop after configuration.
Cursor
Add to ~/.cursor/mcp.json (global) or .cursor/mcp.json (per project):
{
"mcpServers": {
"scantool": {
"command": "uvx",
"args": ["scantool"]
}
}
}
Windsurf
Add to ~/.codeium/windsurf/mcp_config.json:
{
"mcpServers": {
"scantool": {
"command": "uvx",
"args": ["scantool"]
}
}
}
VS Code (Copilot agent mode)
Add to .vscode/mcp.json in your workspace:
{
"servers": {
"scantool": {
"command": "uvx",
"args": ["scantool"]
}
}
}
Cline
In the Cline panel: MCP Servers icon → Configure tab → Configure MCP Servers, then add the same mcpServers entry as above. (Cline CLI reads ~/.cline/mcp.json.)
Troubleshooting: uvx not found
uvx comes with uv, the Python package manager. Install it first:
# macOS / Linux / WSL
curl -LsSf https://astral.sh/uv/install.sh | sh
# Windows (PowerShell)
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
After installing uv, restart your terminal (or open a new one) so uvx is on your PATH. Then re-run the setup command above.
If uvx still isn't found after restarting the terminal, add it to your PATH manually:
# Linux / WSL - add to ~/.bashrc or ~/.zshrc:
export PATH="$HOME/.local/bin:$PATH"
# macOS - usually works out of the box, but if not:
export PATH="$HOME/.local/bin:$PATH"
Alternative: Install from source
git clone https://github.com/mariusei/file-scanner-mcp.git
cd file-scanner-mcp
uv sync
# Claude Code
claude mcp add --transport stdio scantool -- uv run --directory /path/to/file-scanner-mcp scantool
# Claude Desktop
# Use command: "uv", args: ["run", "--directory", "/path/to/file-scanner-mcp", "scantool"]
Share with your team (.mcp.json)
Add a .mcp.json file to your project root to share the config with your team:
{
"mcpServers": {
"scantool": {
"command": "uvx",
"args": ["scantool"]
}
}
}
Claude Code will prompt team members for approval on first use.
Features
Multi-language Support
Python, JavaScript, TypeScript, Rust, Go, C/C++, Java, PHP, C#, Ruby, Zig, Swift, SQL (PostgreSQL, MySQL, SQLite), HTML, CSS, SCSS, Markdown, Plain Text, Images
Structure Extraction
- Classes, methods, functions, imports
- Function signatures with type annotations
- Decorators and attributes
- Docstrings and JSDoc comments
- Precise line numbers (from-to ranges)
Analysis Tools
- preview_directory: Intelligent codebase analysis with entry points, import graph, call graph, and hot functions (5-10s)
- scan_file: Detailed file structure with signatures and metadata;
focus=reads one named function/class/section verbatim with parent context - scan_directory: Compact directory tree with inline function/class names
- search_structures: Filter by type, name pattern, decorator, or complexity
- list_directories: Directory tree (folders only)
- find_divergence: Audit a directory for peer divergence — functions that break a call pattern their siblings follow (peers calling X also call Y, this one doesn't); a review hint, not a verified bug; silent on a consistent codebase. The same section also appears inline in
scan_diff(changed code) andpreview_directory(deep)
Output Formats
- Tree format with box-drawing characters
- JSON format for programmatic use
- Configurable display options
Usage
preview_directory - Code analysis (primary tool)
Analyzes codebase structure including entry points, import graph, call graph, and hot functions.
preview_directory(
directory=".",
depth="deep", # "quick", "normal", or "deep" (default: "deep")
max_files=10000, # Safety limit (default: 10000)
max_entries=20, # Entries per section (default: 20)
respect_gitignore=True # Honor .gitignore (default: True)
)
Depth levels:
"quick": Metadata only (0.5s) - file counts, sizes, types"normal": Architecture analysis (2-5s) - imports, entry points, clusters"deep": Full analysis (5-10s) - includes hot functions and call graph (default)
Example output (depth="deep"):
project/
--- ENTRY POINTS ---
main.py:main() @1
backend/application.py:Flask app @15
frontend/index.ts:export default
--- CORE FILES (by centrality) ---
backend/database.py: imports 0, used by 15 files
backend/auth.py: imports 1, used by 8 files
shared/utils.py: imports 2, used by 12 files
--- ARCHITECTURE ---
Entry Points: 25 files
Core Logic: 68 files
Plugins: 15 files
Tests: 42 files
--- HOT FUNCTIONS (most called) ---
get_database() (function): called by 41, calls 1 @backend/database.py
authenticate() (function): called by 23, calls 5 @backend/auth.py
validate_input() (function): called by 15, calls 2 @shared/utils.py
Analysis: 486 files in 4.82s (layer1+layer2)
Use cases:
- First-time codebase exploration
- Understanding multi-modality projects (frontend/backend/database)
- Finding critical functions (hot spots)
- Identifying entry points
scan_file - Detailed file analysis
scan_file(
file_path="path/to/file.py",
focus=None, # Read ONE node verbatim by name ("query",
# "DatabaseManager.query", a markdown heading)
# instead of guessing line ranges — see below
show_signatures=True, # Include function signatures with types
show_decorators=True, # Include @decorator annotations
show_docstrings=True, # Include first line of docstrings
show_complexity=False, # Show complexity metrics
condense=True, # Condensed skeletons (set False for verbatim lines)
budget=None, # Approx token cap for skeletons — least salient
# functions degrade first, output stays predictable
output_format="tree" # "tree" or "json"
)
Example output:
example.py (1-57)
- file-info: 1.4KB modified: 2 hours ago
- imports: import statements (3-5)
- class: DatabaseManager (8-26)
"Manages database connections and queries."
- method: __init__ (self, connection_string: str) (11-13)
- method: connect (self) (15-17)
"Establish database connection."
- method: query (self, sql: str) -> list (24-26)
"Execute a SQL query."
return self.cursor.execute(sql).fetchall()
- function: main () (53-57)
"Main entry point."
Functions additionally show their implementation as a condensed method skeleton: pseudocode lines without line numbers where control flow with conditions, calls and returns are kept and trivial statements fold to … (verbatim lines always carry N | line numbers — that's how you tell them apart). Skeletons come in two tiers: the most salient functions (by entropy, uniqueness and centrality) get full depth, every other function gets a shallow depth-2 outline — measured as the best fact-coverage per token. Markers are plain ASCII because box-drawing glyphs cost 2-3 BPE tokens each. Pass condense=False to get line-numbered excerpts (top tier only) instead.
Condensation adapts to the language: imperative languages (Python, TypeScript, Go, Rust, Java, ...) get fold-by-default skeletons, declarative ones (CSS, SQL, HTML) keep their content and drop only blanks, comments and closing punctuation, and prose/config stay verbatim — where there is nothing safe to fold, the original excerpt is shown unchanged.
focus= — the read step
After a scan or search has located a node, pass focus= to read exactly that function/class/method/heading verbatim — instead of guessing a line range for Read/cat/sed:
scan_file(file_path="example.py", focus="DatabaseManager.query")
focus: DatabaseManager.query @24-26
example.py (3-57)
- import statements @3
- DatabaseManager @8 # Manages database connections and queries.
- __init__ (self, connection_string: str) @11
- connect (self) @15 # Establish database connection.
- disconnect (self) @19 # Close database connection.
- query (self, sql: str) -> list @24 # Execute a SQL query.
24 | def query(self, sql: str) -> list:
25 | """Execute a SQL query."""
26 | return []
- UserService @29 # Handles user-related operations.
- validate_email (email: str) -> bool @48 # Validate email format.
- main () @53 # Main entry point.
The rest of the file stays as a depth-1 skeleton, so the node arrives with its parent context. Names resolve in three tiers: exact match, qualified path (ClassA.method, works for markdown headings too), then case-insensitive substring; an ambiguous name returns the qualified candidate list instead of guessing. Measured on real agent episodes (experiments/benchmark/M2C.md): equal answer quality at 75% fewer read tokens than cat/sed line-range guessing.
scanfilecontent - Analyze content directly
Scan content without requiring a file path. Works with remote files, APIs, or in-memory content.
scan_file_content(
content="def hello(): pass\n\nclass MyClass:\n pass",
filename="example.py", # Extension determines parser
show_signatures=True,
show_decorators=True,
show_docstrings=True,
show_complexity=False,
output_format="tree"
)
scan_directory - Compact overview
Shows directory tree with inline class/function names.
scan_directory(
directory="./src",
pattern="**/*", # Glob pattern
max_files=None, # File limit
respect_gitignore=True, # Honor .gitignore
exclude_patterns=None, # Additional exclusions
output_format="tree" # "tree" or "json"
)
Example output:
src/ (22 files, 15 classes, 127 functions, 89 methods)
├─ languages/
│ ├─ python.py (1-329) [11.9KB, 2 hours ago] - PythonLanguage
│ ├─ typescript.py (1-505) [18.9KB, 1 day ago] - TypeScriptLanguage
│ └─ rust.py (1-481) [17.6KB, 3 days ago] - RustLanguage
├─ scanner.py (1-232) [8.8KB, 5 mins ago] - FileScanner
└─ server.py (1-735) [27.2KB, just now] - scan_file, scan_directory, ...
Pattern examples:
# Specific file types
scan_directory("./src", pattern="**/*.py")
# Multiple types
scan_directory("./src", pattern="**/*.{py,ts,js}")
# Shallow scan (1 level deep)
scan_directory(".", pattern="*/*")
# Exclude directories
scan_directory(".", exclude_patterns=["tests/**", "docs/**"])
search_structures - Find and filter
# Find test functions
search_structures(
directory="./tests",
type_filter="function",
name_pattern="^test_"
)
# Find classes ending in "Manager"
search_structures(
directory="./src",
type_filter="class",
name_pattern=".*Manager$"
)
# Find functions with @staticmethod
search_structures(
directory="./src",
has_decorator="@staticmethod"
)
# Find complex functions (>100 lines)
search_structures(
directory="./src",
type_filter="function",
min_complexity=100
)
list_directories - Folder structure
Shows directory tree without files.
list_directories(
directory=".",
max_depth=3, # Maximum depth (default: 3)
respect_gitignore=True # Honor .gitignore (default: True)
)
Example output:
/Users/user/project/
├─ src/
│ ├─ components/
│ ├─ services/
│ └─ utils/
├─ tests/
│ ├─ unit/
│ └─ integration/
└─ docs/
Output Contract
The default output format IS the API: LLM agents consume scantool output directly and uncritically, so format drift is behavior drift in the consumer (measured in experiments/benchmark/M2B.md). Two consequences:
- Defaults are the measured optimum — parameters are escape hatches.
Every default (two-tier condensation, saliency selection, skeleton depth, compact vs verbatim per language) is backed by measurements in experiments/condensation/, experiments/entropy_metrics/ and experiments/benchmark/. Override them when a specific situation demands it, not as a style preference.
- The default format is frozen by golden tests (
tests/test_golden.py,
snapshots in tests/golden/). A deliberate format change requires a deliberate snapshot update (UPDATE_GOLDEN=1 uv run pytest tests/test_golden.py); an accidental change fails CI. Environment- dependent parts (file size/mtime, git churn, delta memory) live outside the frozen layer. Peer divergence is a pure function of the code, so it is frozen too (tests/golden/consensus.txt, fixture in tests/golden/consensus_fixture/).
Supported Languages
| Extension | Language | Extracted Elements | |-----------|----------|-------------------| | .py, .pyw | Python | classes, methods, functions, imports, decorators, docstrings | | .js, .jsx, .mjs, .cjs | JavaScript | classes, methods, functions, imports, JSDoc comments | | .ts, .tsx, .mts, .cts | TypeScript | classes, methods, functions, imports, type annotations, JSDoc | | .rs | Rust | structs, enums, traits, impl blocks, functions, use statements | | .go | Go | types, structs, interfaces, functions, methods, imports | | .c, .h | C | functions, structs, enums, includes | | .cpp, .hpp, .cc, .hh | C++ | classes, functions, namespaces, templates, includes | | .java | Java | classes, methods, interfaces, enums, annotations, imports | | .php | PHP | classes, methods, functions, traits, interfaces, namespaces | | .cs | C# | classes, methods, properties, structs, enums, namespaces | | .rb | Ruby | modules, classes, methods, singleton methods | | .zig | Zig | functions, structs, enums, unions, tests | | .swift | Swift | clas
…
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: mariusei
- Source: mariusei/file-scanner-mcp
- License: MIT
- Homepage: https://pypi.org/project/scantool/
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.