FilePilot AI

Local-first file intelligence for desktop users, scripts, and AI coding agents.

FilePilot AI helps you search, understand, tag, deduplicate, summarize, and safely organize local files. It includes a desktop app, a CLI, and a privacy-first MCP server for Claude Code, Codex, Cursor, Claude Desktop, and other agent clients.

Version 0.8.1

At A Glance

What it is	Why it matters
Local-first file manager	Search, preview, tag, deduplicate, and organize files without uploading an index to a cloud service.
MCP server for agents	Let AI coding agents inspect only the folders you allow, with bounded reads and read-only defaults.
Preview-first organizer	Generate dry-run organization plans before any files move.
Optional AI summaries	Use local models or explicitly configured cloud providers for document summaries.
Desktop + CLI + MCP	Start visually, automate with scripts, or expose scoped tools to agent clients.

Related MCP server: File Organizer MCP

Best For

Developers who want Claude Code, Codex, Cursor, or Claude Desktop to inspect local files without broad filesystem access.
Desktop users with messy Downloads, exports, backups, screenshots, PDFs, and duplicate files.
Maintainers who want a local-first file intelligence layer with tests, docs, release checks, and a clear safety model.
Builders looking for a practical Python/PySide6 MCP reference project that is more than a toy demo.

Why FilePilot Exists

Modern AI agents can reason about code and documents, but giving them raw access to your whole filesystem is risky. FilePilot sits between your local files and the tools that need them.

It is built around a simple promise:

Your files stay local by default.
File reads are scoped, bounded, and explicit.
Cleanup starts as a preview, not a destructive action.
AI features are optional and use only the providers you configure.
Agent-facing write operations require opt-in write mode, confirmation, validation, and audit logs.

What Makes It Different

Most file tools focus on either a desktop UI, a command line, or an AI demo. FilePilot deliberately connects all three:

The same core services power the desktop app, CLI, and MCP tools.
MCP access is directory-scoped instead of "let the agent browse everything."
Organization is plan-based, so agents can propose changes before anything moves.
Release assets include checksum sidecars and CI verification.
The repository includes issue forms, security policy, roadmap, architecture docs, and workflow prompts for contributors.

Three Ways To Use It

Layer	Best for	Entry point
Desktop app	Visual browsing, previews, search, tags, summaries, duplicate review, and organization planning.	`python -m filepilot.main`
CLI	Repeatable scripts for scanning, searching, exports, disk usage, duplicates, and dry-run organization.	`python -m filepilot.cli`
MCP server	Safe local file tools for Claude Code, Codex, Cursor, Claude Desktop, and other MCP clients.	`filepilot-mcp`

MCP For AI Agents

FilePilot MCP is the most agent-ready part of the project. It exposes useful file operations without handing an agent unrestricted filesystem access.

Safety concern	FilePilot MCP behavior
Filesystem scope	Only directories passed with `--allow` are accessible.
Default permissions	The server starts read-only. Write-like tools require `--write`.
Large or sensitive reads	File size and returned-character limits are enforced.
Hidden paths	Dot-prefixed hidden paths are blocked unless `--allow-hidden` is set.
Organization changes	Plans are dry-run first, saved by ID, discoverable/filterable, then applied only with `confirm=True`.
Auditability	Write-like operations are recorded as JSONL audit events.

Current MCP tools:

server_status, scan_files, search_files, index_folder, search_index,
read_file, extract_file_text, summarize_file, suggest_tags, add_tags,
find_duplicates, propose_organization_plan, list_plans,
cleanup_plans, apply_organization_plan, undo_organization_plan,
list_workflow_templates, get_workflow_template, mcp_client_config

See docs/MCP.md for the full safety model, docs/MCP-CLIENTS.md for Claude Desktop, Claude Code, Cursor, and Codex snippets, docs/MCP-WORKFLOWS.md for built-in agent workflow templates, and docs/ARCHITECTURE.md for the project architecture.

Quick Start

Desktop App

git clone https://github.com/cuiheng511/filepilot-ai.git
cd filepilot-ai

python -m venv .venv

# Windows
.venv\Scripts\activate

# macOS / Linux
source .venv/bin/activate

pip install -r requirements.txt
python -m filepilot.main

Package installs can choose only the needed layer:

pip install "filepilot-ai[desktop]"
pip install "filepilot-ai[mcp]"

MCP Server

Install the MCP extra and allow one local folder:

pip install -e ".[mcp]"
filepilot-mcp --allow ~/Documents --read-only

Allow multiple roots when a task needs both source and target folders:

filepilot-mcp --allow ~/Downloads --allow ~/Sorted --read-only

Enable write-like tools only for trusted sessions:

filepilot-mcp --allow ~/Downloads --allow ~/Sorted --write

Minimal MCP client config:

{
  "mcpServers": {
    "filepilot": {
      "command": "filepilot-mcp",
      "args": ["--allow", "C:\\Users\\you\\Documents", "--read-only"]
    }
  }
}

CLI

# Scan a folder
python -m filepilot.cli scan ~/Documents

# Search indexed files
python -m filepilot.cli search ~/Documents "project notes"

# Find duplicate files
python -m filepilot.cli duplicates ~/Downloads

# Export an inventory report
python -m filepilot.cli export ~/Projects --format csv -o report.csv

# Preview an organization plan before moving anything
python -m filepilot.cli organize ~/Downloads ~/Sorted --dry-run --rules category date

What FilePilot Can Do

Area	Capabilities
Search and indexing	Local full-text search with Whoosh, SQLite metadata filtering, incremental indexing, and optional semantic re-ranking.
File understanding	Text extraction for PDF, DOCX, XLSX, PPTX, Markdown, code, and plain text, with optional summaries.
Organization	Preview-first organization by category, date, extension, or size, with multiple source folders, workflow stages, safety precheck, target slots, Review routing, recent history, and undo.
Duplicate cleanup	Duplicate grouping with size checks, partial hashing, and full SHA-256 verification.
Tags and memory	File tags, saved searches, favorites, tag cloud, and tag automation rules.
Desktop workflows	File browser, previews, AI chat panel, notifications, tray support, themes, and accessibility labels.
Product guidance	First-run onboarding, dashboard workspace status, organize workflow guidance, and a settings view for security and privacy boundaries.
Extensibility	Extractor plugin SDK and plugin registry with safer remote-plugin checks.
Agent workflows	Directory-scoped MCP tools with read limits, discoverable saved plans, write opt-in, apply/undo planning, and audit logs.

Screenshots

Dashboard	File Browser

Search	Tags

Organize	Duplicates

AI Summary	Index

Architecture

flowchart LR
    Desktop["Desktop app"] --> Core["Core services"]
    CLI["CLI"] --> Core
    MCP["MCP server"] --> Guard["Path guard"]
    Guard --> Core
    Core --> Scanner["Scanner"]
    Core --> Indexer["Whoosh + SQLite"]
    Core --> Duplicates["Duplicate finder"]
    Core --> Organizer["Organizer"]
    Core --> Tags["Tags"]
    Scanner --> Extractors["Extractors"]
    Extractors --> Summary["Summaries"]
    Summary --> Providers["Local or configured cloud AI"]

filepilot-ai/
|-- filepilot/
|   |-- ai/                  # AI providers and summarization
|   |-- core/                # Scanner, indexer, organizer, duplicates, tags, operations
|   |-- extractors/          # PDF, Markdown, code, image, Office, OCR extractors
|   |-- mcp/                 # MCP server, tools, audit log, and path safety
|   |-- ui/                  # PySide6 panels and dialogs
|   |-- cli.py               # Command-line interface
|   `-- main.py              # GUI entry point
|-- docs/                    # MCP, build, AI provider, plugin, and release docs
|-- tests/                   # Unit and UI tests
|-- scripts/                 # Build and release helpers
`-- pyproject.toml           # Package metadata and tooling

AI Providers

AI is optional. FilePilot works locally for scanning, indexing, duplicates, tags, and organization planning. When summaries or open-ended chat need a model, FilePilot can use configured local or cloud providers.

Provider	Mode	Default URL
Ollama	Local	`http://localhost:11434`
llama.cpp / vLLM	Local	`http://localhost:8080`
LM Studio	Local	`http://localhost:1234`
OpenAI	Cloud	`https://api.openai.com/v1`
Anthropic	Cloud	`https://api.anthropic.com`
Custom endpoint	Cloud or local	User-defined

See docs/AI-PROVIDERS.md for setup details.

Security And Privacy

Area	Design
Local-first workflow	Scanning, indexing, duplicate detection, tags, and organization planning run locally.
MCP access	Agent access is limited to explicitly allowed directories.
MCP writes	Write-like tools are disabled unless the server starts with `--write`.
MCP audit log	Write-like MCP operations are recorded as JSONL audit events.
Organization apply/undo	Saved organization plans require `--write`, `confirm=True`, and current allowlist validation before any move or restore.
Bounded reads	MCP reads enforce file-size and character limits.
Optional AI	Summaries can use local models or explicitly configured cloud providers.
API keys	Stored with OS keyring when available, with encrypted fallback storage.
Safe deletion	Duplicate cleanup uses the system recycle bin through `send2trash`.
Plugin installs	Registry plugin names are constrained, remote entries require SHA-256 pins, and installs require confirmation.
Telemetry	No analytics, tracking, or background phone-home behavior.

Development

pip install -e ".[test,dev,desktop,mcp]"
ruff check .
ruff format --check .
mypy
python -m pytest

The current test suite covers core services, UI behavior, CLI flows, MCP security, MCP tools, and release helpers.

Documentation

Document	Description
docs/MCP.md	MCP server setup, safety model, tools, and troubleshooting.
docs/MCP-CLIENTS.md	Client snippets for Claude Desktop, Claude Code, Cursor, and Codex.
docs/MCP-WORKFLOWS.md	Built-in agent workflow templates and MCP client config helper notes.
docs/ARCHITECTURE.md	System map, data flow, core services, MCP safety boundary, and extension points.
docs/ROADMAP.md	Near-term quality track, 0.8.x MCP verification, 0.9 desktop confidence work, larger refactors, and contribution ideas.
docs/USE-CASES.md	Practical workflows for Downloads triage, duplicates, summaries, MCP agents, maintenance, and plugins.
docs/AI-PROVIDERS.md	Local and cloud AI provider configuration.
docs/FEATURES.md	Practical notes for newer desktop workflows.
docs/PLUGIN_SDK.md	Extractor plugin SDK and plugin examples.
docs/BUILD.md	Cross-platform packaging guide.
docs/AUTO-UPDATE.md	Auto-update API and troubleshooting.
docs/PROMOTION.md	Project pitches, submission copy, repository topics, and launch checklist.
RELEASING.md	Release process and integrity checks.

Contributing

Contributions are welcome. Please read CONTRIBUTING.md, keep changes focused, and include tests for behavior changes. For security-sensitive behavior, use SECURITY.md. For general help and issue context, see SUPPORT.md.

License

FilePilot AI is released under the MIT License.

FilePilot AI

FilePilot AI

At A Glance

Best For

Why FilePilot Exists

What Makes It Different

Three Ways To Use It

MCP For AI Agents

Quick Start

Desktop App

MCP Server

CLI

What FilePilot Can Do

Screenshots

Architecture

AI Providers

Security And Privacy

Development

Documentation

Contributing

License

Maintenance

Resources

Latest Blog Posts

MCP directory API