footprinter-cli 1.0.4

A local context layer for your files, browser history, chats, and email — searchable, user-owned, MCP-served.

Footprinter

A local context layer for your files, browser history, chats, and email — searchable, user-owned, and served to AI agents through MCP.

Your work lives across filesystems, browsers, inboxes, chat histories, and other tools. Footprinter indexes those sources into a single local store, organizes them into the projects and groupings you define, and serves the result to AI agents through a governed access layer. You control what the agent can see. Everything stays on your machine.

Install

Requires Python 3.11+ and macOS 13+ or Linux. The install script checks your Python version and handles the rest:

curl -fsSL https://raw.githubusercontent.com/harringjohn/footprinter-cli/main/scripts/release/install.sh | bash

Or install with pipx directly:

pipx install footprinter-cli

Either method gives you the fp command with the indexing pipeline, CLI, MCP server, and HTTP API. Optional extras add more:

Extra	What it adds
[semantic]	Semantic search via ChromaDB + ONNX embeddings
[parse]	PDF, Word, Excel, PowerPoint content extraction
[full]	Both of the above

To install with extras: use the full install script, or pipx install 'footprinter-cli[full]'.

Troubleshooting & alternative install methods

Python version: Stock macOS ships Python 3.9. Install 3.11+ from python.org or brew install python@3.11.

macOS caveats:

• zsh treats [...] as a glob — quote extras specifiers: 'footprinter-cli[full]'
• System/Homebrew Python blocks bare pip install (PEP 668) — use pipx or a venv instead

Inside an existing venv: pip install footprinter-cli works as expected.

Full Disk Access: Required for browser history indexing on macOS. fp setup will prompt you when needed.

ChromaDB telemetry: Footprinter sets anonymized_telemetry=False. ChromaDB also removed product telemetry in v1.5.4. See Chroma OSS overview.

Uninstall

fp uninstall                        # remove MCP entry + user data
pipx uninstall footprinter-cli      # remove the package

Quick Start

fp setup     # Configure sources (interactive wizard)
fp ingest    # Index your files
fp status    # See what's indexed
fp search "meeting notes"   # Find things

A few first-run notes:

• The first ingest is implicitly full; subsequent runs are incremental. If you change exclusions or add directories after the first run, re-run with fp ingest --full so previously skipped files get picked up.
• With [semantic] or [full], the first ingest downloads ~80MB of ONNX embedding model weights. It's a one-time cost — subsequent ingests are fast.
• Keep the directories you want indexed outside ~/Downloads — the default exclusion list skips it.

Connect to Claude Desktop

Footprinter includes an MCP server that gives Claude Desktop (or any MCP client) structured access to your indexed data:

fp setup mcp --claude    # Configure MCP for Claude Desktop

After running this, fully quit Claude Desktop (Cmd+Q) and relaunch before the Footprinter tools appear in the conversation tools list. A simple window close isn't enough — the app keeps running in the menu bar.

Once configured, Claude can search your files, browse projects, and find related conversations — through natural language.

What It Indexes

Source	What's captured
Local files	Path, type, size, timestamps, content hash
Browser history	Safari and Chrome — URLs, titles, visit times
Chat exports	Claude and ChatGPT conversation exports
Email	Subject, sender, recipients, body, timestamps
Documents	PDF, Word, Excel, PowerPoint content (with [parse] extra)
Semantic embeddings	Conceptual similarity across all sources (with [semantic] extra)

What lands in the database — and when — is controlled by the content storage tier you opt into. By default, Footprinter only indexes metadata; it does not read your file content until you explicitly enable it. See Content Storage for the full breakdown.

CLI Commands

All commands use the fp entry point.

Command	Purpose
fp setup	Configure sources and integrations
fp ingest	Run the indexing pipeline
fp status	System health and data counts
fp search	Search across all indexed sources
fp connect	Manage optional integrations
fp mcp	MCP server and access policies
fp api	Start the HTTP API server
fp view	Browse indexed data (files, folders, projects, clients, chats, emails, visits)
fp upsert	Create/update records, assign relationships, or soft-delete via --status removed
fp data	Export data, generate templates, or import metadata corrections
fp delete	Hard-delete a super entity (irreversible)
fp vectorize	Manage per-record vectorization control
fp doctor	Post-install health check (Python version, install location, FDA, MCP wiring)
fp uninstall	Remove Footprinter — MCP entry, user data, package

Run fp <command> --help for full usage.

Architecture

Single-process CLI with optional MCP server. SQLite database. No containers, no cloud, no accounts.

Sources are scanned into SQLite with bidirectional links connecting local files to remote backups via content hash matching. Embeddings are generated at ingest time for semantic search. The MCP server exposes indexed data with two-layer access control (visibility + permissions) — you decide what agents can see.

Documentation

• Interfaces — CLI commands, MCP tools, Python API
• Data Model — database schema
• Pipeline — indexing stages and configuration
• Content Storage — metadata vs. snippet vs. full-content tiers
• Access Control — MCP security model

Contributing

Bug fixes, documentation, and tests welcome. For new features or architectural changes, open an issue first to discuss the approach.

Development setup

git clone https://github.com/harringjohn/footprinter-cli.git
cd footprinter
python3 -m venv venv
./venv/bin/pip install -e ".[dev]"

Running tests

./venv/bin/pytest tests/ -v --tb=short

Code style

• PEP 8
• Type hints on function signatures
• logging over print() in library code

Workflow

1. Fork the repository
2. Create a feature branch from main
3. Write tests (TDD preferred — tests before implementation)
4. Run the test suite
5. Submit a PR targeting main

Never commit API keys, tokens, or credentials. Report security vulnerabilities privately — see SECURITY.md.

Pull request expectations

• Tests must pass
• No breaking changes to existing CLI commands
• Fill out the PR template
• One logical change per PR

All PRs are reviewed by the maintainer. Expect reviews within one week. CI must pass before review begins.

No Contributor License Agreement required. By submitting a PR, you agree your contribution is licensed under the project's MIT License.

Community

• Code of Conduct
• Security Policy

License

MIT — see LICENSE.