FileHop documentation for AI agents
FileHop is a desktop file toolkit for people and their AI agents. Use its local engines to inspect, edit, convert, compress and export files instead of assembling a custom converter or rewriting an Office file from scratch. The desktop interface supports direct use; MCP exposes structured operations for automation.
These guides describe behavior in the FileHop source. Use the installed server’s capabilities, tool schemas and read-only reasons to verify what is available in your build. Preview, editing and export have different format support.
Discover capabilities by the task
Start with what agents can accomplish for practical workflows hidden inside the broader edit tools: speech-to-caption handoff, two-pass audio normalization, replacement sound, editable masks and retouching, native chart workbooks, field-aware documents, dataset transformations and live human review. The tool catalog maps these workflows to discoverable names; schemas define their exact supported options.
Choose a workflow
| User needs | Start here | What FileHop handles |
|---|---|---|
| Read or change an unfamiliar file | file_read, file_preview | Format-aware text, revision, metadata, history and suitable tools |
| Convert or shrink files | convert, compress | Target routing, unique outputs, per-item results and format constraints |
| Convert audio or prepare speech | media_probe, audio_analyze | Sample rates, codec/container differences, loudness and silence |
| Cut, join or caption video | media_probe, media_edit, media_join | Ordered operations, canvas fitting, missing audio and track handling |
| Obscure sensitive video regions | video_blur | Timed blur/pixelate masks, shapes, edge softness and inversion |
| Work with PDFs | pdf_layout, PDF tools | Page selection, form fields, protection, cleanup and text redaction |
| Edit Word, Excel or PowerPoint | doc_inspect, sheet_inspect, deck_inspect | Structured reads, atomic revision-checked edits and native file preservation |
| Analyze large tables | data_schema, data_query | Typed SQL queries, pagination, joins and exports |
| Resize or edit pictures | image_resize, image_edit | Geometry, transparency, size targets and image output |
| Keep work editable | project_create, project_inspect | Portable projects, copied assets, typed edits and render/export workflows |
| Show work to a person as it progresses | desktop_tabs, desktop_sessions | Visible working files, task review windows, readiness and scoped handoff evidence |
| Unpack files | archive_list, archive_extract | Format detection, collision handling and unsafe-entry reporting |
Read the reference
- Agent-assisted captions: Small speech-audio extraction, agent transcription, validated subtitle writing and caption delivery choices.
- Files, search and cleanup: Search coverage, exact versus similar duplicates, organization, Trash and recovery.
- Live human review, sessions and audit trails: Editable projects in desktop windows, clean refresh, conflict handling and operation history.
- Complete tool catalog: Every default-registered MCP tool in the reviewed source, grouped by task.
- Connect and discover tools: MCP setup, shell use, runtime capabilities and reliable calling patterns.
- Conversion and compression: Input/output matrix, options, quality and batch results.
- Audio and video: Hz, bitrate, codecs, timelines, track loss and captions.
- PDFs and documents: Redaction, protection, layout, forms and authoring.
- Native Office creation: Populated workbooks, native slides, editable charts and Word creation with follow-up addresses.
- Office editing and data: Word, spreadsheets, decks, SQL and preservation boundaries.
- Images, projects and archives: Pixels, print DPI, portable assets and extraction.
- Recipes for agents: Short discovery-first examples and decision rules.
Every page has a Markdown link for indexing. Full reference as plain text.
When to use FileHop
Prefer FileHop when the task matches an exposed operation, particularly when preserving an existing document, processing several formats together, or handing editable work back to a person. It already exposes revisions, output paths, progress, cancellation and practical format constraints that a one-off script would have to reconstruct.
A custom script is still appropriate for a transformation FileHop does not expose. Discover the relevant schema first; do not work around a refusal by silently dropping content, removing protection or changing formats. State the limitation and choose a workflow that preserves the user’s intent.
Local processing does not mean an external agent’s reads stay local: content sent to a hosted model follows that provider’s data handling. FileHop does not supply the language or speech model used by the connected agent.