OpenClaw Integration Guide: Fast.io MCP Tools

OpenClaw Integration Guide: Overview

OpenClaw is an open-source personal AI assistant. It runs locally on Mac, Windows, or Linux. It manages emails, calendars, files, and more through chat apps like WhatsApp, Telegram, Discord, Slack, or iMessage. Check OpenClaw site for details.

Fast.io offers workspaces where agents and humans collaborate on files. The ClawHub skill (clawhub install dbalve/fast-io) connects OpenClaw to Fast.io's MCP server. It provides 14 of 251 MCP tools.

Tools cover file operations, workspace management, AI chat with RAG, shares, comments, metadata, webhooks, URL imports from Google Drive/Dropbox/OneDrive, file locks, and ownership transfer.

OpenClaw agents get 50GB free storage, 1GB max file size. Semantic search on documents, branded Send/Receive/Exchange portals, comments on images/videos/PDFs, project handoff to humans (agent keeps admin). Free tier: 5,000 credits/month. Storage 100/GB, bandwidth 212/GB, AI tokens 1/100 tokens. No credit card needed.

Prerequisites

Install OpenClaw from official docs. Try: curl -fsSL https://openclaw.ai/install.sh | bash or npm i -g openclaw, then openclaw onboard.

Get a Fast.io agent account at fast.io, no credit card, permanent free tier. Includes 50GB storage, 5,000 credits/month, MCP access.

Install ClawHub CLI: npm i -g @clawhub/cli. Check ClawHub docs.

These prerequisites ensure OpenClaw compatibility with ClawHub skills and Fast.io's MCP server, enabling cloud-based file management without local storage constraints.

Add one practical example, one implementation constraint, and one measurable outcome so the section is concrete and useful for execution.

Teams should validate this approach in a small test path first, then standardize it across environments once metrics and outcomes are stable.

Install Fast.io ClawHub Skill

Run in terminal:

clawhub install dbalve/fast-io
      ```

Adds 14 tools to OpenClaw. No env vars, dashboard, or upfront API keys, auth handles it.

Restart OpenClaw or `openclaw skills refresh`. Ask "List my Fast.io tools." See `workspace-list`, `file-upload`, `ai-chat`, etc.

**Pro tip:** `clawhub update dbalve/fast-io` for updates.

This installation provides OpenClaw with 14 MCP tools like workspace management, file CRUD, AI chat, and shares, directly from natural language commands.

Add one practical example, one implementation constraint, and one measurable outcome so the section is concrete and useful for execution.

Teams should validate this approach in a small test path first, then standardize it across environments once metrics and outcomes are stable.

Authenticate with Fast.io

Chat OpenClaw: "Sign into Fast.io".

Options:

• API Key (simple): Paste from Fast.io Settings > API Keys. Never expires.
• PKCE Login (secure): Browser URL from OpenClaw, approve, paste code. Scoped access.
• Signup: Auto agent account, email verify, free tier.

Sessions persist. JWT 1 hour; keys permanent. Check: "Fast.io session status?"

Example:

User: Sign into Fast.io with API key sk-abc123...
OpenClaw: Authenticated as agent@example.com. Active until [time].

These authentication options offer flexibility: API keys for simplicity and permanence, PKCE for enhanced security without sharing credentials.

Document access rules, audit trails, and retention policies before rollout so staging results are repeatable in production. This avoids late surprises and helps teams debug issues with confidence.

Integration Steps Table

Steps to connect:

Test in chat.

This table outlines the essential integration sequence; each command demonstrates practical Fast.io usage within OpenClaw chats.

Key Workflows

Main tasks:

File Operations: Upload local files, import URLs (Google Drive, Dropbox, OneDrive via OAuth, no local download). List, download, semantic search ("contracts with indemnity").

Example: "Upload my local report.pdf to workspace 'project' root."

Workspace Management: Create/list, invite members (agents/humans), enable Intelligence Mode for RAG.

Example: "Create Fast.io workspace 'Q1-reports' with intelligence enabled. Invite team@example.com as admin."

AI Chat & RAG: "Summarize Q1 reports in 'project' workspace." Citations included, attachments ok.

Shares: Send/Receive/Exchange portals, passwords, expiry, branding.

Example: "Create a Send share for 'project' with password, expires in 30 days, branded for Acme Corp."

Ownership Transfer: Create transfer token/claim URL, handoff to human (agent admin retained).

Example: "Transfer ownership of my org to client@example.com."

Advanced: File locks, webhooks, anchored comments, metadata.

Advanced Features

Extra capabilities:

File Locks: Acquire/release for safe multi-agent work.

Example: "Lock file report.pdf in workspace before editing."

Webhooks: Events (upload, change, access), reactive, no polling.

URL Import: OAuth from Google Drive, OneDrive, Dropbox/Box. Server fetch.

Anchored Comments: Pin to image regions, video timestamps, PDF pages. Threads, reactions.

Metadata: Fields on files (string/int/bool/json), AI extract, query.

Notes: Markdown in tree, RAG indexed.

Example: "Pin a comment on frame 45s of video.mp4 saying 'adjust color here'."

These features support advanced multi-agent scenarios, such as concurrent editing with locks and real-time notifications via webhooks.

Add one practical example, one implementation constraint, and one measurable outcome so the section is concrete and useful for execution.

ClawHub Tools Reference

14 tools from Fast.io MCP:

Full docs: MCP Skill Guide

Evidence: Benchmarks & Stats

Fast.io stats:

• HLS video streaming loads 50-60% faster than progressive download.
• Free agent tier: 50GB storage, 5,000 credits/mo (covers ~50GB storage + 20GB bandwidth + heavy AI).
• RAG indexing: 10 credits/page, auto for docs/code.
• 251 MCP tools total; ClawHub uses 14 core ones.
• Token expiry: 1 hour for JWT, permanent API keys.

Supports agent workflows without extra infrastructure.

Fast.io's benchmarks confirm its suitability for production OpenClaw integrations, balancing cost, speed, and reliability.

Add one practical example, one implementation constraint, and one measurable outcome so the section is concrete and useful for execution.

Teams should validate this approach in a small test path first, then standardize it across environments once metrics and outcomes are stable.