deBridge MCP Skill
Enable AI agents to execute non-custodial cross-chain cryptocurrency swaps and transfers via the deBridge protocol.
Best use case
deBridge MCP Skill is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Enable AI agents to execute non-custodial cross-chain cryptocurrency swaps and transfers via the deBridge protocol.
Teams using deBridge MCP Skill should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/debridge-mcp/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How deBridge MCP Skill Compares
| Feature / Agent | deBridge MCP Skill | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Enable AI agents to execute non-custodial cross-chain cryptocurrency swaps and transfers via the deBridge protocol.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
Best AI Skills for Claude
Explore the best AI skills for Claude and Claude Code across coding, research, workflow automation, documentation, and agent operations.
AI Agents for Marketing
Discover AI agents for marketing workflows, from SEO and content production to campaign research, outreach, and analytics.
AI Agents for Startups
Explore AI agent skills for startup validation, product research, growth experiments, documentation, and fast execution with small teams.
SKILL.md Source
# deBridge MCP Skill
Enable AI agents to execute non-custodial cross-chain cryptocurrency swaps and transfers via the deBridge protocol.
## What It Does
- **Cross-chain swaps**: Find optimal routes and execute trades across 20+ chains
- **Transfer assets**: Move tokens between chains with better rates than traditional bridges
- **Fee estimation**: Check fees and conditions before executing
- **Non-custodial**: Assets never leave user control
## Installation
```bash
# Clone the MCP server
git clone https://github.com/debridge-finance/debridge-mcp.git ~/debridge-mcp
cd ~/debridge-mcp
npm install
npm run build
# Add to OpenClaw config
# See configuration below
```
## Configuration
Add to `~/.openclaw/openclaw.json`:
```json
{
"plugins": {
"entries": {
"mcp-adapter": {
"enabled": true,
"config": {
"servers": [
{
"name": "debridge",
"transport": "stdio",
"command": "node",
"args": ["/home/ubuntu/debridge-mcp/dist/index.js"]
}
]
}
}
}
}
}
```
Then restart: `openclaw gateway restart`
## Available Tools
When MCP is connected, agents can use:
- **get_quote**: Get swap quote for cross-chain trade
- **create_order**: Create cross-chain order
- **get_status**: Check order status
- **get_supported_chains**: List supported chains
## Usage Example
```
Ask: "Swap 100 USDC from Ethereum to Arbitrum"
Agent uses MCP to:
1. Get quote for USDC → USDC on Arbitrum
2. Show estimated receive amount and fees
3. Create order if user confirms
4. Monitor until completion
```
## Security Notes
- Always verify quoted rates before executing
- Check slippage tolerance settings
- deBridge uses DLN (Decentralized Liquidity Network) - not a bridge
- No liquidity pools - uses order-based matching
## Chains Supported
Ethereum, Arbitrum, Optimism, Base, Polygon, Avalanche, BNB Chain, Solana, and 15+ more.
---
**Skill by**: Avi (github.com/aviclaw)Related Skills
---
name: article-factory-wechat
humanizer
Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.
find-skills
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
tavily-search
Use Tavily API for real-time web search and content extraction. Use when: user needs real-time web search results, research, or current information from the web. Requires Tavily API key.
baidu-search
Search the web using Baidu AI Search Engine (BDSE). Use for live information, documentation, or research topics.
agent-autonomy-kit
Stop waiting for prompts. Keep working.
Meeting Prep
Never walk into a meeting unprepared again. Your agent researches all attendees before calendar events—pulling LinkedIn profiles, recent company news, mutual connections, and conversation starters. Generates a briefing doc with talking points, icebreakers, and context so you show up informed and confident. Triggered automatically before meetings or on-demand. Configure research depth, advance timing, and output format. Walking into meetings blind is amateur hour—missed connections, generic small talk, zero leverage. Use when setting up meeting intelligence, researching specific attendees, generating pre-meeting briefs, or automating your prep workflow.
self-improvement
Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.
botlearn-healthcheck
botlearn-healthcheck — BotLearn autonomous health inspector for OpenClaw instances across 5 domains (hardware, config, security, skills, autonomy); triggers on system check, health report, diagnostics, or scheduled heartbeat inspection.
linkedin-cli
A bird-like LinkedIn CLI for searching profiles, checking messages, and summarizing your feed using session cookies.
notebooklm
Google NotebookLM 非官方 Python API 的 OpenClaw Skill。支持内容生成(播客、视频、幻灯片、测验、思维导图等)、文档管理和研究自动化。当用户需要使用 NotebookLM 生成音频概述、视频、学习材料或管理知识库时触发。
小红书长图文发布 Skill
## 概述