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mcp-adapterMCP adapter 搜索

Agent Skill

mcp-adapter 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

153,115

周安装

6,510

GitHub Stars

4

下载量

53,642
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:mcp-adapter(MCP adapter 搜索)
来源仓库:https://github.com/lunarpulse/mcp-adapter
安装命令:
openclaw skills install mcp-adapter
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install mcp-adapter

简介

使用模型上下文协议服务器访问外部工具和数据源。使 AI 代理能够从配置的 MCP 服务器(法律数据库、API、数据库连接器、天气服务等)发现并执行工具。

SKILL.md

name
mcp-integration
description
Use Model Context Protocol servers to access external tools and data sources. Enable AI agents to discover and execute tools from configured MCP servers (legal databases, APIs, database connectors, weather services, etc.).
license
MIT

MCP Integration Usage Guide

Overview

Use the MCP integration plugin to discover and execute tools provided by external MCP servers. This skill enables you to access legal databases, query APIs, search databases, and integrate with any service that provides an MCP interface.

The plugin provides a unified mcp tool with two actions:

  • list - Discover available tools from all connected servers
  • call - Execute a specific tool with parameters

Process

🔍 Phase 1: Tool Discovery

1.1 Check Available Tools

Always start by listing available tools to see what MCP servers are connected and what capabilities they provide.

Action:

{
  tool: "mcp",
  args: {
    action: "list"
  }
}

Response structure:

[
  {
    "id": "server:toolname",
    "server": "server-name",
    "name": "tool-name", 
    "description": "What this tool does",
    "inputSchema": {
      "type": "object",
      "properties": {...},
      "required": [...]
    }
  }
]

1.2 Understand Tool Schemas

For each tool, examine:

  • id: Format is "server:toolname" - split on : to get server and tool names
  • description: Understand what the tool does
  • inputSchema: JSON Schema defining parameters

- properties: Available parameters with types and descriptions - required: Array of mandatory parameter names

1.3 Match Tools to User Requests

Common tool naming patterns:

  • search_* - Find or search operations (e.g., search_statute, search_users)
  • get_* - Retrieve specific data (e.g., get_statute_full_text, get_weather)
  • query - Execute queries (e.g., database:query)
  • analyze_* - Analysis operations (e.g., analyze_law)
  • resolve_* - Resolve references (e.g., resolve_citation)

🎯 Phase 2: Tool Execution

2.1 Validate Parameters

Before calling a tool:

  1. Identify all required parameters from inputSchema.required
  2. Verify parameter types match schema (string, number, boolean, array, object)
  3. Check for constraints (minimum, maximum, enum values, patterns)
  4. Ensure you have necessary information from the user

2.2 Construct Tool Call

Action:

{
  tool: "mcp",
  args: {
    action: "call",
    server: "<server-name>",
    tool: "<tool-name>",
    args: {
      // Tool-specific parameters from inputSchema
    }
  }
}

Example - Korean legal search:

{
  tool: "mcp",
  args: {
    action: "call",
    server: "kr-legal",
    tool: "search_statute",
    args: {
      query: "연장근로 수당",
      limit: 5
    }
  }
}

2.3 Parse Response

Tool responses follow this structure:

{
  "content": [
    {
      "type": "text",
      "text": "JSON string or text result"
    }
  ],
  "isError": false
}

For JSON responses:

const data = JSON.parse(response.content[0].text);
// Access data.result, data.results, or direct properties

🔄 Phase 3: Multi-Step Workflows

3.1 Chain Tool Calls

For complex requests, execute multiple tools in sequence:

Example - Legal research workflow:

  1. Search - search_statute to find relevant laws
  2. Retrieve - get_statute_full_text for complete text
  3. Analyze - analyze_law for interpretation
  4. Precedents - search_case_law for related cases

Each step uses output from the previous step to inform the next call.

3.2 Maintain Context

Between tool calls:

  • Extract relevant information from each response
  • Use extracted data as parameters for subsequent calls
  • Build up understanding progressively
  • Present synthesized results to user

⚠ Phase 4: Error Handling

4.1 Common Errors

"Tool not found: server:toolname"

  • Cause: Server not connected or tool doesn't exist
  • Solution: Run action: "list" to verify available tools
  • Check spelling of server and tool names

"Invalid arguments for tool"

  • Cause: Missing required parameter or wrong type
  • Solution: Review inputSchema from list response
  • Ensure all required parameters provided with correct types

"Server connection failed"

  • Cause: MCP server not running or unreachable
  • Solution: Inform user service is temporarily unavailable
  • Suggest alternatives if possible

4.2 Error Response Format

Errors return:

{
  "content": [{"type": "text", "text": "Error: message"}],
  "isError": true
}

Handle gracefully:

  • Explain what went wrong clearly
  • Don't expose technical implementation details
  • Suggest next steps or alternatives
  • Don't retry excessively

Complete Example

User Request: "Find Korean laws about overtime pay"

Step 1: Discover tools

{tool: "mcp", args: {action: "list"}}

Response shows kr-legal:search_statute with:

  • Required: query (string)
  • Optional: limit (number), category (string)

Step 2: Execute search

{
  tool: "mcp",
  args: {
    action: "call",
    server: "kr-legal",
    tool: "search_statute",
    args: {
      query: "연장근로 수당",
      category: "노동법",
      limit: 5
    }
  }
}

Step 3: Parse and present

const data = JSON.parse(response.content[0].text);
// Present data.results to user

User-facing response:

Found 5 Korean statutes about overtime pay:

1. 근로기준법 제56조 (연장·야간 및 휴일 근로)
   - Overtime work requires 50% premium
   
2. 근로기준법 제50조 (근로시간)
   - Standard working hours: 40 hours per week

Would you like me to retrieve the full text of any statute?

Quick Reference

List Tools

{tool: "mcp", args: {action: "list"}}

Call Tool

{
  tool: "mcp",
  args: {
    action: "call",
    server: "server-name",
    tool: "tool-name",
    args: {param1: "value1"}
  }
}

Essential Patterns

Tool ID parsing: "server:toolname" → split on : for server and tool names

Parameter validation: Check inputSchema.required and inputSchema.properties[param].type

Response parsing: JSON.parse(response.content[0].text) for JSON responses

Error detection: Check response.isError === true


Reference Documentation

Core Documentation

Usage Examples

  • Examples Collection: EXAMPLES.md - 13 real-world examples including:

- Legal research workflows - Database queries - Weather service integration - Multi-step complex workflows - Error handling patterns


Remember: Always start with action: "list" when uncertain about available tools.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

91.29%
按下载量换算48,970

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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