Super Mcp Integration 1.0.0

Unlock the full potential of your AI agent with Model Context Protocol (MCP) integration. This capability connects your agent to a vast ecosystem of external tools, APIs, and data sources through multiple MCP servers—including legal databases, weather services, database connectors, and more. By centralizing access, it enables dynamic tool discovery and execution, enhancing flexibility, reliability, and real-time data retrieval. Empower your agent to adapt and perform across diverse domains with robust, scalable integration. box burroughs candidate fjord external php perhaps ljubljana untitled hence michigannto capability sidekick architecture

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:

text

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

Response structure:

json

[
  {
    "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:

text

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

Example - Korean legal search:

text

{
  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:

json

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

For JSON responses:

javascript

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:

json

{
  "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

text

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

Response shows kr-legal:search_statute with:

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

Step 2: Execute search

text

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

Step 3: Parse and present

javascript

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

User-facing response:

text

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

text

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

Call Tool

text

{
  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

• Plugin README: README.md - Installation and configuration
• Real Example: REAL_EXAMPLE_KR_LEGAL.md - Working kr-legal setup
• API Reference: API.md - Technical API details
• Configuration: CONFIGURATION.md - Server configuration guide
• Troubleshooting: TROUBLESHOOTING.md - Common issues and solutions

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.