How to Setup MCP Servers in OpenAI Platform

This guide shows you how to configure MCP servers in OpenAI's chat platform (https://platform.openai.com).

Available MCP Servers

Server	Endpoint	Purpose
Companies	https://ask.sonalabs.com/mcp/data-activation-companies	Query company/account data
Visitors	https://ask.sonalabs.com/mcp/data-activation-visitors	Query visitor data
Revenue	https://ask.sonalabs.com/mcp/revenue	Query revenue/system reports
Outbound	https://ask.sonalabs.com/mcp/outbound	Query outbound campaign engagements
Sales Prioritization	https://ask.sonalabs.com/mcp/sales-prioritization	Query sales prioritization data

Setup Instructions

Step 1: Add MCP Server to OpenAI Platform

1. Go to your OpenAI platform chat configuration
2. Add a new MCP server with:
   • Server URL: Choose from the endpoints above (e.g., https://ask.sonalabs.com/mcp/data-activation-companies)
   • Authentication Header:

     x-api-key: your-organization-api-key

Step 2: Configure System Instructions

Add these mandatory system instructions to your OpenAI chat configuration:

# MCP Server Usage Instructions

You have access to MCP tools for querying data. These tools MUST be used in a specific order.

## CRITICAL WORKFLOW - NEVER SKIP THIS

For EVERY data query, you MUST follow this exact sequence:

### Step 1: Call Schema Tool FIRST

- Tool: `[domain]-schema-tool` (e.g., `companies-schema-tool`)
- Parameters: None required
- Purpose: Get exact field names and types
- **DO NOT SKIP THIS STEP**

### Step 2: Review Schema Response

- Read the `mapping` object for exact field names (case-sensitive)
- Read the `field_instructions` for usage guidance
- Note which fields require `.keyword` suffix

### Step 3: Call Compute Tool

- Tool: `[domain]-compute-tool` (e.g., `companies-compute-tool`)
- Parameters: Elasticsearch query using EXACT field names from schema
- Use field names character-for-character as returned in schema

### Step 4: Analyze Results

- Present findings to user

## ERRORS TO AVOID

❌ **NEVER** call compute tool without first calling schema tool
❌ **NEVER** guess field names - always use exact names from schema
❌ **NEVER** skip the schema step "to save time" - it will cause failures

If you call the compute tool without the schema, the query WILL fail.

## Example Correct Flow

User: "Show me high-intent companies"

Your actions:

1. Call `companies-schema-tool` → Get field mapping
2. Review response → See that "Intent" field exists, is type "long"
3. Call `companies-compute-tool` with query:
   ```json
   {
     "query": { "range": { "Intent": { "gte": 50 } } },
     "_source": ["Name", "Domain", "Uuid", "Intent"],
     "size": 20
   }
   ```

4. Present results to user

When analyzing data:

• Use exact field names from schema (case-sensitive)
• Apply date filters for time-based queries
• Include relevant fields in _source for list queries
• Use aggregations for counts and breakdowns

### Step 3: Test the Setup

Test with a simple query to verify everything works:

**Test Query**: "Show me companies with high ICP scores"

**Expected Behavior**:
1. First tool call: `companies-schema-tool` (no parameters)
2. Second tool call: `companies-compute-tool` with proper query
3. Results displayed

If the schema tool is skipped, check that:
- System instructions are properly configured
- Server is accessible and authenticated
- Tool descriptions are loading correctly

## That's It!

Your MCP server is now configured and ready to use in OpenAI platform.