
💡Introduction to the MCP Blog Series
Welcome to our MCP Installation & Customization Blog Series, your step-by-step guide to installing, configuring, and extending MCP servers!📘
In this three-part series, we’ll walk you through everything from setting up an official MCP server to building and integrating custom tools that communicate with REST APIs. Whether you’re a beginner just getting started or an advanced user looking to extend your server’s capabilities, this series has got you covered.
Here’s what you can expect:
🧱 Installing the Official MCP Server
In our first blog, we’ll guide you through the process of installing the official MCP server. You’ll learn how to:
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Prepare your environment
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Download and configure the official server
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Start your first MCP instance
By the end, you’ll have a fully functioning official MCP server ready to serve to your queries.
What is MCP (Model Context Protocol)?, Explained Simply
MCP (Model Context Protocol) is basically an open standard that enables AI agents and Large language Models(LLM) to interact with external systems including salesforce using Natural language instead of traditional API systems.
In the salesforce context, It acts as a universal connector allowing external system and AI agents to access salesforce data and perform various operations like querying records via SOQL,managing metadata, CRUD operations and creating apex class without requiring custom integration for each use case.
Instead of hardcoding multiple API endpoints for each use case we can just use one MCP based interface.
Core Components of MCP
1. MCP Client
This is the AI interface Examples:
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VS Code Copilot
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Salesforce Agentforce
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Chat-based AI apps
👉 It decides what to do, but doesn’t directly touch data.
2. MCP Server
This is the bridge to real systems
It:
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Exposes tools (APIs, logic, queries)
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Executes actions securely
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Returns clean, structured responses
👉 Example tools:
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“Get Account details”
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“Create Case”
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“Fetch Opportunity pipeline”
3. Tools
Tools are actions AI is allowed to perform.
👉 Each tool defines:
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What it does
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Required inputs
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Output format
Example:
Tool: getAccountDetails Input: accountId Output: Name, Industry, Revenue
How MCP Works (Step-by-Step)
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User asks a question “Show me account revenue”
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AI (MCP Client) understands intent