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What is MCP?

Model Context Protocol (MCP) is Anthropic’s standard for AI agents to use tools. Instead of HTTP requests, AI agents communicate directly via stdio with JSON-RPC 2.0. Syncline supports both REST API (HTTP) and MCP Protocol (stdio). Functionality is identical—choose what fits your architecture.

Why Use MCP?

Zero Latency

No HTTP overhead. Direct process communication.

Native Integration

Works seamlessly with Claude and other MCP-compatible agents.

Stateful

Maintain context across multiple tool calls.

Simpler Auth

No API keys in headers. Auth via environment variables.

Architecture

Available Tools

Find time slots where attendees are available.Input:
  • attendees: Array of emails
  • duration_minutes: Meeting duration (optional)
Output: 5 ranked time slots
Create a calendar event with Google Meet.Input:
  • attendees: Array of emails
  • start_time: ISO 8601 datetime
  • title: Meeting title
  • duration_minutes: Duration (optional)
Output: Meeting details with Google Meet link
Check a single user’s calendar.Input:
  • email: User’s email
  • date_range: Start and end times
Output: Busy and free time slots
Update user scheduling preferences.Input:
  • email: User’s email
  • preferences: New preferences object
Output: Updated preferences

Integration Guides

Claude Desktop

Integrate with Claude Desktop or Claude Code

Python Client

Build custom Python agents

Node.js Client

Build custom Node.js agents

Protocol Spec

Full JSON-RPC 2.0 specification

Quick Example

1. Start MCP Server

2. Send JSON-RPC Request

3. Receive Response

MCP vs REST API

Protocol Flow

1

Initialize

Agent sends initialize method. Server responds with capabilities.
2

List Tools

Agent calls tools/list. Server returns available tools with schemas.
3

Call Tool

Agent calls tools/call with tool name and arguments. Server executes and returns result.
4

Repeat

Agent can call tools multiple times in same session.

Example Conversation

Next Steps

Integrate with Claude

Add Syncline to Claude Desktop

Build Python Client

Create custom Python agent