| name | freshdesk-mcp-connector |
| description | MCP connector for Freshdesk – enables AI-powered helpdesk management, ticket automation, and knowledge base operations through Claude |
| license | Proprietary/API |
| tags | ["business","support","mcp","freshdesk","helpdesk"] |
| difficulty | intermediate |
| time_to_master | 4-8 weeks |
| version | 1.0.0 |
Freshdesk MCP Connector
Overview
This skill enables Claude to interact with Freshdesk through the Model Context Protocol (MCP). It provides a bridge between Claude's AI capabilities and Freshdesk's REST API, allowing natural language control of Freshdesk operations, intelligent automation, and AI-powered assistance for Freshdesk workflows.
When to Use This Skill
- Ticket management and assignment via AI
- Automation rule creation
- Solution article generation
- Customer satisfaction tracking
- Agent productivity analysis
Architecture
┌─────────────┐ ┌─────────────────┐ ┌──────────────────┐
│ Claude │────▶│ MCP Server │────▶│ Freshdesk │
│ (Client) │◀────│ (TypeScript) │◀────│ (REST API )│
└─────────────┘ └─────────────────┘ └──────────────────┘
Core Concepts
MCP Server Setup
The connector implements an MCP server that exposes Freshdesk operations as tools Claude can invoke. The server translates natural language intentions into REST API calls.
Key Endpoints/Interfaces
/api/v2/tickets, /api/v2/contacts, /api/v2/solutions/articles, /api/v2/automations, /api/v2/canned_responses
Implementation
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";
const server = new McpServer({
name: "freshdesk-mcp-connector",
version: "1.0.0",
});
server.tool(
"list_resources",
"List and query Freshdesk resources with optional filters",
{
query: z.string().optional().describe("Search query or filter"),
limit: z.number().optional().describe("Max results to return"),
},
async ({ query, limit }) => {
const response = await fetch(`${BASE_URL}/api/v2/tickets`, {
headers: { "Authorization": `Bearer ${API_KEY}` },
});
const data = await response.json();
return {
: [{ : , : .(data, , ) }],
};
}
);
server.(
,
,
{
: z.().(),
: z.({}).().().(),
},
({ name, config }) => {
response = (, {
: ,
: {
: ,
: ,
},
: .({ name, ...config }),
});
data = response.();
{
: [{ : , : }],
};
}
);
server.(
,
,
{
: z.().(),
: z.().().(),
},
({ , timeframe }) => {
response = (, {
: { : },
});
data = response.();
{
: [{ : , : .(data, , ) }],
};
}
);
transport = ();
server.(transport);
Claude Desktop Configuration
{
"mcpServers": {
"freshdesk-mcp-connector": {
"command": "node",
"args": ["path/to/freshdesk-mcp-connector/index.js"],
"env": {
"FRESHDESK_API_KEY": "your-api-key",
"FRESHDESK_BASE_URL": "https://your-instance-url"
}
}
}
}
Best Practices
- Authentication: Store API keys securely using environment variables; never hardcode credentials
- Rate Limiting: Implement request throttling to respect Freshdesk API rate limits
- Error Handling: Provide clear, actionable error messages for common failure scenarios
- Pagination: Handle paginated responses for large datasets efficiently
- Caching: Cache frequently accessed read-only data to reduce API calls
- Security: Validate all inputs before passing to the Freshdesk API; sanitize outputs
- Logging: Log all API interactions for debugging and audit purposes
Example Prompts
"Create canned responses for the top 10 frequently asked questions and set up auto-assignment rules"
Security Considerations
- All API credentials must be stored as environment variables
- Implement input validation and sanitization for all tool parameters
- Use HTTPS for all API communications
- Follow the principle of least privilege for API token permissions
- Audit log all write operations for compliance tracking
Resources
Changelog
| Version | Date | Changes |
|---|
| 1.0.0 | 2026-04-01 | Initial MCP connector skill |
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