Freshdesk▌
by effytech
Automate support with Freshdesk! Use AI customer service to manage tickets, improve workflows, and elevate your customer
Integrate AI models with Freshdesk to automate support operations. Create, update, and manage support tickets seamlessly through the Freshdesk API. Enhance your customer support experience with automated ticket management and AI-driven interactions.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Customer support teams automating ticket workflows
- / AI-powered helpdesk automation
- / Support operation managers tracking ticket metrics
capabilities
- / Create support tickets with custom fields
- / Update existing ticket status and details
- / Search tickets by various criteria
- / Delete tickets from the system
- / Retrieve ticket field configurations
- / List all support tickets with pagination
what it does
Connects AI models to Freshdesk's support platform for automated ticket management and customer service operations.
about
Freshdesk is a community-built MCP server published by effytech that provides AI assistants with tools and capabilities via the Model Context Protocol. Automate support with Freshdesk! Use AI customer service to manage tickets, improve workflows, and elevate your customer It is categorized under developer tools.
how to install
You can install Freshdesk in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Freshdesk is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
Freshdesk MCP Server
An MCP server implementation that integrates with Freshdesk, enabling AI models to interact with Freshdesk modules and perform various support operations.
Features
- Freshdesk Integration: Seamless interaction with Freshdesk API endpoints
- AI Model Support: Enables AI models to perform support operations through Freshdesk
- Automated Ticket Management: Handle ticket creation, updates, and responses
Components
Tools
The server offers several tools for Freshdesk operations:
-
create_ticket: Create new support tickets- Inputs:
subject(string, required): Ticket subjectdescription(string, required): Ticket descriptionsource(number, required): Ticket source codepriority(number, required): Ticket priority levelstatus(number, required): Ticket status codeemail(string, optional): Email of the requesterrequester_id(number, optional): ID of the requestercustom_fields(object, optional): Custom fields to set on the ticketadditional_fields(object, optional): Additional top-level fields
- Inputs:
-
update_ticket: Update existing tickets- Inputs:
ticket_id(number, required): ID of the ticket to updateticket_fields(object, required): Fields to update
- Inputs:
-
delete_ticket: Delete a ticket- Inputs:
ticket_id(number, required): ID of the ticket to delete
- Inputs:
-
search_tickets: Search for tickets based on criteria- Inputs:
query(string, required): Search query string
- Inputs:
-
get_ticket_fields: Get all ticket fields- Inputs:
- None
- Inputs:
-
get_tickets: Get all tickets- Inputs:
page(number, optional): Page number to fetchper_page(number, optional): Number of tickets per page
- Inputs:
-
get_ticket: Get a single ticket- Inputs:
ticket_id(number, required): ID of the ticket to get
- Inputs:
-
get_ticket_conversation: Get conversation for a ticket- Inputs:
ticket_id(number, required): ID of the ticket
- Inputs:
-
create_ticket_reply: Reply to a ticket- Inputs:
ticket_id(number, required): ID of the ticketbody(string, required): Content of the reply
- Inputs:
-
create_ticket_note: Add a note to a ticket- Inputs:
ticket_id(number, required): ID of the ticketbody(string, required): Content of the note
- Inputs:
-
update_ticket_conversation: Update a conversation- Inputs:
conversation_id(number, required): ID of the conversationbody(string, required): Updated content
- Inputs:
-
view_ticket_summary: Get the summary of a ticket- Inputs:
ticket_id(number, required): ID of the ticket
- Inputs:
-
update_ticket_summary: Update the summary of a ticket- Inputs:
ticket_id(number, required): ID of the ticketbody(string, required): New summary content
- Inputs:
-
delete_ticket_summary: Delete the summary of a ticket- Inputs:
ticket_id(number, required): ID of the ticket
- Inputs:
-
get_agents: Get all agents- Inputs:
page(number, optional): Page numberper_page(number, optional): Number of agents per page
- Inputs:
-
view_agent: Get a single agent- Inputs:
agent_id(number, required): ID of the agent
- Inputs:
-
create_agent: Create a new agent- Inputs:
agent_fields(object, required): Agent details
- Inputs:
-
update_agent: Update an agent- Inputs:
agent_id(number, required): ID of the agentagent_fields(object, required): Fields to update
- Inputs:
-
search_agents: Search for agents- Inputs:
query(string, required): Search query
- Inputs:
-
list_contacts: Get all contacts- Inputs:
page(number, optional): Page numberper_page(number, optional): Contacts per page
- Inputs:
-
get_contact: Get a single contact- Inputs:
contact_id(number, required): ID of the contact
- Inputs:
-
search_contacts: Search for contacts- Inputs:
query(string, required): Search query
- Inputs:
-
update_contact: Update a contact- Inputs:
contact_id(number, required): ID of the contactcontact_fields(object, required): Fields to update
- Inputs:
-
list_companies: Get all companies- Inputs:
page(number, optional): Page numberper_page(number, optional): Companies per page
- Inputs:
-
view_company: Get a single company- Inputs:
company_id(number, required): ID of the company
- Inputs:
-
search_companies: Search for companies- Inputs:
query(string, required): Search query
- Inputs:
-
find_company_by_name: Find a company by name- Inputs:
name(string, required): Company name
- Inputs:
-
list_company_fields: Get all company fields- Inputs:
- None
- Inputs:
Getting Started
Installing via Smithery
To install freshdesk_mcp for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @effytech/freshdesk_mcp --client claude
Prerequisites
- A Freshdesk account (sign up at freshdesk.com)
- Freshdesk API key
uvxinstalled (pip install uvorbrew install uv)
Configuration
- Generate your Freshdesk API key from the Freshdesk admin panel
- Set up your domain and authentication details
Usage with Claude Desktop
- Install Claude Desktop if you haven't already
- Add the following configuration to your
claude_desktop_config.json:
"mcpServers": {
"freshdesk-mcp": {
"command": "uvx",
"args": [
"freshdesk-mcp"
],
"env": {
"FRESHDESK_API_KEY": "<YOUR_FRESHDESK_API_KEY>",
"FRESHDESK_DOMAIN": "<YOUR_FRESHDESK_DOMAIN>"
}
}
}
Important Notes:
- Replace
YOUR_FRESHDESK_API_KEYwith your actual Freshdesk API key - Replace
YOUR_FRESHDESK_DOMAINwith your Freshdesk domain (e.g.,yourcompany.freshdesk.com)
Example Operations
Once configured, you can ask Claude to perform operations like:
- "Create a new ticket with subject 'Payment Issue for customer A101' and description as 'Reaching out for a payment issue in the last month for customer A101', where customer email is [email protected] and set priority to high"
- "Update the status of ticket #12345 to 'Resolved'"
- "List all high-priority tickets assigned to the agent John Doe"
- "List previous tickets of customer A101 in last 30 days"
Testing
For testing purposes, you can start the server manually:
uvx freshdesk-mcp --env FRESHDESK_API_KEY=<your_api_key> --env FRESHDESK_DOMAIN=<your_domain>
Troubleshooting
- Verify your Freshdesk API key and domain are correct
- Ensure proper network connectivity to Freshdesk servers
- Check API rate limits and quotas
- Verify the
uvxcommand is available in your PATH
License
This MCP server is licensed under the MIT License. See the LICENSE file in the project repository for full details.
FAQ
- What is the Freshdesk MCP server?
- Freshdesk is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Freshdesk?
- This profile displays 66 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
List & Promote Your MCP Server
Share your MCP server with the developer community
Ratings
4.6★★★★★66 reviews- ★★★★★Emma Liu· Dec 28, 2024
Useful MCP listing: Freshdesk is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Kwame Brown· Dec 24, 2024
We wired Freshdesk into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Pratham Ware· Dec 20, 2024
Freshdesk is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★James Nasser· Dec 20, 2024
According to our notes, Freshdesk benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Aditi Sethi· Dec 20, 2024
We evaluated Freshdesk against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Mia Gonzalez· Dec 16, 2024
I recommend Freshdesk for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Lucas Sanchez· Nov 19, 2024
Freshdesk is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Sakshi Patil· Nov 11, 2024
We evaluated Freshdesk against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Ama Wang· Nov 11, 2024
Freshdesk is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Mia Diallo· Nov 7, 2024
Strong directory entry: Freshdesk surfaces stars and publisher context so we could sanity-check maintenance before adopting.
showing 1-10 of 66