Famulor▌
by bekservice
Famulor — Voice agent platform for automated phone calls: configure assistants, manage campaigns, send SMS, and run mid-
Voice agent platform for phone calling, assistant configuration, campaign management, SMS messaging, and mid-call tool execution for automated voice interactions.
github stars
★ 1
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Sales teams automating outbound calls
- / Customer support with AI voice agents
- / Developers building voice interaction workflows
- / Businesses running phone campaigns
capabilities
- / Make AI-powered phone calls
- / Manage voice assistants and configurations
- / Retrieve call transcripts and recordings
- / Configure call campaigns
- / Send SMS messages
- / Execute tools during active calls
what it does
Voice agent platform that enables AI-powered phone calls through ChatGPT and other MCP clients. Make calls, manage voice assistants, and retrieve call transcripts and recordings.
about
Famulor is a community-built MCP server published by bekservice that provides AI assistants with tools and capabilities via the Model Context Protocol. Famulor — Voice agent platform for automated phone calls: configure assistants, manage campaigns, send SMS, and run mid- It is categorized under communication, developer tools.
how to install
You can install Famulor 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 supports remote connections over HTTP, so no local installation is required.
license
NOASSERTION
Famulor is released under the NOASSERTION license.
readme
🤖 Famulor MCP Server
An MCP (Model Context Protocol) server for the Famulor Voice Agent Platform that enables AI-powered phone calls, assistant management, and call data retrieval through ChatGPT and other MCP-compatible clients.

Demo Video
https://www.youtube.com/watch?v=OMQeTiBNW3Q
Overview
This MCP server provides access to the Famulor Voice Agent Platform, allowing users to make AI-powered phone calls, manage voice assistants, and retrieve call transcripts and recordings - all directly from any MCP-compatible client like ChatGPT Desktop, Claude Desktop, or other MCP-compatible applications.
🌐 Online MCP Server
You can use the hosted MCP server without local installation:
- Server URL: https://mcp.famulor.io
- SSE Endpoint: https://mcp.famulor.io/sse
- Health Check: https://mcp.famulor.io/health
The server is ready to use! For online usage instructions, see the Online Deployment Guide.
Features
- 📞 Make Calls - Initiate AI-powered phone conversations
- 🤖 Manage Assistants - Get and manage your AI assistants
- 📊 Retrieve Call Data - Get transcripts, recordings, and metadata
- 🔒 Secure Authentication - API key-based authentication per user
Prerequisites
- An MCP-compatible client such as:
- A Famulor API key (Get one here)
Note: If you want to run your own local server (Option 2), you'll also need:
- Node.js >= 20.0.0 (Download)
Quick Start
Option 1: Use Online MCP Server (Recommended - No Installation Required)
The easiest way to get started! Use our hosted MCP server at https://mcp.famulor.io.
1. Get Your API Key
- Go to Famulor API Keys
- Sign in or create an account
- Create a new API key
- Copy the API key (you'll need it in the next step)
2. Configure MCP in Your Client
See the Client-Specific Installation section below for detailed instructions for your MCP client (Cursor, Claude Desktop, ChatGPT Desktop, etc.).
Quick Example Configuration:
{
"mcpServers": {
"famulor": {
"url": "https://mcp.famulor.io/sse",
"env": {
"FAMULOR_API_KEY": "your-api-key-here"
}
}
}
}
3. Restart Your MCP Client
- Close your MCP client completely
- Restart it
- The MCP server should be automatically connected
4. Test It!
In your MCP client (ChatGPT, Claude, etc.), try asking:
- "Show me my Famulor assistants"
- "List my recent calls"
- "Make a call with assistant [ID] to [phone number]"
Option 2: Use Your Own Local Server
If you prefer to run the server locally:
1. Clone the Repository
git clone https://github.com/bekservice/Famulor-MCP.git
cd Famulor-MCP
2. Install Dependencies
npm install
3. Build the Server
npm run build
4. Get Your API Key
- Go to Famulor API Keys
- Sign in or create an account
- Create a new API key
- Copy the API key (you'll need it in the next step)
5. Configure MCP in Your Client
Create or edit the MCP configuration file for your platform and client. See the Client-Specific Installation section below for detailed instructions.
Example Configuration:
{
"mcpServers": {
"famulor": {
"command": "node",
"args": [
"/absolute/path/to/Famulor-MCP/dist/index.js"
],
"env": {
"FAMULOR_API_KEY": "your-api-key-here"
}
}
}
}
Important:
- Replace
/absolute/path/to/Famulor-MCPwith the actual absolute path to your cloned repository - Replace
your-api-key-herewith your actual Famulor API key - On Windows, use forward slashes or escaped backslashes in the path
Example paths:
- macOS:
/Users/username/Famulor-MCP/dist/index.js - Windows:
C:/Users/username/Famulor-MCP/dist/index.jsorC:\Users\username\Famulor-MCP\dist\index.js - Linux:
/home/username/Famulor-MCP/dist/index.js
6. Restart Your MCP Client
- Close your MCP client (ChatGPT Desktop, Claude Desktop, etc.) completely
- Restart it
- The MCP server should be automatically connected
7. Test It!
In your MCP client (ChatGPT, Claude, etc.), try asking:
- "Show me my Famulor assistants"
- "List my recent calls"
- "Make a call with assistant [ID] to [phone number]"
Client-Specific Installation
Choose your MCP client below for specific installation instructions:
For Claude Desktop
Important: Claude Desktop currently only supports local command-based MCP server configurations. HTTP/URL-based configurations are not supported, even in the latest version.
Setup Instructions
-
Find your configuration file:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json - Linux:
~/.config/Claude/claude_desktop_config.json
- macOS:
-
Add the MCP server configuration:
Open the configuration file and add the following to the
mcpServerssection:{ "mcpServers": { "famulor": { "command": "node", "args": [ "/absolute/path/to/Famulor-MCP/dist/index.js" ], "env": { "FAMULOR_API_KEY": "your-api-key-here" } } } }Important:
- Replace
/absolute/path/to/Famulor-MCPwith your actual absolute path to the repository - Replace
your-api-key-herewith your actual Famulor API key - You can get your API key at Famulor API Keys
- Make sure you've built the server:
npm run build - The path must be absolute (not relative)
- Replace
-
Restart Claude Desktop completely for the changes to take effect.
For Cursor
Option 1: Use Online MCP Server (Recommended - No Installation Required)
Global Installation (Recommended):
-
Go to Cursor Settings > Tools & Integrations
-
Click "New MCP Server"
-
This will open
~/.cursor/mcp.json -
Add the following configuration:
{ "mcpServers": { "famulor": { "type": "http", "url": "https://mcp.famulor.io/sse", "headers": { "Authorization": "Bearer your-api-key-here" } } } }Important:
- Replace
your-api-key-herewith your actual Famulor API key - The API key must be prefixed with
Bearerin the Authorization header - You can get your API key at Famulor API Keys
- Replace
-
Go back to Settings > MCP and click the refresh button
-
The Cursor agent will now be able to use the Famulor MCP tools
Project-Specific Installation:
- Create or edit
.cursor/mcp.jsonin your project root - Add the same configuration as above
- Restart Cursor or refresh MCP settings
Option 2: Use Your Own Local Server
Global Installation (Recommended):
-
Go to Cursor Settings > Tools & Integrations
-
Click "New MCP Server"
-
This will open
~/.cursor/mcp.json -
Add the following configuration:
{ "mcpServers": { "famulor": { "command": "node", "args": [ "/absolute/path/to/Famulor-MCP/dist/index.js" ], "env": { "FAMULOR_API_KEY": "your-api-key-here" } } } } -
Go back to Settings > MCP and click the refresh button
-
The Cursor agent will now be able to use the Famulor MCP tools
Project-Specific Installation:
- Create or edit
.cursor/mcp.jsonin your project root - Add the same configuration as above
- Restart Cursor or refresh MCP settings
For Claude Code
Option 1: Use Online MCP Server (Recommended - No Installation Required)
To add the online MCP server to Claude Code, run this command in your terminal:
claude mcp add-json "famulor" '{"type":"http","url":"https://mcp.famulor.io/sse","headers":{"Authorization":"Bearer your-api-key-here"}}'
Note:
- Replace
your-api-key-herewith your actual Famulor API key - The API key must be prefixed with
Bearerin the Authorization header - You can get your API key at Famulor API Keys
Option 2: Use Your Own Local Server
To add your local MCP server to Claude Code, run this command in your terminal:
claude mcp add-json "famulor" '{"command":"node","args":["/absolute/path/to/Famulor-MCP/dist/index.js"],"env":{"FAMULOR_API_KEY":"your-api-key-here"}}'
Note: Replace /absolute/path/to/Famulor-MCP/dist/index.js with your actual path and your-api-key-here with your actual API key.
See the official Claude Code MCP documentation for more details.
For ChatGPT Desktop App
Option 1: Use Online MCP Server (Recommended - No Installation Required)
- Find your configuration file:
- macOS:
~/Library/Application Support/ChatGPT/mcp.json - Windows:
%APPDATA%\ChatGPT\mcp.jsonorC:\Users\YourUsername\AppData\Roaming\ChatGPT\mcp.json - Linux: `~/.config/ChatGPT/
- macOS:
FAQ
- What is the Famulor MCP server?
- Famulor 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 Famulor?
- This profile displays 38 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.8 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.
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Ratings
4.8★★★★★38 reviews- ★★★★★Chaitanya Patil· Dec 28, 2024
Famulor is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Diego Abbas· Dec 16, 2024
I recommend Famulor for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Kiara Chawla· Dec 12, 2024
Famulor is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Tariq Ghosh· Dec 8, 2024
Famulor has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Piyush G· Nov 19, 2024
Famulor is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Benjamin Ghosh· Nov 7, 2024
Famulor reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Layla Verma· Nov 3, 2024
Famulor is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Benjamin Bhatia· Oct 26, 2024
Useful MCP listing: Famulor is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Camila Flores· Oct 22, 2024
We evaluated Famulor against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Shikha Mishra· Oct 10, 2024
We evaluated Famulor against two servers with overlapping tools; this profile had the clearer scope statement.
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