Famulor
by bekservice
Famulor — Voice agent platform for automated phone calls: configure assistants, manage campaigns, send SMS, and run mid-
★ 1
GitHub stars
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
Frequently Asked Questions
- 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
Discussion
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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