W3J Telnyx MCP
Exposes the full Telnyx API as Model Context Protocol tools and enables deploying autonomous AI voice agents from a YAML spec.
README
W3J Telnyx MCP
MCP server exposing the full Telnyx API as Model Context Protocol tools, plus an autonomous voice agent builder that deploys live AI receptionists from a YAML spec.
Quick start
# Install
git clone https://github.com/mnjbold/w3j-telnyx-mcp.git
cd w3j-telnyx-mcp
uv venv .venv --python 3.12 --seed
source .venv/bin/activate # Linux/macOS
# or: .venv\Scripts\Activate.ps1 (Windows)
uv sync --all-extras
# Health check
python -m telnyx_mcp.utils.env
python -m telnyx_mcp.clients.telnyx_client
# Start MCP server (stdio — for Claude Desktop / Cursor / Windsurf)
python -m telnyx_mcp.server
# Start MCP server (HTTP — for remote MCP clients)
python -m telnyx_mcp.server --transport http --host 0.0.0.0 --port 8765
# Deploy an agent from YAML
python agent_builder/builder.py agents/my-agent/spec.yaml --dry-run
python agent_builder/builder.py agents/my-agent/spec.yaml
What you get
| Tool surface | Tools |
|---|---|
numbers |
search, order, list, get, update |
voice |
dial, transfer, hangup, answer, reject, start/stop AI assistant, recordings |
assistants |
CRUD AI Assistants |
infrastructure |
Call Control Apps, Outbound Voice Profiles, Messaging Profiles, Voice Clones |
messaging |
send SMS |
utility |
balance, account summary, health check |
Deploy a voice agent
# From YAML spec
python agent_builder/builder.py agents/w3j-llc-concierge/spec.yaml
# agents/my-agent/spec.yaml
name: My Agent
instructions: |
You are a friendly receptionist for Acme Corp...
country_code: US
area_code: "415"
buy_number: true
webhook_url: https://your-server/webhooks/telnyx
model: openai/gpt-4o
voice: Telnyx.KokoroTTS.af_heart
CI/CD
Push to main → GitHub Actions CI runs pytest + type check + lint.
See .github/workflows/ci.yml.
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
Neon Database
MCP server for interacting with Neon Management API and databases
E2B
Using MCP to run code via e2b.
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.