How do I find my SignalWire Project ID and Token?

Log in to your [**SignalWire Dashboard**](https://signalwire.com/signin), select your Project, and navigate to **API** in the sidebar. You will find your Project ID and can generate a new API Token there.

What is the Space URL?

The Space URL is the prefix of your SignalWire domain (e.g., if your domain is `example.signalwire.com`, the Space is `example`). Enter only the prefix.

Can the agent send SMS messages?

Yes. Use the `send_sms` tool providing the recipient number, your SignalWire number, and the message body. Your agent will deliver the SMS and confirm the status instantly.

SignalWire MCP Server for CrewAI 8 tools — connect in under 2 minutes

Name: SignalWire
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

Connect your CrewAI agents to SignalWire through Vinkius, pass the Edge URL in the `mcps` parameter and every SignalWire tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="SignalWire Specialist",
    goal="Help users interact with SignalWire effectively",
    backstory=(
        "You are an expert at leveraging SignalWire tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in SignalWire "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 8 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About SignalWire MCP Server

Empower your AI agent to orchestrate your entire cloud communication infrastructure with SignalWire, the advanced platform for messaging, voice, and video. By connecting SignalWire to your agent, you transform complex telecom management into a natural conversation. Your agent can instantly list your phone numbers, audit message delivery, and retrieve call logs without you ever touching a technical console. Whether you are providing customer alerts or managing corporate voice lines, your agent acts as a real-time telecom operator, ensuring your communication is always reliable and your usage data is organized.

When paired with CrewAI, SignalWire becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call SignalWire tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Messaging Intelligence — Send SMS messages instantly and retrieve detailed message status and history.
Call Auditing — List all recent voice calls and retrieve metadata for each, including direction and duration.
Number Oversight — List and monitor all incoming phone numbers associated with your project.
Usage Intelligence — Retrieve detailed usage records to maintain strict organizational control over your communication costs.
Account Governance — Monitor account-wide metadata to understand your project status in real-time.

The SignalWire MCP Server exposes 8 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect SignalWire to CrewAI via MCP

Follow these steps to integrate the SignalWire MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 8 tools from SignalWire

Why Use CrewAI with the SignalWire MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with SignalWire through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

SignalWire + CrewAI Use Cases

Practical scenarios where CrewAI combined with the SignalWire MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries SignalWire for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries SignalWire, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain SignalWire tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries SignalWire against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

SignalWire MCP Tools for CrewAI (8)

These 8 tools become available when you connect SignalWire to CrewAI via MCP:

get_account_info

Get SignalWire account details

get_call

Get details for a specific call

get_message

Get details for a specific message

list_calls

List recent voice calls

list_messages

List recent SMS/MMS messages

list_phone_numbers

List SignalWire phone numbers

list_usage

Get account usage records

send_sms

Send an SMS message

Example Prompts for SignalWire in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with SignalWire immediately.

"List all my SignalWire phone numbers."

"Send SMS 'Server alert: high usage detected' to +15550123."

"Show me recent call logs for my project."

Troubleshooting SignalWire MCP Server with CrewAI

Common issues when connecting SignalWire to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

SignalWire + CrewAI FAQ

Common questions about integrating SignalWire MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.