Apiary MCP Server for CrewAI 10 tools — connect in under 2 minutes
Connect your CrewAI agents to Apiary through Vinkius, pass the Edge URL in the `mcps` parameter and every Apiary tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
from crewai import Agent, Task, Crew
agent = Agent(
role="Apiary Specialist",
goal="Help users interact with Apiary effectively",
backstory=(
"You are an expert at leveraging Apiary 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 Apiary "
"and summarize their capabilities."
),
agent=agent,
expected_output=(
"A detailed summary of 10 available tools "
"and what they can do."
),
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)
* 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 Apiary MCP Server
Connect your Apiary workspace to your AI agent and take full control of your API design, specification, and validation processes through natural conversation.
When paired with CrewAI, Apiary becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Apiary 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
- Read API Blueprints — Fetch raw Markdown-based API Blueprints or Swagger files defining endpoints, methods, and parameters without leaving your editor
- Publish Documentation — Instantly update your Apiary projects with new markdown code. Mock servers and public documentation sync automatically
- Run Dredd Tests — Validate your backend implementation against the blueprint specifications using integrated tests
- Team Management — Query team API projects, list team members, and manage your engineering ecosystem intuitively
The Apiary MCP Server exposes 10 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 Apiary to CrewAI via MCP
Follow these steps to integrate the Apiary 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 10 tools from Apiary
Why Use CrewAI with the Apiary MCP Server
CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Apiary 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
Apiary + CrewAI Use Cases
Practical scenarios where CrewAI combined with the Apiary MCP Server delivers measurable value.
Automated multi-step research: a reconnaissance agent queries Apiary 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 Apiary, analyzes trends over time, and generates executive briefings in markdown or PDF format
Multi-source enrichment pipelines: chain Apiary 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 Apiary against predefined policy rules, generates deviation reports, and routes findings to the appropriate team
Apiary MCP Tools for CrewAI (10)
These 10 tools become available when you connect Apiary to CrewAI via MCP:
get_api
Get the full API Blueprint source code of an Apiary API project
get_doc_url
Get the documentation and mock server URLs for an Apiary API project
get_me
Get the authenticated Apiary user profile
get_team
Get details of a specific Apiary team
list_apis
Apiary is an API design-first platform. List all API projects on Apiary
list_team_apis
List all API projects belonging to a specific Apiary team
list_team_members
List all members of an Apiary team
list_teams
List all teams the authenticated user belongs to on Apiary
publish_blueprint
Use with valid Markdown blueprint/Swagger. Publish (update) the API Blueprint of an Apiary API project
run_tests
Get or run Dredd-style API tests against an Apiary project
Example Prompts for Apiary in CrewAI
Ready-to-use prompts you can give your CrewAI agent to start working with Apiary immediately.
"Get the API Blueprint code for my project named 'payments-gateway'."
"List all team members of the 'frontend-team' in Apiary."
"Update my 'users-api' with this new blueprint code..."
Troubleshooting Apiary MCP Server with CrewAI
Common issues when connecting Apiary to CrewAI through the Vinkius, and how to resolve them.
MCP tools not discovered
Agent not using tools
Timeout errors
Rate limiting or 429 errors
Apiary + CrewAI FAQ
Common questions about integrating Apiary MCP Server with CrewAI.
How does CrewAI discover and connect to MCP tools?
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?
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?
Can CrewAI agents call multiple MCP tools in parallel?
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)?
crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.Connect Apiary with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Apiary to CrewAI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.