Can I use this server to manage Kong's AI Proxy plugin?

Absolutely. The `create_ai_plugin` tool is specifically designed to inject the `ai-proxy` plugin onto Services. You can define providers like OpenAI or Anthropic and manage model routing directly through your agent.

How do I create a new API route through a conversation?

Use the `create_route` tool and provide a JSON payload defining the paths and the Service ID it should point to. Your agent will handle the Admin API call to provision the routing rule instantly.

Can my agent generate new API keys for consumers?

Yes. The `create_consumer_key` tool allows you to provision new credentials for specific Consumers. This is perfect for onboarding new tenants or rotating keys for downstream applications securely.

Kong (AI API Gateway) MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Kong (AI API Gateway)
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Kong (AI API Gateway) Specialist",
    goal="Help users interact with Kong (AI API Gateway) effectively",
    backstory=(
        "You are an expert at leveraging Kong (AI API Gateway) 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 Kong (AI API Gateway) "
        "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)

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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 Kong (AI API Gateway) MCP Server

Connect your Kong API Gateway instance to any AI agent and take full control of your API lifecycle and AI traffic management through natural conversation.

When paired with CrewAI, Kong (AI API Gateway) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Kong (AI API Gateway) 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

Service Orchestration — List backend services and create new upstream definitions defining URLs and protocols directly from your agent
Route Management — Configure inbound routing rules to map client requests to backend services based on specific paths or hostnames
AI Plugin Control — Apply and configure the ai-proxy plugin to enable LLM routing, model providers, and key encapsulation securely
Operational Patching — Update existing plugin configurations in real-time, allowing you to adjust rate limits or swap AI models dynamically
Consumer CRM — Manage consumer profiles and generate API keys for key-auth plugins to track specific user or tenant usage
Infrastructure Audit — Discover enabled plugins across your gateway and remove unused modules instantly to maintain a clean proxy pipeline

The Kong (AI API Gateway) 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 Kong (AI API Gateway) to CrewAI via MCP

Follow these steps to integrate the Kong (AI API Gateway) 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 Kong (AI API Gateway)

Why Use CrewAI with the Kong (AI API Gateway) MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Kong (AI API Gateway) 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

Kong (AI API Gateway) + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Kong (AI API Gateway) MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Kong (AI API Gateway) 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 Kong (AI API Gateway), analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Kong (AI API Gateway) 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 Kong (AI API Gateway) against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Kong (AI API Gateway) MCP Tools for CrewAI (10)

These 10 tools become available when you connect Kong (AI API Gateway) to CrewAI via MCP:

create_ai_plugin

Frequently used for enabling the `ai-proxy` plugin for LLM routing and key encapsulation. Apply a new Plugin (like AI Proxy) to a specific Service

create_consumer_key

Generate an API Key credential for a Kong Consumer

create_route

Create a new Route to expose a Service in Kong

create_service

The payload must define the upstream URL, name, and protocol information. Create a new backend Service in Kong

delete_plugin

Delete and permanently remove a Plugin from the Kong Gateway

list_consumers

List all Consumer profiles registered in Kong

list_plugins

g., Rate Limiting, AI Proxy, Key Auth) currently configured globally or scoped to specific Services/Routes. List all enabled Plugins on the Kong Gateway

list_routes

List all routing rules configured in the Kong API Gateway

list_services

List all Services registered in the Kong API Gateway

update_plugin

Useful for adjusting rate limits dynamically or swapping AI model providers under heavy load. Update the configuration of an existing Kong Plugin

Example Prompts for Kong (AI API Gateway) in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Kong (AI API Gateway) immediately.

"List all registered services in my Kong Gateway"

"Add the 'ai-proxy' plugin to service ID '123-abc' using OpenAI"

"Who are the registered consumers in our gateway?"

Troubleshooting Kong (AI API Gateway) MCP Server with CrewAI

Common issues when connecting Kong (AI API Gateway) 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.

Kong (AI API Gateway) + CrewAI FAQ

Common questions about integrating Kong (AI API Gateway) 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.