Bring Api Gateway
to CrewAI
Learn how to connect Kong Gateway to CrewAI and start using 40 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Kong Gateway MCP Server?
Connect your Kong Gateway Admin API to any AI agent and take full control of your API management lifecycle through natural conversation.
What you can do
- Services & Routes — List, create, and update upstream services and their associated routing rules to manage traffic flow.
- Consumer Management — Query and manage API consumers, allowing you to track users and applications interacting with your gateway.
- Plugin Configuration — Inspect and manage plugins for authentication, rate limiting, and logging across your services and routes.
- Upstreams & Targets — Configure load balancing by managing upstreams and their health-checked targets.
- SSL/TLS Management — List and update certificates and SNIs to ensure secure communication across your endpoints.
- System Health — Retrieve real-time status and information about your Kong instance to monitor performance.
How it works
- Subscribe to this server
- Enter your Kong Admin URL (and optional Admin Token)
- Start managing your API infrastructure from Claude, Cursor, or any MCP-compatible client
No more manual cURL commands or navigating complex dashboards to check a route configuration. Your AI acts as a dedicated DevOps engineer or API Architect.
Who is this for?
- DevOps Engineers — quickly check gateway status, list plugins, and verify upstream health without leaving the terminal or IDE.
- Backend Developers — create and test new services and routes instantly during the development cycle.
- API Architects — audit consumer access and plugin configurations to ensure security and compliance across the organization.
Built-in capabilities (40)
Create a new Kong Certificate
Create a new Kong Consumer
Create a new Kong Plugin
Create a new Kong Route
Create a new Kong Service
Create a new Kong SNI
Create a new Target for an Upstream
Create a new Kong Upstream
Delete a Kong Certificate
Delete a Kong Consumer
Delete a Kong Plugin
Delete a Kong Route
Delete a Kong Service
Delete a Kong SNI
Delete a Target from an Upstream
Delete a Kong Upstream
Get details for a specific Kong Certificate
Get details for a specific Kong Consumer
Retrieve general information about the Kong node
Get details for a specific Kong Plugin
Get details for a specific Kong Route
Get details for a specific Kong Service
Get details for a specific Kong SNI
Retrieve the status of the Kong node
Get details for a specific Kong Upstream
List all Kong Certificates
List all Kong Consumers
List all Kong Plugins
List all Kong Routes
List all Kong Services
List all Kong SNIs
List all Targets for an Upstream
List all Kong Upstreams
Update an existing Kong Certificate
Update an existing Kong Consumer
Update an existing Kong Plugin
Update an existing Kong Route
Update an existing Kong Service
Update an existing Kong SNI
Update an existing Kong Upstream
Why CrewAI?
When paired with CrewAI, Kong Gateway becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Kong Gateway tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
- —
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
mcpsparameter 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 Gateway in CrewAI
Kong Gateway and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Kong Gateway to CrewAI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Kong Gateway in CrewAI
The Kong Gateway 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. All 40 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in CrewAI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
Kong Gateway for CrewAI
Every tool call from CrewAI to the Kong Gateway MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How can I check if my Kong Gateway instance is running correctly?
You can use the get_status tool. It will return the current status of the Kong node, including database connectivity and server metrics.
Can I list all the plugins currently enabled on my gateway?
Yes! Use the list_plugins tool to retrieve a complete list of all configured plugins across your entire Kong instance.
Is it possible to create a new service and its route through the AI?
Absolutely. You can use create_service to define your upstream and then create_route to specify how traffic should reach that service.
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.
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.
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