The Model Context Protocol (MCP) has quickly become the USB-C of AI tooling: a single standard that lets AI agents talk to your databases, billing systems, observability stacks, and internal APIs. But there is a catch every growing team runs into, and it is called MCP sprawl. Everyone installs the same servers locally, credentials get copy-pasted into a dozen config files, and nobody is sure who has access to what.
MCPJungle fixes exactly that. In this guide we will cover what an MCP gateway is, why it matters, and how to connect one to Gleap Kai so your AI agents get every tool from a single, secure endpoint.
What is the Model Context Protocol (MCP)?
MCP is an open standard that gives AI models a consistent way to call external tools and data sources. Instead of building custom integrations for every model, you run an MCP server (for MongoDB, ClickHouse, your billing provider, your own API, and so on) and any MCP-compatible client can use it, from Claude and Cursor to Gleap’s Kai. If you are new to building on top of it, our guide to building AI agents in 2026 is a good starting point.
What is MCPJungle?
MCPJungle is an open-source MCP gateway and registry. Rather than installing MCP servers on every laptop, you register each server once with MCPJungle and it exposes them all through one endpoint. Your AI clients connect to that single URL and instantly see every tool you have registered.
Think of it as a reverse proxy and access-control layer for the Model Context Protocol: one place to add servers, manage credentials, and decide who can use what.
Why your team needs an MCP gateway
Running MCP servers directly works fine for one developer. Across a team, a gateway pays for itself fast:
- Central management. Add, update, or remove an MCP server once and everyone gets the change. No more “works on my machine” config drift.
- One endpoint for every client. Point Kai Code, Cursor, or Claude Desktop at a single URL instead of maintaining a separate config for each server.
- Credentials stay server-side. Database passwords and API keys live on the gateway, not scattered across laptops.
- Granular access control. Issue a scoped token per teammate and decide which servers each one can reach.
- Read-only guardrails. Expose production data for reading while blocking writes and destructive operations, which is ideal for a shared support or analytics workflow.
This is the same philosophy behind Gleap’s own integrations ecosystem: connect once, use everywhere.
How MCPJungle works
MCPJungle has two core concepts:
- The registry is the catalog of MCP servers you have added, whether remote HTTP servers or local stdio servers.
- The gateway is the single MCP endpoint your clients connect to, which proxies each request to the right server.
Run it in enterprise mode and you also get token-based authentication: an admin token for managing the gateway, plus per-client tokens for each teammate or agent. Every AI client authenticates with a bearer token and only sees the servers it is allowed to use.
How to self-host MCPJungle
MCPJungle is free and open source. A minimal self-hosted setup looks like this:
- Deploy it with Docker Compose (the server plus a Postgres database) on any small virtual machine.
- Put it behind HTTPS using a reverse proxy such as Caddy with a TLS certificate, ideally on a dedicated host.
- Register your servers, for example a read-only database, your billing provider, and your observability tool.
- Mint client tokens for each teammate and share them privately.
Full instructions live in the official MCPJungle repository. Once it is live, connecting AI clients takes seconds, including Gleap’s.
Using MCPJungle with Gleap Kai
Here is where it gets powerful. Because Kai speaks MCP, you can give your AI support agent and coding agent access to all of your internal tools through the gateway, without wiring up each server individually.
Connect MCPJungle in Kai Code (MCP settings)
Kai Code is Gleap’s autonomous AI coding agent. To give it your whole toolset at once, open Kai Code’s MCP settings in your Gleap dashboard, add a new MCP server pointing at your gateway URL, and include the authorization header with the client token you minted in MCPJungle. Save it, and Kai Code can now query your database, check billing, or read logs while it works on a fix. When you add a new MCP server to the gateway later, Kai Code picks it up automatically.
Add MCPJungle to your Gleap custom agents
With Kai custom agents you can build purpose-built agents, such as a billing triage bot, an on-call incident assistant, or a data-lookup helper, and scope each one to exactly the tools it needs. Attach your MCPJungle gateway as an MCP source in the agent configuration and the agent can call those tools inside its workflow. Pair it with a read-only gateway token and you get a safe, capable agent that can look up anything but cannot change production data.
See the Gleap documentation for step-by-step setup, and explore the AI support copilot to see what connected context makes possible.
The other direction: Gleap’s own MCP server
MCPJungle helps you bring external tools into Kai. Gleap also works the other way around. With the Gleap MCP server you can connect Claude, ChatGPT, Cursor, or VS Code directly to your Gleap tickets, contacts, docs, and changelogs, so your AI assistant has real customer context. Used together, your agents can both read your product data and act across your internal systems.
Security best practices
A shared MCP gateway touches sensitive systems, so treat it accordingly:
- Default to read-only. Register production data sources with write and destructive tools disabled.
- One token per identity. Give each teammate and agent its own scoped token so you can revoke access individually.
- Encrypt in transit. Always front the gateway with HTTPS and TLS.
- Rotate credentials. Cycle any API keys or database passwords periodically.
- Least privilege at the source. Where possible, connect using a read-only database user rather than an admin account.
Bring your tools and your AI together
MCP is turning AI agents from clever chatbots into genuine copilots for your business. A gateway like MCPJungle makes that scalable and secure, and Gleap’s Kai turns those tools into real outcomes, from resolving support tickets to shipping code through self-driving development. If you are exploring what is possible, our roundup of the best AI agents for SaaS support and our look at AI-driven development are great next reads.
Ready to put your tools to work? Start with Gleap Kai and connect your first MCP gateway today, or see pricing to find the right plan for your team.