MCPJungle mcp gateway

MCPJungle is a single source-of-truth registry for all Model Context Protocol Servers running in your Organisation.

🧑‍💻 Developers use it to register & manage MCP servers and the tools they provide from a central place.

🤖 MCP Clients use it to discover and consume all these tools from a single "Gateway" MCP Server.

Who should use MCPJungle?

1. Developers using MCP Clients like Claude & Cursor that need to access MCP servers for tool-calling
2. Developers building production-grade AI Agents that need to access MCP servers with built-in security, privacy and Access Control.
3. Organisations wanting to view & manage all MCP client-server interactions from a central place. Hosted in their own datacenter 🔒

📋 Table of Contents

• Quick Start guide
• Installation
• Usage
  • Server
    • Running mcpjungle server inside Docker
    • Running mcpjungle server directly on the host machine
  • Client
    • Adding Streamable HTTP-based MCP servers
    • Adding STDIO-based MCP servers
    • Removing MCP servers
  • Connect to mcpjungle from Claude
  • Connect to mcpjungle from Cursor
  • Enabling/Disabling Tools globally
  • Authentication
  • Enterprise features
    • Access Control
• Limitations
• Contributing

Quickstart guide

This quickstart guide will show you how to:

1. Start the MCPJungle server locally using docker-compose
2. Register a simple MCP server in mcpjungle
3. Connect your Claude to mcpjungle to access your MCP tools

Start the server

Register MCP servers

Download the client binary either using brew or from the Releases.

Add the context7 remote MCP server to mcpjungle

Connect to mcpjungle

Add the following configuration in your Claude MCP Servers:

Try asking Claude for the following:

Claude will then attempt to call the context7__get-library-docs tool via MCPJungle, which will return the documentation for the Lodash library.

Congratulations 🎉 You have successfully registered a remote MCP server in MCPJungle and called one of its tools via Claude

Installation

MCPJungle is shipped as a stand-alone binary.

You can either download it from the Releases Page or use Homebrew to install it:

Verify your installation by running

MCPJungle provides a Docker image which is useful for running the registry server (more about it later).

Usage

MCPJungle has a Client-Server architecture and the binary lets you run both the Server and the Client.

Server

The MCPJungle server is responsible for managing all the MCP servers registered in it and providing a unified MCP gateway for AI Agents to discover and call tools provided by these registered servers.

The gateway itself runs over streamable http transport and is accessible at the /mcp endpoint.

Running inside Docker

For running the MCPJungle server locally, docker compose is the recommended way:

This will start the MCPJungle server along with a persistent Postgres database container.

You can quickly verify that the server is running:

If you plan on registering stdio-based MCP servers that rely on npx or uvx, use mcpjungle's stdio tagged docker image instead.

This image is significantly larger. But it is very convenient and recommended for running locally when you rely on stdio-based MCP servers.

For example, if you only want to register remote mcp servers like context7 and deepwiki, you can use the standard (minimal) image.

But if you also want to use stdio-based servers like filesystem, time, github, etc., you should use the stdio-tagged image instead.

Production Deployment

The default MCPJungle Docker image is very lightweight - it only contains a minimal base image and the mcpjungle binary.

It is therefore suitable and recommended for production deployments.

For the database, we recommend you deploy a separate Postgres DB cluster and supply its endpoint to mcpjungle (see Database section below).

You can see the definitions of the standard Docker image and the stdio Docker image.

Running directly

You can also run the server directly on your host machine using the binary:

This starts the main registry server and MCP gateway, accessible on port 8080 by default.

Database

The mcpjungle server relies on a database and by default, creates a SQLite DB in the current working directory.

This is okay when you're just testing things out locally.

Alternatively, you can supply a DSN for a Postgresql database to the server:

Client

Once the server is up, you can use the mcpjungle CLI to interact with it.

MCPJungle currently supports MCP servers using stdio and Streamable HTTP Transports.

Let's see how to register them in mcpjungle.

Registering streamable HTTP-based servers

Let's say you're already running a streamable http MCP server locally at http://127.0.0.1:8000/mcp which provides basic math tools like add, subtract, etc.

You can register this MCP server with MCPJungle:

If you used docker-compose to run the server, and you're not on Linux, you will have to use host.docker.internal instead of your local loopback address.

The registry will now start tracking this MCP server and load its tools.

You can also provide a configuration file to register the MCP server:

All tools provided by this server are now accessible via MCPJungle:

The config file format for registering a Streamable HTTP-based MCP server is:

Registering STDIO-based servers

Here's an example configuration file (let's call it filesystem.json) for a MCP server that uses the STDIO transport:

You can register this MCP server in MCPJungle by providing the configuration file:

The config file format for registering a STDIO-based MCP server is:

Limitation 🚧

MCPJungle creates a new connection when a tool is called. This means a new sub-process for a STDIO mcp server is started for every tool call.

This has some performance overhead but ensures that there are no memory leaks.

But it also means that currently MCPJungle doesn't support stateful connections with your MCP server.

We want to hear your feedback to improve this mechanism, feel free to create an issue, start a discussion or just reach out on Discord.

Deregistering MCP servers

You can remove a MCP server from mcpjungle.

Once removed, this mcp server and its tools are no longer available to you or your MCP clients.

Integration with other MCP Clients

Assuming that MCPJungle is running on http://localhost:8080, use the following configurations to connect to it:

Claude

Cursor

Enabling/Disabling Tools

You can enable or disable a specific tool or all the tools provided by an MCP Server.

If a tool is disabled, it is not available via the MCPJungle Proxy, so no MCP clients can view or call it.

A disabled tool is still accessible via mcpjungle's HTTP API, so humans can still manage it from the CLI (or any other HTTP client).

Authentication

MCPJungle currently supports authentication if your Streamable HTTP MCP Server accepts static tokens for auth.

This is useful when using SaaS-provided MCP Servers like HuggingFace, Stripe, etc. which require your API token for authentication.

You can supply your token while registering the MCP server:

Or from your configuration file

Support for Oauth flow is coming soon!

Enterprise Features 🔒

If you're running MCPJungle in your organisation, we recommend running the Server in the production mode:

By default, mcpjungle server runs in development mode which is ideal for individuals running it locally.

In Production mode, the server enforces stricter security policies and will provide additional features like Authentication, ACLs, observability and more.

After starting the server in production mode, you must initialize it by running the following command on your client machine:

This will create an admin user in the server and store its API access token in your home directory (~/.mcpjungle.conf).

You can then use the mcpjungle cli to make authenticated requests to the server.

Access Control

In development mode, all MCP clients have full access to all the MCP servers registered in MCPJungle Proxy.

production mode lets you control which MCP clients can access which MCP servers.

Suppose you have registered 2 MCP servers calculator and github in MCPJungle in production mode.

By default, no MCP client can access these servers. You must create an MCP Client in mcpjungle and explicitly allow it to access the MCP servers.

Mcpjungle creates an access token for your client. Configure your client or agent to send this token in the Authorization header when making requests to the mcpjungle proxy.

For example, you can add the following configuration in Cursor to connect to MCPJungle:

A client that has access to a particular server this way can view and call all the tools provided by that server.

Current limitations 🚧

We're not perfect yet, but we're working hard to get there!

1. MCPJungle doesn't maintain any long-running connections to the registered MCP Servers

When you call a tool in a Streamable HTTP server, mcpjungle creates a new connection to the server to serve the request.

When you call a tool in a STDIO server, mcpjungle creates a new connection and starts a new sub-process to run this server.

After servicing your request, it terminates this sub-process.

So a new stdio server process is started for every tool call.

This has some performance overhead but ensures that there are no memory leaks.

It also means that if you rely on stateful connections with your MCP server, mcpjungle can currently not provide that.

We plan on improving this mechanism in future releases and are open to ideas from the community!

2. MCPJungle does not support OAuth flow for authentication.

This is a work in progress.

We're collecting more feedback on how people use OAuth with MCP servers, so feel free to start a Discussion or open an issue to share your use case.

Contributing 💻

If you're interested in contributing to MCPJungle, see Developer Docs.