# Glxymesh

> Managed MCP server hosting: build, deploy and host MCP servers in the cloud and connect them to Claude, ChatGPT, Gemini and other AI clients.

Glxymesh is a hosted platform for Model Context Protocol (MCP) tools. A project is a gx.yml and one tool.yml per tool: an http tool is a request described in YAML, and a function tool adds one run function in Go, TypeScript or Python, and can connect to databases over TCP. The gxmesh CLI pushes a project; the platform builds it, runs its tests, deploys its code to the project's own AWS Lambda, and serves every tool from one authenticated MCP endpoint at https://<org>.mcp.glxymesh.com/<project> over Streamable HTTP with OAuth. Every outbound call leaves through an egress gateway that allows only the hosts and database addresses a tool names and adds the project's encrypted keys itself, so tool code never holds them. Agents can draft tools for a person to review and publish. Teams use owner, admin and member roles, and the console shows each call and its outcome.

## Pages

- [Home](https://www.glxymesh.com/): what the platform does, how a request flows through the gateway, quickstart and FAQ
- [Pricing](https://www.glxymesh.com/pricing): Free, Pro, Team and Enterprise plans in USD (INR in India), included usage and AI credits, and limits
- [About](https://www.glxymesh.com/about): what Glxymesh offers and who runs it
- [Contact](https://www.glxymesh.com/contact): sales, support, partnerships and billing; business details
- [Compare MCP hosting](https://www.glxymesh.com/compare/best-mcp-server-hosting): Glxymesh, Cloudflare Workers, Vercel, FastMCP Gateway, MintMCP and Railway compared on languages, client sign-in, API keys, deploys and price, with sources
- [Blog](https://www.glxymesh.com/blog): guides and engineering notes
- [Meet Glxymesh: turn your ideas into hosted MCP tools](https://www.glxymesh.com/blog/meet-glxymesh): Watch the 90-second launch video, then walk through each step it shows: describe a tool, let AI build and test it, approve what it may reach, and connect any AI client.
- [What is the Model Context Protocol (MCP)?](https://www.glxymesh.com/blog/what-is-the-model-context-protocol): A plain guide to MCP: what the Model Context Protocol is, how MCP servers and clients talk, what tools, resources and prompts are, and how to host a server.
- [Self-hosted vs managed MCP servers: which to choose](https://www.glxymesh.com/blog/self-hosted-vs-managed-mcp-servers): What running your own MCP server really involves, what managed MCP server hosting takes off your hands, and when each one is the right choice.
- [How a request moves through Glxymesh](https://www.glxymesh.com/blog/how-a-request-moves-through-glxymesh): From the moment an AI client calls a tool to the structured result it gets back: identity, the project's Lambda, keys at egress and the gateway in between.
- [MCP server tutorial: deploy your first MCP server](https://www.glxymesh.com/blog/deploy-your-first-mcp-tool): A step-by-step MCP server tutorial: install the gxmesh CLI, build an MCP server with one tool in Go, TypeScript or Python, deploy it and connect a client.
- [Keeping API keys out of your tool code](https://www.glxymesh.com/blog/keeping-api-keys-out-of-your-tool-code): Encrypted project secrets, added to outbound requests by the egress gateway, so neither your code nor the calling client ever holds them.
- [Connect MCP servers to AI clients like Claude and ChatGPT](https://www.glxymesh.com/blog/connect-claude-chatgpt-and-gemini-to-one-endpoint): One endpoint for every AI client. How OAuth and Streamable HTTP fit together when Claude, ChatGPT, Gemini or Cursor connects to your MCP server.
- [MCP tools and integrations: calling external APIs](https://www.glxymesh.com/blog/calling-external-apis-from-a-sandboxed-tool): Build MCP integrations by wrapping a third-party HTTP API once, with its key kept out of your code, and serve it to every agent connected to your project.
- [Reading your invocation history](https://www.glxymesh.com/blog/reading-your-invocation-history): Follow calls, inspect outcomes and spot timeouts before your users do.

## Docs

- [Overview](https://docs.glxymesh.com/): write MCP tools in Go, TypeScript or Python, or describe them in YAML, deploy with one command, and connect Claude Code, Claude Desktop, Cursor or VS Code to one MCP endpoint
- [Quickstart](https://docs.glxymesh.com/quickstart/): install the gxmesh CLI, start a project, add a tool, push it and call it from Claude Code
- [How it works](https://docs.glxymesh.com/concepts/how-it-works/): organizations, projects and tools; the MCP gateway; OAuth 2.1 with dynamic client registration; Lambda and the egress gateway
- [Tool kinds](https://docs.glxymesh.com/guides/tool-kinds/): http tools in YAML and function tools in Go, TypeScript or Python
- [Keys and network](https://docs.glxymesh.com/guides/keys-and-network/): allowed hosts, project secrets bound to hosts, keys added at egress, and keys the code reads
- [Connect to a database](https://docs.glxymesh.com/guides/databases/): Postgres, MySQL, Redis and other TCP services from a function tool
- [Develop locally](https://docs.glxymesh.com/guides/local-development/): gxmesh dev, call and test on your own machine
- [Deploy](https://docs.glxymesh.com/guides/deploy/): push, approvals, tests before going live, revisions and rollback
- [Connect clients](https://docs.glxymesh.com/guides/connect-clients/): connect Claude Code, Claude Desktop, Cursor, VS Code and other MCP clients over Streamable HTTP with OAuth
- [CLI reference](https://docs.glxymesh.com/reference/cli/): every gxmesh command, from login and project scope to push and rollback
- [Limits](https://docs.glxymesh.com/reference/limits/): time and memory per call, outbound requests, push size and sleep

## Plans

- Free, $0 a month (₹0 in India): Try the platform with real tools. Calls stop when the month's usage runs out, so there is never a bill. Includes a month's usage and 5 AI credits; 10 hosted tools, 1 member, up to 256 MB and 10 s per call, 5 calls a second. When the month's usage runs out: calls stop until next month.
- Pro, $29 a month (₹2,599 in India): For a developer shipping tools to real users. Includes a month's usage and 100 AI credits; 250 hosted tools, 3 members, up to 1024 MB and 60 s per call, 50 calls a second. When the month's usage runs out: keeps answering, up to your spend cap.
- Team, $79 a month (₹6,999 in India): For a team running tools in production. Includes a month's usage and 300 AI credits; 2,500 hosted tools, 10 members, up to 2048 MB and 60 s per call, 200 calls a second. When the month's usage runs out: keeps answering, up to your spend cap.
- Enterprise, custom: limits, rates and invoice terms agreed on a call.

## FAQ

### What is Glxymesh?

Glxymesh is managed MCP server hosting. Describe tools in YAML or write them in Go, TypeScript or Python; each project becomes an MCP server that we build, host and serve to compatible AI clients through an authenticated gateway.

### What is the Model Context Protocol?

The Model Context Protocol (MCP) is an open standard that lets AI applications discover and call outside tools and data in one common way. An MCP server offers tools; an MCP client, such as Claude, ChatGPT, Cursor or VS Code, connects to it and lets the model call them.

### How do I deploy an MCP server?

Install the gxmesh CLI, sign in, scaffold a tool with gxmesh new and run gxmesh push. The platform builds it and hosts it for you, and your project's MCP endpoint serves the tools you enable. There is no server for you to run.

### Which languages can I use?

Go, TypeScript and Python. A tool that only calls an API needs no code at all: you describe the request in YAML. Each project's code runs in its own AWS Lambda, and every outbound call and database connection goes through the egress gateway.

### How do I connect MCP servers to AI clients?

Each project has one MCP endpoint. Any client that supports remote MCP over Streamable HTTP with OAuth, such as Claude Code, Claude Desktop, Cursor or VS Code, can connect to it and sign in through the gateway. The console's Connect page shows the endpoint and each client's setup.

### Should I self-host my MCP server or use managed hosting?

Self-hosting means you run the server, TLS, OAuth for remote clients, secrets, scaling and logs. Managed MCP server hosting takes those off your hands: you push tools and get an authenticated endpoint. Self-host when a server must run inside your own network or on a user's machine.

### How are API keys and secrets kept safe?

Secrets are encrypted and scoped to a project. The AI client that calls your tools never receives your service or model API keys, and each organization's data is kept separate.

### Is there a free plan?

Yes. Free includes a month's usage and 5 AI credits, and calls stop when the usage is used up, so it never bills. Pro is $29 and Team $79 a month (₹2,599 and ₹6,999 in India), each with a month's usage and AI credits included.

### Is the Control Surface available?

The Control Surface is a planned operator interface for automation. This platform focuses on deploying and connecting MCP tools; Control Surface integration comes later.

## Product

- [Console](https://platform.glxymesh.com/): sign in, deploy tools, manage projects, secrets and members
- [Sign up](https://accounts.glxymesh.com/signup): create a free account

## Optional

- [Terms of service](https://policies.glxymesh.com/terms/)
- [Privacy policy](https://policies.glxymesh.com/privacy/)
- [Refund and cancellation policy](https://policies.glxymesh.com/refunds/)
- [Acceptable use policy](https://policies.glxymesh.com/acceptable-use/)
- [Service delivery](https://policies.glxymesh.com/delivery/)
- [Grievance officer](https://policies.glxymesh.com/contact/)
- Support: support@glxymesh.com
- [LinkedIn](https://www.linkedin.com/company/glxymeshhq/), [X](https://x.com/GlxymeshHQ), [YouTube](https://www.youtube.com/@glxymesh), [Reddit](https://www.reddit.com/user/glxymesh/)