These kind of gateways showcase that larger organizations will equip their employees with tools the same way employees are currently granted access to specific SaaS applications.
One of the bigger challenges we are currently observing is missing authorization for MCP servers.
We actually also just released a mcp-gateway[1] initially focusing on adding OAuth authorization to streamable HTTP MCP servers.
I built hyper-mcp[1] as side project with each MCP as a WASM plugin.
The idea is each plugin runs in their own wasm vm with limited network/file system access. Plugins are written in any language, as long as they can compile to WASM and publish to OCI registry (signed & verified with sigstore)
Recently, Microsoft released their own version of hyper-mcp named Wassete[2]
Ideally, I want to make it like a gateway with more security & governance features in this layer.
For many years we were fine with running DLLs, Java .class deps, npm modules, brew packages etc. why do you think we need so much isolation for left-pad class mcp tools?
blitzar · 2h ago
IBM pivoting to Ai, must be getting close to the top now.
N_Lens · 2m ago
Actually already peaked.
fhd2 · 2h ago
Not sure I'd call that a pivot, they've been at it for many years and even at the forefront every now and then, e.g. IBM Watson. At least it seems like that from my non-specialist, outside perspective.
Xantier · 2h ago
I find the context forge quite nice from IBM. I used a few approaches they've implemented within my Ctxpack context management solution as well.
I think the agentic use cases aside, the client side of MCPs are still lacking quite a bit and would need to mature to be able to catch up to the spec. I feel a lot of use cases exist outside of fully automated agentic approaches, since we can't really rely on LLMs yet to produce at a human level.
The underserved cases rely a lot on prompt and resource management at the moment. Being able to iterate and share those across teams to provide easy starting points to delegate tasks is something I feel would be workable for the current iteration of AI assisted work, outside of pure software engineering.
Hopefully other clients join VS Code Copilot to allow more varied approaches than just simple tool calls here. I think Copilot's approach on prompt and resource management isn't quite the best approach either though. It is still early days for MCPs in general so i think we'll see a lot of experiments in this space.
jumploops · 2h ago
Does anyone use MCP within their product, or is the MCP ecosystem entirely focused on enabling new workflows within an existing chat/agent framework (a la Cursor or Claude code)?
Assuming the latter, are there any viable non-developer MCP clients?
MCP is one of the most powerful ways for app-to-app communication. Instead of having to hardcode against an API, the LLM can just request the latest API spec and request what it needs. As a developer you could completely skip the LLM.
MCP, is just a really good M2M documentation.
manojlds · 1h ago
Claude.ai and Claude Desktop are the main non developer MCP clients.
ChatGPT has limited MCP support as of now (read only use cases with deep research) but the expectation is that full MCP support might be dropping soon.
pmig · 11m ago
ChatGPT launching MCP support would dramatically improve adoption, but MCP server installation must become way easier to find non coding use case adoption.
Xantier · 2h ago
I've done a bit of research around trying to find the best, simple clients that don't need an engineering degree to set up but haven't really stumbled upon a good one yet. Claude desktop app advertises that they support all features (they don't), all the others with closer to full spec compliance are related to software development (VS Code and Continue etc.).
thecopy · 3h ago
Many Gateways popping up now, im also doing my own gateway (https://mcp-boss.com/) but im starting to worry its hard to compete with Docker, Microsoft, now IBM...
sublimefire · 8m ago
mcp is not the future IMO, agent2agent is, e.g. a2aproject/A2A
The problem with MCP is that it cannot reliably scale, so some abstraction is helpful, i.e. separate “agent” with its own instructions and a predefined set of tools.
ares623 · 2h ago
You should pivot to building an MCP for all the MCP gateways
One of the bigger challenges we are currently observing is missing authorization for MCP servers.
We actually also just released a mcp-gateway[1] initially focusing on adding OAuth authorization to streamable HTTP MCP servers.
[1]: https://github.com/hyprmcp/mcp-gateway
The idea is each plugin runs in their own wasm vm with limited network/file system access. Plugins are written in any language, as long as they can compile to WASM and publish to OCI registry (signed & verified with sigstore)
Recently, Microsoft released their own version of hyper-mcp named Wassete[2]
Ideally, I want to make it like a gateway with more security & governance features in this layer.
[1]: https://github.com/tuananh/hyper-mcp [2]: https://github.com/microsoft/wassette
[1]: https://github.com/hyprmcp/mcp-gateway
I think the agentic use cases aside, the client side of MCPs are still lacking quite a bit and would need to mature to be able to catch up to the spec. I feel a lot of use cases exist outside of fully automated agentic approaches, since we can't really rely on LLMs yet to produce at a human level.
The underserved cases rely a lot on prompt and resource management at the moment. Being able to iterate and share those across teams to provide easy starting points to delegate tasks is something I feel would be workable for the current iteration of AI assisted work, outside of pure software engineering.
Hopefully other clients join VS Code Copilot to allow more varied approaches than just simple tool calls here. I think Copilot's approach on prompt and resource management isn't quite the best approach either though. It is still early days for MCPs in general so i think we'll see a lot of experiments in this space.
Assuming the latter, are there any viable non-developer MCP clients?
MCP, is just a really good M2M documentation.
ChatGPT has limited MCP support as of now (read only use cases with deep research) but the expectation is that full MCP support might be dropping soon.
The problem with MCP is that it cannot reliably scale, so some abstraction is helpful, i.e. separate “agent” with its own instructions and a predefined set of tools.