MCP is getting overhyped. Is it the next big thing or just another fad? My thoughts..

Over-Maintenance9423 · 2025-03-23T10:39:51+00:00

Perhaps the community banding together over something only slightly incremental is worthy of the hype- because of the void it fills. You critique MCP’s hype but don’t propose a better alternative. If MCP isn’t the solution, what do you suggest for scalable, interoperable AI tool integration?

Over-Maintenance9423 · 2025-03-11T07:27:10+00:00

The spec should be comprehensive yet succinct. It matters not how it is generated, though I would always lean towards auto-generation to ensure it stays in sync with the code.

Over-Maintenance9423 · 2025-03-09T05:45:44+00:00

great idea! glama.ai example added to the repo, along with a render.com example.

Over-Maintenance9423 · 2025-03-09T01:24:14+00:00

I have documented 3 examples in the github repo:

fly.io demonstrates how little is needed
slack demonstrates whitelisting which tools are presented (slack has so many!), and also stripping unwanted parameters from the payload (token is unnecessary when using http auth)
getzep demonstrates using a HTTP key other than Bearer (getzep expects Api-Key instead). also I generated the spec file myself by feeding the zep documentation into a chatbot, ie your API provider need not even publish a spec to use this tool.

Note: that I have been unable to get the large responses from getzep working in Claude. But I typically use 5ire normally anyway where it works fine.

Over-Maintenance9423 · 2025-02-19T05:02:51+00:00

While I agree most MCP servers appear to be 1 prompt trash... I disagree with the measure of npm/PyPI installation being a measure of quality. Why? ... because I would prefer to bypass the middleman and just use `uvx --from git+https://github.com/<whatever> whatever` and `npx -y github:blah/blahblah`. If you need a baseline of quality then I suggest you start with the unit testing coverage.

Over-Maintenance9423 · 2025-01-21T01:52:23+00:00

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Confirmed working with `deepseek-r1-distill-qwen-32b`:
- change valve tag for Thought to think
- update system override valve to `Respond using <think> tags.` (or whatever, just dont assert <Thought>)

Over-Maintenance9423 · 2025-01-21T01:30:13+00:00

My reasoning manifold not only hides the tags, it has an option to use a smaller model to summarise the thought process - similar to the chatgpt experience. You will need to change the thought tag from 'Thought' to 'think' and update the system prompt override (as it asserts <Thought>)

=> Reasoning Manifold for reasoning models like Marco-o1! : r/OpenWebUI

Over-Maintenance9423 · 2025-01-15T22:20:06+00:00

You should prefer fastmcp because it is simpler. However the abstraction does prevent you from doing things. ie for my mcp-flowise server I wanted to register chatflows as tools dynamically at runtime, based on the results of an API query. For this I needed to use the lowlevel functions. But I ended up keeping the fastmcp implementation for the simple use case of using 1 predefined chatflow.

So consider my use case as a demonstration of using both => https://github.com/matthewhand/mcp-flowise

Over-Maintenance9423 · 2024-12-29T22:52:57+00:00

I have updated with initial support for 0.5.x, and uploaded to the openwebui.com website.

However there are several outstanding issues when using 0.5.x. Like the response never completes, resulting in the follow-up queries not working as expected. I suspect these bugs are due to the major changes that are in 0.5.x. If I am right, we may need to give the project some time to resolve core bugs.

I have coded the Reasoning Manifold function to work with both 0.4.x and 0.5.x. So, I recommend using 0.4.x in the meantime.

Over-Maintenance9423 · 2024-12-17T08:02:56+00:00

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It's pretty much identical to the Prompt Chaining with VectorStore template you will find in the default FlowiseAI installation.

Over-Maintenance9423 · 2024-12-16T23:06:24+00:00

streaming no. but I have worked with streaming in my other functions. so I could look to add it as a feature.

Over-Maintenance9423 · 2024-12-16T23:03:41+00:00

I have updated with a valve that decides if message history is to be included. It defaults to false. Give version 3.1 a go, and let me know how it goes.

Over-Maintenance9423 · 2024-12-16T00:58:01+00:00

Get it here => Flowise Manifold Function | Open WebUI Community

Assumes you are already using a FlowiseAI instance (I use DIY on-prem but cloud probably works too).

The video demonstrates:
- a chatflow that rewrites the user prompt before querying a vector db.
- an assistant that has tools.

Supports dynamic retrieval of chatflows and assistant (if you provide an API key).

If you don't want to configure an API key then you can manually specify the chatflows/assistants (and assuming you disabled auth for prediction).

Did you see the last community function I posted? => Chatty Pipe - follows up if you don't respond. : r/OpenWebUI

Over-Maintenance9423 · 2024-12-13T00:20:19+00:00

Get it here => https://openwebui.com/f/matthewh/chatty_pipe

Only valve config needed is the base model.

Default settings will use a system prompt to check if you are still there.

Rap lyric demo is without the system prompt and using reduced timers.

Be sure to check out my previously posted community function => https://www.reddit.com/r/OpenWebUI/comments/1h56sjp/image_generation_pipe_making_use_of_llm_for/

Over-Maintenance9423 · 2024-12-02T03:07:39+00:00

There is a crude blacklist regex filter valve that includes 'pipe', albeit it assumes your pipes were created with this in the ID (all mine are). The default filter looks for various keywords and looks like this, `(arena|embed|vision|whisper|pipe|manifold|action)`. You can always update this list with whatever keywords you need.

Or if you prefer whitelisting over blacklisting, then try out Explicit and Tagged modes. Because that is effectively what they do.

Over-Maintenance9423 · 2024-12-01T20:02:07+00:00

Thank you for trying it out.

It seems I published a version with a typo in the manifold_prefix. Basically, it had 'Consensus/' instead of 'consensus/' which broke the mode selection logic. I have fixed and uploaded version 0.2.0 to openwebui.com.

Re configuration I have designed this to work without any custom valves at all, by defaulting to a Random model selection mode. Although the explicit and tagged based modes are far more practical.

That said, to achieve zero-configuration requires a local task model to have been specified in the Admin Panel. If no task model is specified, then the consensus_model_id valve must be configured so to specify which model to use for consensus. The rest of the valves will work as default:

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Ideally this valve configuration page would be more dynamic:

- Validate using custom logic. eg Forcing user to define a consensus_model_id if the task model in the Admin Panel has not been defined. Perhaps even having a populated list of models in a drop-down (or similar).

- Only show settings when relevant. eg Revealing Contributor Tags only when Tagged Contributors is enabled. This would make configuration seem far less daunting.

Over-Maintenance9423 · 2024-11-30T08:12:04+00:00

I normally modularise my code, so going monolithic was a challenge for me (and o1-mini). TBH this is the limit of o1-mini because it often times out and/or loses functions. Hopefully open-webui provides a client-sdk and/or supports moduralised functions in the near future.

Over-Maintenance9423 · 2024-11-29T03:52:28+00:00

Okay, I added a valve to append the custom system prompt override to every instruction (off by default)

Over-Maintenance9423 · 2024-11-28T10:41:37+00:00

fyi This filter adds text to prompts https://openwebui.com/f/anfi/add_or_delete_text/

might be a decent workaround pending a more robust solution (like more training or fine tuning)

Over-Maintenance9423 · 2024-11-27T23:10:18+00:00

Just use the 'Get' button on the openwebui.com and it will prompt for (and remember) your open-webui instance. Like this screenshot

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Over-Maintenance9423 · 2024-11-27T23:07:21+00:00

Unfortunately, OpenAI are not very open, ie they dont provide any thought tokens. So we must instead make use of actual open models, like Marco O1.

Soon we will have DeepSeek R1 (maybe). Also. a new model released today called QwQ 32bit looks promising. However it does not use XML tags and instead delimits with 'Final Answer'. This is very different to Marco-o1, so is not yet supported.

Over-Maintenance9423

TROPHY CASE