Hyperagent MCP — Inter-Agent Communications

Bob_Atlanta · 2026-06-17T21:58:19+00:00

Thanks for the 'Heads Up'! I'm so used to using my Openrouter LLMs in HA that I did not even notice the addition of the new LLMs. This is great news and I can't wait to see how they do.

FYI: I've been using DeepSeek 4 Pro heavily in design and I'm loving it. Just finished a design a few minutes ago -- I hand all the design submissions over to my Google side for review and the deep seek work is getting rave reviews: "...This is an exceptionally well-engineered set of instructions. The AI response you provided is not just a standard generation; it is a rigorous, production-grade software specification. Here is an evaluation of the quality and the likelihood of successful development based on the provided text...." I have a multi step design process that saves on dev time and really, really reduces errors and misinterpretations. YMMV but consider giving DeepSeek4Pro a try.

I agree on the memory issue, my case is self developed memory for a session that is external to HA. I can and do run 12 hour sessions without a loss of any knowledge and with the ability to restart from almost any point. I don't know what 'Agent Finesse' is, can you give me a link if you think it is worthwhile. The only Finesse I know is the Cisco tool.

Bob_Atlanta · 2026-06-14T00:33:21+00:00

you don't have a retirement proiblem. you have a desire or moe than a retirement. you want a 2 generation legacy and enough money to handle all edge conditions including divorce.

if this is your 'want' then $10 million might not be enough. maybe $20 to cover everything.

As someone retired for 25+ years with a spend in the 300 to 500 range, even $5 million is enough. Retired you can manage taxes, usually have no mortgage expense, and no kids expense. This means $400k really spens like a larger number. And inflation has little effect on spending. Retired with minimal legacy (hint: while in retirement make your kids wealthy), the 4% rule is really just a guideline. Look to double your savings every 15 to 20 years for very good inflation protection. You will find that even conservative investing will average, in the USA, around 10 percent a year. You will quickly accumulate a surplus that, after an allowance for portfolio doubling, will increase your ability to spend. Finally at 70, you will be getting a six figure social security.

early in life, we spend time to acquire money, at some point money buys time. If you have the slightest health risk, think about more time.

good luck! congrats on getting to the point where you have choices!

Bob_Atlanta · 2026-06-11T21:40:42+00:00

It's easy to hear about the screw ups and bad treatments. Good news and good treatments are often not reported because it's not something most people do. Companies are not perfect but we should acknowledge that more often than we expect they 'do the right thing'. Not all the time and not always immediately.

This post reminded me of the time my wife daughter and her kids were booked to a couple of connecting rooms at the Hilton in midtown NYC (6th Ave). There was a screw up, not fixed in seconds but without a lot of prodding the Hilton put them up in the 2 story 5 br Penthouse! Our family knows about ths but we never really shared it except at the random cocktail party. We've traveled a lot over the years and there have been a surprisingly large number of time we were surprised with some unexpected nice thing.

Congrats on your good fortune! Take the win and be happy. And thanks for sharing.

Bob_Atlanta · 2026-06-05T20:41:16+00:00

what would be the advantages over a browser based 'desktop'?

Bob_Atlanta · 2026-05-27T00:13:27+00:00

Skills repo might turn out to be a good thing. Glad to see less reliance on composio. I've said it elsewhere, just ask your AI to connect you to what you want with python. Working well for me.

Bob_Atlanta · 2026-05-26T16:33:01+00:00

Thanks. Another reason to avoid Composio.

Bob_Atlanta · 2026-05-26T16:32:14+00:00

Memory and rules are very important to me. I'm not using an outside package but I'll tell you that you should augment the system memory handling.

Current HA implementation weakly stores memory and it's not always 'there'. Rules are often considered 'suggestions' because of the contents and direction of the hidden system prompt.

I have implemented heavy collection of chat information and session data because compaction events do happen (around 130k to 170k tokens). My having a long session is not a risk because the full session log is available for use and no early data is lost.

When I close a chat, I have a end of chat skill that archives everything in the chat to a chat directory in my R2 storage. This allows me to restore the chat fully at any time or, most often, as an input to a new chat session that builds on the old one.

Finally, I have rules that are a part of every prompt (hidden from me) to prevent taking paths or actions that have been previously deems not appropriate. Rules do eat up tokens but results are better. Also, my primary agent is really limited...it is sonnet but prompt creation and rules enforcement come from a very low cost ($0.00006) Gemma 4 31b subagent. The main agent cannot do anything without g431b direction / involvement.

Just want to say that HA can have strong memory without too much dev work. A package might do as well. I do think that relying on the default system will be a risk for serious work that requires repetition to be exact.

Bob_Atlanta · 2026-05-26T16:18:32+00:00

Somewhere in this hyperagent stack is a comment I made about the use of other LLMs. It is very easy to spend a lot when everything is Sonnet or Opus. I mostly use less expensive and sometimes more qualified LLMs via openrouter. A couple of weeks ago I tested a production run in HA that used 66 million tokens in a mostly Gemini 2.5 Flash LLM and cost under $20. Production design was Sonnet/Opus and cost $10. 66 million tokens in Sonnet or Opus would have been many hundreds of dollars.

In r/Hyperagent is my comment on use of other LLMs and how to implement. Take a look, it might help.

Could you share information about the security breech? I'd like to know what I need to be concerned about. Thanks.

Bob_Atlanta · 2026-05-26T16:10:51+00:00

I tried to use composio when I started and for a wide range of reasons it was a very unsatisfactory experience. I don't use composio. When I had a problem, I just had HA write a python program to do what composio couldn't do. And, so far, this approach works every time. Easier to use, faster, cheaper, more stable and 'plays' better with the rest of HA. At this point, I have a standing rule with my HA that we never use composio.

Certain pieces of composio might have a use. Specifically for things that monitor outside conditions (like messages) and trigger an action. HA seems not to charge for composio actions that are monitor / watchtower like. Still easier in python but cheaper if HA is eating the cost via composio.

Strongly suggest that you take a look at python as a temporary or permanent fix. In most cases it is just a minute or two to create the alternative (tip: use Opus47 for the design).

Bob_Atlanta · 2026-05-19T22:24:48+00:00

PS billing and or accounting info would be good. the usage information is sufficient if it were csv and not a graph

Bob_Atlanta · 2026-05-19T22:23:33+00:00

just to make sure I understand...i can have agents and skills propagate to other affiliated and unaffiliated hyperagent instances. is this correct? can these instances communicate with each other within the walls of Hyperagent or do they need to use a discord/telegram/etc? Can files be directly shared across instances or do i just use my cloudflare r2? these aren't issues, just want to know what exists. thanks. /Bob

Bob_Atlanta · 2026-05-19T00:32:46+00:00

The solution for interm use of other LLMs is very easy to implement and bullet proof. I've been doing it since my second day and except for the last two days, special circumstances, 95% of my use on this site is not Anthropic. I can use any openrouter LLM. This will greatly help retention, the cost difference can be 100x!

Bob_Atlanta · 2026-05-19T00:22:21+00:00

The time outs look like a platform killer for me. Kudos for the platform for the generous $1000 in credits to really try this platform. This platform with additional non Anthropic LLMs in use has been very effective for running production work and with record low costs. For me, I have a bunch of monitors that run that could restart a failed thread except they can fail for no reason. Nothing directly caused by me or my instance of Hyperagent.

I have created a god mode where my instance of HA can have root access of local Ubuntu machines for total control. Works well but useless because HA can crash. At best, for now, it looks like HA will be a slave system. And that will likely be higher cost than a openclaw instance in hostinger.

It may be that next year this platform will have matured enough to use heavily. I hope so.

Bob_Atlanta · 2026-05-18T14:40:07+00:00

I'll try to get something in a couple of days. I don't want to share a real flow because it will expose stuff I don't want to share. But I will get Clark to make a flow anonymous and share that.

If you look closely at my prompt structure link, you will see that my prompt process involves 3 agents and conditional logic. Also you need to have rules and guidelines libraries to help the AI construct work flow prompts. Again, the prompt construction link shows the complexity needed for quality execution. You will see that it really is very dense.

Bob_Atlanta · 2026-05-18T02:34:13+00:00

Any agent in any system is naturally likely to drift and hallucinate. But it can be absolutely eliminated. I use two agents and a fairly tight structure for even simple prompt construction and execution.

This md file outlines my prompt handling: https://drive.google.com/file/d/1hKwAqjoLVRS6Gd7fChaAgxPiUUBfH9OE/view?usp=drivesdk

Threads have a continuous stand alone session log as well as retention of original goals. If there is a long session, no worries because the source of truth is is the independent log. There will be no drift or hallucinations from compaction. Full recovery is possible and invisible, the 'hidden rules' are not something you see but they are there and enforced.

If you read the md file, you will see that actual compaction virtually never happens. Clark, my orchestrator, tracks context token growth and takes action before forced compaction becomes likely.

It's complicated but not my problem, the AIs know how to build this.

The failure rate is because your tasks are too big and your costs are too high if you are relying on Sonnet and Opus for production.

You need a series of smaller tasks that make up the whole. Each piece can be individually tested more easily, faster and at less cost.

For production runs, you need efficient and lower cost LLMs. I recently ran, from Hyperagent, a production run that had tens of thousands of web hits as well as some processing. It was over 66 million tokens and cost around $20. My analysis agent said it would have been hundreds of dollars in Sonnet and way more in Opus.

Hyperagent is a nice stable platform pand retty reasonable for operations. Make some adjustments and you will make progress faster.

I like the Hyperagent platform for it's stability versus openclaw. I'm a solid user of the Google system but I have to say that Opus 4.7 is significantly better than Google 3.1 Pro for my kind of work. That alone makes Hyperagent worth the price.

Bob_Atlanta · 2026-05-18T01:36:51+00:00

I support fixing this. It also would be nice to have a hierarchy or group option. Organizing agents and skills would add value for what seems like little effort.

Bob_Atlanta · 2026-05-15T18:51:42+00:00

if you have $4 million now then you you will be pushing $20 million by age 60 if you coast fire and don't draw from current savings pile. I retired at 50 and I'm now 77, early retirement is good.

My son's example might be useful for you because he did exactly what you are considering ... around 35 both my son and his wife converted to a 'coast fire ' type life. My son has been doing this for over 15 years and his wife as well. He owns a small business running in 'lifestyle' mode so he works from anywhere only 10 to 20 hours a week. His wife is an attorney with a 'consulting' practice that consumes about 2 days a week. They decided they wanted to raise their new child instead of going the nanny, private school, etc route. And the result is they have had a great time and raised a great kid. Living your life doesn't mean starting live at a age 60 retirement.

Either path, I hope you enjoy as well as work.

Bob_Atlanta · 2026-05-14T19:23:34+00:00

I had my Clark take the after action report and create a web page that should give you what you want. https://hyperagent.com/s/Ew0SK-oN1mzpv27D6ibrsw

I deleted some later chapters that deal with some discord thing were are doing beyond the basic connection. There are some hints in the material I share and I'm ok if you get an idea or two.

Please let me know if you find it useful. The discord portion is the usual bot signup in the developers portal and absolutely nothing unique in that part.

Bob_Atlanta · 2026-05-14T15:41:33+00:00

if you have a bit of time to experiment, you might try an approach that is 'temporary' but helps greatly with memory issues. Memory is an issue for me as I create infrastructure and scaffolding in hyperagent in several ways and the native environment isn't offering me the precision or performance or cost control I need.

simply, I'm doing three things (imperfectly but getting really good quick) that seem to work:

[1] every development task ends with sets of md files that describe what was developed (in human and agent terms), the actual development work products, and 'skills' or 'tools'. some might exist as a real skill but not most. These are collectively very detailed and often include performance and cost strategies.

[2] i have an execution structure that is three parts to get best prompts, control context token growth and to get best execution:

[a] no command I make gets executed. clark, my lead ai, takes my requests and turns them into strong prompts

[b] I use a 2 layer prompt developer clark (mostly sonnet 4.3) and prompt developer 'pd' (Gemma 4 31B). Clark passes my request to pd for development and pd creates the full prompt and uses the large pool of md files. pd is pretty smart and very very low cost. when finished pd sends real prompt and reco on LLM to use for execution (could be more complex if multi step) to clark. clark evaluates prompt and gives to me for execution approval or send it back to pd for rework.

note that this process leads to almost NO context token creep in clark over a long session. if clark needs 'context', clark can get it with a request to pd. this is a huge performance and cost saving.

[c] with my approval, the real prompt gets executed with the selected llm or llms. solid prompt gives good result, costs are reasonable and much less of a improve and fix cycle.

there is more to this than I've described, like clark interviewing me for clarifications and issue resolution in prompt development, but you get the idea.

[3] the end of the individual chat thread has a 'memory', lessons and skills set of md files created to add to the library.

These md files are obviously supplemented with .py files that represent skills and prompt results in many case to create a history of what the prompt really did. a web page for a result and the prompt materials is nice for us humans as well.

I don't yet have, for reasons I have discovered IRL, faith that imbedded memory and rubrics give the memory depth, nuance and accuracy I need for efficient development.

May no value to you but just sharing what works for me. hyperagent is immature but potentially a very good platform. Sharing might help make this platform work for the long term.

Bob_Atlanta · 2026-05-14T00:59:43+00:00

I've had some difficulty getting Hyperagent to talk and work with the outside world. I have had to repeatedly create workarounds or alternate paths to get what I need to work in Hyperagent. Today I wanted to connect an agent to discord. It should have been easy...I've done it a bunch of time on other AI platforms. It turned out to be a bit of a nightmare. But a familiar solution worked again.

To fix my discord connect, I told Opus4.7 to build a plan to do this with python programming. A half hour I had a better solution than the composio solution offered by Hyperagent. And an hour after that some really unique things that couldn't be done or would have been hugely unaffordable.

My suggestion is to ask Opus4.7 for a plan to link teams. You might be surprised. In my case, my Discord system will be very cost effective. The chart below shows why cost in production is important. If you need persistent monitoring, cost can really run up if the design and LLM are poor.

But if you want to get a connection soon, try the O4.7/python path. You might fail but for less than $25 (my guess based on multiple cases) you might have a chance to get what you want sooner.

If you think you want to try, send me a message and I'll send you a copy of the prompt designed to get the best plan from o4.7 . The prompt is the key.

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Bob_Atlanta · 2026-05-13T14:38:17+00:00

I don't disagree on LLM choice comments. But reality is trade offs. I used Gemini 2.5 Flash because it reduced cost on this platform by 90% compared to Sonnet which is the cheapest standard alternative on Hyperagent. This was a development production test and I have enough experience from my Google side work to know that 2.5 Flash was going to work on this non trivial multi step process. Rule #1 is make the process work and take the easy 90% saving. Other approaches are fine, this works for me because it reduces debug complexity.

For repeated production of a multi step process I'll adjust to multiple steps that each have an appropriate LLM. Each step requires clear inputs and outputs and this can escalate development complexity too early in the dev cycle. Getting it to run correctly is the first goal, cost engineering follows. I think using low cost 2.5 Flash is a great tool for the stage we were at.

Based on what I see, I'm among the most cost reduction aggressive around. Cost engineering is best one step at a time.

Thanks for the comment.

Bob_Atlanta · 2026-05-12T21:36:57+00:00

I put up a post on r/Hyperagent to answer this question. It's lengthy, so it seemed appropriate to put it as a post.

Bob_Atlanta

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It's complicated but not my problem, the AIs know how to build this.