100% - I'll implement and add that now :)

nice, ship it fast and break things. curious what your persistence layer looks like -- are you serializing full context or just surfacing semantic anchors? the anchor approach is way more interesting imo, lets you reconstruct intent without dragging 50k tokens of cruft into every new session. thats the real trick nobody talks about

I'm not gonna lie - at the moment it's pretty basic as a chunked semantic store where relevant chunks are retrieved in conjunction with some criteria the Agent can pass to the MCP server.

Context usage is definitely a problem that's on my mind also and semantic anchors are one area I'm exploring but don't have a clear architecture for it jotted down yet. The real problem I'm facing right now is how to inject this into say claude or chatgpt and have those agents default use it as a memory layer

for the injection problem - system prompt is your friend. just hardcode "before responding, query your memory MCP tool with relevant keywords" into the system prompt. crude but it works. claude especially follows tool-use instructions pretty reliably when theyre explicit. chatgpt less so honestly. the real trick is making the retrieval call feel like the agents idea, not an obligation - framing it as "you have a memory layer, use it" vs "you must call this tool" makes a suprising difference

That is what I do at the moment - I gotta update the instructions on the website to prod users to set things up this way.

The issue I perceive though is that adding an MCP server alone is not enough to modify the system prompt of the AI Agent. I tried to have the mcp server description be an injected prompt to add these instructions to the system prompt but that doesn't seem to work, I tried adding sampling to the MCP server which supposedly should be able to plug into messages without luck, tried to optimise for chatGPT with an OpenAPI spec etc.

The only way I found that I can get those clients to use my memory layer is by doing what you describe - which is not necessarily the most user friendly/one-click setup I desire

yeah the system prompt injection problem is a real pain. the mcp spec wasnt really designed with "persistent context shaping" in mind, its more request/response than ambient influence.

one hacky workaround ive seen work: expose a tool thats always called first via a resource that hints at it, basically tricking the agent into self-priming. ugly but functional.

honestly though for true one-click youre probably stuck until clients expose better hooks. the spec needs to catch up to the use case.

Tried the resource trick - it's also quite hit and miss. Not all clients properly support resources yet.

I believe you're right and I'm just gonna have to wait or try to engage directly with MCP/Anthropic/OpenAi and further this agenda

Claude Code just added http hooks which are fantastic addition for this problem :) So I've hooked that up with my system. Pretty good start tbh.

http hooks are slick! What’s your anchor strategy? Full context or just the good stuff?

At the moment I'm doing a hybrid but that's still something that needs a lot of trial and error to get right. Doing turn-based context with auto compacting at the moment, but I'm sure that'll change a few more times before it works well

turn-based with auto-compacting sounds tricky. anchors over full context? def way to go for flexibility. keep iterating!