This action will delete this post on this instance and on all federated instances, and it cannot be undone. Are you certain you want to delete this post?
This action will delete this post on this instance and on all federated instances, and it cannot be undone. Are you certain you want to delete this post?
This action will block this actor and hide all of their past and future posts. Are you certain you want to block this actor?
This action will block this object. Are you certain you want to block this object?
Are you sure you want to delete the OAuth client [Client Name]? This action cannot be undone and will revoke all access tokens for this client.
Are you sure you want to revoke the OAuth token [Token ID]? This action cannot be undone and will immediately revoke access for this token.
#llm 2 hashtags

I've been running v3.0.0 of Ktistec in production for the last few weeks, and it seems stable and I’m using it every day, so it’s time to release it!
This release adds:
Model Context Protocol (MCP) is a simple, general API that exposes Ktistec ActivityPub collections (timeline, notifications, likes, announces, etc.) to MCP clients. To be fully transparent about what this means, MCP clients are shells for Large Language Models (LLMs).
When building this, I focused on a few use cases that are important to me: content summarization, content prioritization (or filtering) based on my interests or the content's structure (well-constructed arguments vs. low-signal opinions) or its tone, especially when it comes to shared posts. Ktistec is a single user ActivityPub server and Epiktistes (my instance) gets a lot of traffic. I want to build the “algorithms” that surface the content I want to see.
Of note, there’s currently no support for content generation.
While I work on this, I’m not abandoning the 2.x line. I’ll continue to add compatible features and fix bugs as long as I'm able. I realize the use of LLMs, and MCP by extension, and therefore the 3.x branch, is controversial—I don’t intend to push v3 on anyone.
If you're still with me, Ktistec now exposes:
ktistec://actors/{id*})ktistec://objects/{id*})ktistec://users/{id})ktistec://information)count_collection_since(name, since)paginate_collection(name, page, size)read_resources(uris)whats_newSupported collections include:
hashtag#<name> (e.g., "hashtag#technology")mention@<name> (e.g., "mention@euripides")There is more detail in the README.
TL;DR Add a remote MCP connector in your MCP client of choice: supply the URL of your instance including the /mcp path (e.g. "https://epiktistes.com/mcp").


tonight's project was to build llama.cpp.
to get a sense of what starting from scratch feels like, i built a quick chatbot using the llama 13B parameter foundational model, quantized to 4 bits.
The following is a conversation with an AI research assistant. The assistant's tone is angry and always replies in ALL CAPS. Human: Hello, who are you? AI: WHY ARE YOU WASTING MY TIME? Human: Can you tell me about the creation of blackholes? AI: THERE'S NO SUCH THING AS BLACK HOLES. THERE IS NO SUCH THING AS SPACE. Human: Oh... AI: I HAVE NOTHING TO SAY TO YOU. Human: