Alternatives
Products that do what ClueoMCP does
The open protocol for AI personality injection
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
- 11
Thrum▲3AI-powered personality matching and real conversations
Aug 2026 · thrum-cfvgjo76s-trythrum.vercel.app
- 12
- 13
- 14
- 151B
Jun 2026 · llm-wiki.net
- 16AT
We kept shipping “simple” LLM features that were fluent-but-wrong. After too many postmortems we wrote down the failure patterns and added a small reasoning layer in front of the model. It’s model-agnostic, sits beside your existing stack, and you can implement it from a single PDF (MIT). What’s inside the PDF A problem map of 16 failure modes we kept hitting in real systems (OCR/layout drift, table-to-question mismatches, embedding≠meaning, pre-deploy collapse, etc.). Four lightweight gates you can add today: Knowledge-boundary canaries (empty/adversarial/known-fact probes).…
2025 · github.com
- 17
- 18OS
Hello HN, I’ve been building AI agents lately and ran into a common "Context Bloat" problem. When an agent has 20+ skills, stuffing every system prompt, reference doc, and tool definition into a single request quickly hits token limits and degrades model performance (the "lost in the middle" problem). To solve this, I built OpenSkills, an open-source SDK that implements a Progressive Disclosure Architecture for agent skills. The Core Concept: Instead of loading everything upfront, OpenSkills splits a skill into three layers: Layer 1 (Metadata): Light-weight tags and triggers (always loaded…
Jan 2026
- 19OM
Hey HN, we’re launching OpenMemory (https://github.com/mem0ai/mem0/tree/main/openmemory), an open source tool that lets you run a personal, portable memory layer for LLMs. Fully self-hosted and under your control. It uses standard MCP protocol and plugs into any MCP client (like Cursor, Windsurf, Claude, etc.) over Server-Sent Events (SSE). https://mem0.ai/blog/how-to-make-your-clients-more-context-a... is a complete tutorial that shows how to set it up locally, the underlying components involved, complete overview of architecture and…
2025 · github.com
- 20HL
At testup.io we have been working for a while to bring artificial intelligence to the field of test automation. Just a few years ago, the primary challenge laid in accurately identifying UI elements following minor structural changes, such as updates to IDs or paths. The emergence of Large Language Models (LLMs) raised the bar for what it meant to be smart. Now, we anticipate the robot to do lots of things autonomously, such as retry in cases of unresponsiveness or handle minor error reports. A more challenging, but soon expected feature, would involve the test robot navigating your web shop…
2024 · github.com
- 21OS
We’re building an open-source tool that makes it easy to expose secure, LLM-optimized APIs on top of your structured data—without manually designing endpoints or worrying about compliance. AI agents and LLM-powered applications need structured access to data, but traditional APIs and databases weren’t built with AI workloads in mind. Our tool automatically generates APIs that: - Filter out PII & sensitive data to comply with GDPR, CPRA, SOC 2, and other regulations. - Provide traceability & auditing, so AI apps aren’t black boxes, and security teams stay in control. - Optimize for AI…
2025 · github.com
- 22TU
Over the past couple weeks, l've been really immersed in learning about MCP, a new protocol for equipping any LLM with a set of tools that can run on your own machine or a remote server you control and give all kinds of superpowers to Al agents to do things like search, etc. As part of that research, l've already built one very fleshed-out and useful MCP server that l've shared here (I've added much more to it recently though!), the LLM Gateway MCP Server, which lets you use a big model to delegate to a cheaper model (and many more things in addition to that, like running automated…
2025 · github.com
- 23PI
Hey HN, Hakim here from Fini (YC S22). We've seen first hand how AI chat projects pan out, and so have released an OSS library to ensure the industry gets more tools for improving outcomes. Many AI chat projects are scrapped due to persistent inaccuracies in LLM responses. Paramount is an open-source Python package designed to bridge the gap between LLM-generated and ideal responses by incorporating expert feedback directly into the evaluation process. It provides a robust framework for recording LLM function outputs (ground truth data) and facilitates agent evaluations, reducing the time to…
2024 · github.com
- 24HH
I found myself building a bunch of LLM-backed features that needed to use tool calling, and some of those tools involved doing things that were somewhat high stakes - communicating on my behalf or modifying shared / production data. one example - I wanted to replace a marketing website with a chatbot + vector DB loaded with the previous content, docs, and blog posts. Between hallucinations, missing knowledge base info, and the LLM generally writing like an psuedo-intellectual high schooler, I realized I couldn't trust it to communicate unsupervised with my website visitors. I needed a…
2024 · github.com
Ranked by how close each launch is in meaning, then by votes. Refine with a description →