AgentSearch is a self-hosted search API for AI agents that need web retrieval without depending on paid hosted search products. The official README describes 16 endpoints, nine-strategy content extraction, optional Tor-anonymized stack support, no API keys, no per-query fees, and no vendor lock-in. It is useful for developers building research agents, RAG systems, automation tools, or MCP-style assistants that need repeatable search and page extraction under their own control. AgentSearch is notable now because search is a core tool for autonomous agents, but hosted APIs can become costly or restrictive at scale. By packaging search and extraction as a self-hostable service, it gives builders a practical infrastructure option for private or cost-sensitive agent workflows.
Reader rating
No ratings yet
You might also like
codemap is an MIT-licensed project brain for AI coding tools that gives LLMs instant architectural context from your codebase without burning tokens. It generates a fast tree/context view, dependency flow, dependency blast-radius analysis, and a layered handoff format for cross-agent continuation, then exposes everything through a JSON context bundle and an MCP server compatible with Claude Code and Codex. A built-in Codex plugin and community skill registry make it easy to install and share. Developers use codemap to onboard agents to large repos in seconds, keep session continuity across handoffs, and scope the impact of a change before running it.
Type.com is a multiplayer AI workspace where teams collaborate with Claude, Codex and other models in a shared company context. It brings conversations, files, skills, integrations and automations into collaborative Spaces instead of leaving useful work trapped in individual chat windows. Marketing, sales, support and operations teams can tag Type from Slack or email, share access through role-based permissions, and build custom dashboards or internal apps grounded in company knowledge. Type also supports OAuth, MCP and API connections, with granular controls for users and spaces. It is notable now because its Product Hunt launch presents a practical answer to the coordination problem emerging as teams adopt multiple coding and general-purpose agents. The official site confirms a shipped cloud workspace with desktop and mobile access, not merely an agent concept.
Ollama is a local AI platform for running, managing, and sharing open models on your own machine or private infrastructure. It makes it easy to pull models, serve them through an API, and integrate local inference into developer workflows without relying on a fully managed cloud stack. Teams use Ollama for privacy-sensitive assistants, internal tools, offline experimentation, and rapid testing of open-weight models across laptops, workstations, and servers. It is especially useful for developers, operators, and AI builders who want quick setup with less operational overhead. What makes Ollama distinctive is how approachable it is: it packages model runtime, distribution, and deployment into a streamlined experience that helps people get productive with local AI in minutes instead of spending days on configuration.
From the blog
Gemini 4 Argon launches at $2/$10; Meta's Muse Wonder reaches frontier tier at half Anthropic's cost. Dyna-2 robotics hit 99.4% autonomy. Decision models emerge as a product category. Frontier labs sprint week resets pricing for Q4 2026.
Anthropic released Haiku 5.5 at Luna pricing. That's a 75% cost reduction from Haiku 4.4, and it forces every builder to rethink their entire model architecture. Small models now handle what frontier models used to do. Unit economics change overnight.
OpenAI published 722 math papers solving 90 open problems, then fired the safety researchers overseeing external evaluation. A week that defines the tension between capability and oversight.
