Developer framework for building AI agents that autonomously trade on Polymarket prediction markets. Bundles the Polymarket and Gamma APIs, a Chroma RAG layer that pulls in news, and a CLI to query markets, reason with an LLM, and execute trades.
Runs a native, extensible AI agent on desktop, CLI, or API to automate code, workflows, research, and writing. Built in Rust, supports 15+ LLM providers and 70+ extensions via the Model Context Protocol — designed for local-first automation and developer workflows.
Stores agent memory as human- and agent-readable Markdown files with wikilinks instead of an opaque vector DB. Auto Memory/Resource/Dream jobs distill conversations into long-term notes, and hybrid wikilink + BM25 + embedding search retrieves them.
Desktop finance analytics terminal that combines CFA-level models, real-time trading and 100+ data connectors with embedded Python for analytics; includes 37 AI agents and local/multi-provider LLM support for automated research and decision workflows.
Gives LLM agents self-editing memory that persists across sessions, so they keep learning about a user instead of resetting each chat. Model-agnostic: bring your own LLM while it handles the memory and agent state, run via API or open source.
Give an agent a goal and it plans, then executes each step using AI models and your everyday apps. Build agents via chat-driven AutoPilot, a drag-and-drop builder, or self-hosted code, then run them on a schedule across integrations.
Reviews code in the IDE, CLI, and pull requests, flagging bugs, logic gaps, security holes, and missing tests using context from the whole repo and its dependencies. Enforces team-specific rules learned from past PRs.
Generates and deploys full-stack React apps from natural-language prompts on Cloudflare’s platform, combining AI code generation, previews, Workers, Durable Objects, and containers.
Runs autonomous AI-agent workforces where each agent, skill, and company process lives as version-controlled code you own. Agents act in isolated sandboxes and submit deliverables for human review, with 3,000+ connectors plus MCP support.
Enables agents to autonomously operate GUIs and complete complex computer tasks — includes the Agent S papers and the gui-agents SDK, grounding-model support, and runnable S3 agent implementations for Windows/macOS/Linux.
Agentive operating system for physical robots that lets developers compose agent-native modules in Python to connect perception, spatial memory, and control across humanoids, quadrupeds, drones, and simulators.
Turns any website into a structured, text-like interface that LLM agents can read and act on, handling clicks, forms, scraping, anti-detection and CAPTCHAs. Ships as an open-source Python library plus a hosted cloud API for running browser agents at scale.