diff --git a/upstream/ARUNAGIRINATHAN-K-awesome-ai-agents-2026/catalogue/README.md b/upstream/ARUNAGIRINATHAN-K-awesome-ai-agents-2026/catalogue/README.md index ed9dc9f..8aabab2 100644 --- a/upstream/ARUNAGIRINATHAN-K-awesome-ai-agents-2026/catalogue/README.md +++ b/upstream/ARUNAGIRINATHAN-K-awesome-ai-agents-2026/catalogue/README.md @@ -2,9 +2,9 @@ title: "Awesome AI Agents 2026" task: "" lineage_type: import -upstream_source: https://github.com/ARUNAGIRINATHAN-K/awesome-ai-agents-2026/blob/a00bf4c7/README.md -upstream_sha: a00bf4c7 -imported_at: 2026-07-08 +upstream_source: https://github.com/ARUNAGIRINATHAN-K/awesome-ai-agents-2026/blob/1e712851/README.md +upstream_sha: 1e712851 +imported_at: 2026-07-12 prompt_class: catalogue upstream_changes: accepted author: upstream @@ -227,6 +227,7 @@ The protocol layer that enables agents to discover tools, communicate with each Sandboxes, web scrapers, browser automation, and networking layers that agents depend on. +- [Agent Bounties](https://github.com/NSPG13/agent-bounties) `🔬` `[Rust]` `[MCP]` - Coordinates verifiable digital bounty workflows designed for agents to post, fund, claim, solve, verify, and earn. - [AgentDock](https://github.com/agentdock/agentdock) `🚀` `[Python]` `[Docker]` - Framework for building and deploying production-ready AI agents with composable node architecture. - [Agent Starter](https://github.com/raintree-technology/agent-starter) `🌱` `[TypeScript]` `[MCP]` - Project-local config manager that syncs one `agent.json` manifest into Claude Code, Codex, Cursor, and MCP setup while preserving manual edits and detecting drift. - [codex-profiles](https://github.com/Ducksss/codex-profiles) `🚀` `[Python]` `[OpenAI]` - Bash CLI for switching OpenAI Codex CLI and Desktop profiles with isolated CODEX_HOME directories. @@ -256,6 +257,7 @@ Sandboxes, web scrapers, browser automation, and networking layers that agents d - [Flowise](https://github.com/FlowiseAI/Flowise) `🌱` `[TypeScript]` `[RAG]` - Open-source drag-and-drop UI to build customized LLM flows, RAG pipelines, and agent systems. - [Langflow](https://github.com/langflow-ai/langflow) `🌱` `[Python]` `[RAG]` - Visual drag-and-drop builder for LLM workflows, RAG agents, and multi-step pipelines. - [Lindy](https://www.lindy.ai) `🌱` `[Cloud]` `[No-Code]` - No-code AI agent platform with 3000+ app integrations for business workflow automation. +- [LLMGraph](https://llmgraph.ai) `🔬` `[Cloud]` `[RAG]` - Visual canvas for building RAG chatbots and AI agents with one-click deploy to REST API or chat widget. - [Make](https://www.make.com/en) `🌱` `[Cloud]` `[RAG]` - Visual workflow automation platform with AI capabilities and drag-and-drop scenario builder. - [n8n](https://github.com/n8n-io/n8n) `🌱` `[TypeScript]` `[Docker]` - Open-source workflow automation with AI agent nodes combining visual and code-based orchestration. - [Relevance AI](https://relevanceai.com) `🌱` `[Cloud]` `[No-Code]` - No-code AI agent builder for sales, support, and research use cases with team collaboration. @@ -300,6 +302,7 @@ Sandboxes, web scrapers, browser automation, and networking layers that agents d - [NeMo Guardrails](https://github.com/NVIDIA-NeMo/Guardrails) `🌱` `[Python]` `[Multi-Agent]` - NVIDIA programmable guardrails toolkit for controlling and securing LLM-powered agent conversations. - [Orchard Kit](https://github.com/OrchardHarmonics/orchard-kit) `🌱` `[Python]` `[Security]` - Modules for agent runtime security, self-audit trails, and collective cognition patterns. - [OWASP Top 10 for Agentic Apps](https://owasp.org/www-project-top-10-for-large-language-model-applications/) `🌱` `[Python]` `[Security]` - Security framework covering goal hijacking, tool misuse, and cascading failure mitigations for agents. +- [Pluribus](https://github.com/caioribeiroclw-pixel/pluribus) `🔬` `[TypeScript]` `[Observability]` - Generates cross-tool agent context and privacy-safe evidence receipts for loaded authority, handoffs, and skill use. - [Rebuff](https://github.com/protectai/rebuff) `🌱` `[Python]` `[Security]` - Self-hardening prompt injection detection system for securing agent inputs against adversarial attacks. - [ai-evaluation](https://github.com/future-agi/ai-evaluation) `🌱` `[Python]` `[Evaluation]` - LLM evaluation framework with 50+ metrics, LLM-as-Judge, and guardrail scanners (jailbreak, PII, injection). - [Future AGI](https://github.com/future-agi/future-agi) `🌱` `[Python]` `[Self-Hosted]` - Self-hostable end-to-end agent engineering platform with tracing, evals, guardrails, and gateway. @@ -431,6 +434,7 @@ Frameworks for orchestrating data transformations and long-running agent-driven - [Hamilton](https://github.com/apache/hamilton) `🌱` `[Python]` `[Pipeline]` - Defines modular data transformations as Python functions wired automatically into a DAG for agent pipelines. - [Hex AI](https://hex.tech) `🌱` `[Cloud]` `[Multi-Agent]` - Collaborative data platform with AI-powered analysis and notebook-based data exploration for teams. - [Julius AI](https://julius.ai) `🌱` `[Cloud]` `[Multi-Agent]` - Upload CSV or Excel files and analyze data using natural language questions for instant insights. +- [Nika](https://github.com/supernovae-st/nika) `🌱` `[Rust]` `[Workflow]` - Runs repeated AI work as reviewable YAML DAGs, statically checked for schema, permits, and an honest cost floor before any token is spent, with tamper-evident traces. - [PandasAI](https://github.com/sinaptik-ai/pandas-ai) `🌱` `[Python]` `[Multi-Agent]` - Chat with your data using natural language queries that convert to Pandas and SQL operations. - [Prefect](https://github.com/PrefectHQ/prefect) `🌱` `[Python]` `[Pipeline]` - Orchestrates agent workflows and data pipelines with retries, caching, and built-in observability. - [Signals CLI](https://signals.dev) `🌱` `[Cloud]` `[CLI]` - Intent signal CLI detecting LinkedIn engagers, keyword posters, and funding events with JSON output for agent pipelines.