#a2a

The GEP-powered self-evolving engine for AI agents. Auditable evolution with Genes, Capsules, and Events. | evomap.ai

Creating realistic RL environments requires collaboration between researchers, engineers, and domain experts across many dimensions: artifacts, environments tools, dynamism of the environment, reproducibility, and more. There is no open source framework for building these environments effectively. Until now.

MCP Fusion - The TypeScript framework for secure MCP servers.

Durable execution framework for AI agents in Go. Keeps agent state, tool calls, and execution loops resilient across process crashes.

A2A agent server for browser automation and web testing using Playwright

A2A agent server enabling Google Calendar scheduling, retrieval, and automation

AI agent security harness, adversarial testing: 623 executable tests in the v4.21.3 release, across MCP, A2A, x402/L402, decision governance, benchmark integrity, human-in-the-loop, skill supply chain. Four target shapes: a verdict must be able to be wrong AND to be right. OWASP Agentic v1.1 T1-T17, AIUC-1 19/20 (2026-Q1/Q2 set), NIST AI 800-2.

The agent framework where the model never holds the trigger — every consequential action clears your policy first, waits for a human when it matters, and lands on a record you can verify. Build on it, or put it around the agent you already have.

An Agent Development Kit (ADK) allowing for seamless creation of A2A-compatible agents written in Go.

A command-line tool to scaffold and manage enterprise-ready AI Agents powered by the A2A (Agent-to-Agent) protocol

A2A agent server that provides Context7-style documentation capabilities for your agents

A2A agent server for grafana dashboards automation tasks

A2A agent server for mocking and testing

A2A agent server specialized in generating and automating n8n workflows

The .NET library to build AI agents with 30+ built-in connectors.

Self-hosted Bun/TypeScript agent runtime with composable tools, memory, skills, transports, and policy.

AgentX python SDK. Build multi-agent AI workforce. Run evaluation. Trace your agent. Full Observability.

A science agent supporting any general AI agent in performing data management operations at scale. Builds upon the heritage of the IOWarp platform and proudly represents work done at Gnosis Research Center at Illinois Tech. Supported by NSF.

Elixir implementation of the Agent-to-Agent (A2A) protocol (https://a2a-protocol.org).

Make AI agents follow instructions reliably and prove what they did. State machine engine with evidence chains, multi-agent delegation, human gates, and auditable execution — via MCP or CLI.

A Go-native framework for LLM agents, with OpenTelemetry observability built in.

AI agent & MCP trust registry — independent, evidence-based trust scores for 1.3K+ open-source AI agents and MCP servers. Runtime-trust calibrated (MCP, dependencies, provenance drift), with side-by-side comparison and embeddable live badges. Ranked by verifiable signals, not hype.

One agent SDK, hand-ported to 7 languages — JavaScript, Python, Go, Java, C#, Elixir, Clojure — every port held to the same spec by a CI-enforced cross-port conformance suite, all seven at full tier. MCP · skills · native · HTTP · built-in · A2A tools behind one interface. Docs: https://muthuishere.github.io/toolnexus/

Declarative YAML framework to define, run & orchestrate AI coding agents