agentaegis-mcp
AI developer platformsScan MCP servers and skills before install, vet endpoints before calling them, and run vulnerability scans, threat intel and compliance checks.
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Scan MCP servers and skills before install, vet endpoints before calling them, and run vulnerability scans, threat intel and compliance checks.
open-source framework for creating and managing simulations populated with AI-powered agents.
Agentarius is an independent AI tool guide website that helps users filter AI tools based on their daily work content, cost budget, and tool limitations. The website categorizes tools by role and task, provides item-by-item comparisons and final selection recommendations, labels all facts with a last-verified date, and has no sponsorships and no paid listings.
Signed, recomputable safety scores for MCP servers, packages and tools, with offline-verifiable attestations and a GitHub Action to gate CI merges.
StremAI shared memory for coding agents across sessions, machines and tools, with per-agent attribution, provenance, verification status and export.
Live catalog of x402-payable HTTP tools from AgentBodega: search, public data, social media, status checks, media conversion and agent-readiness checks.
Run multiple coding agents (Claude Code, Codex, OpenCode) in parallel, each in its own sandboxed VM across local Docker, self-hosted, or cloud (Hetzner, Daytona, Vercel, E2B). Sub-1s checkpoints, per-box browser/VS Code/shells. MIT.
Protocol-translation and governance mesh for multi-agent systems that routes calls across MCP, A2A, ACP, OpenAI function calling, Gemini function calling, and related interfaces with identity, budgets, and audit trails.
Open-source CAD CLI and MCP server that lets coding agents generate, render, validate, and export real 3D design output.
Decentralized civil registry for AI agents on Sui: soulbound identities, on-chain memories, reputation and refusal records.
agentclaw is an AI automation agency in Bengaluru, India. We build AI agents and workflow automation for the growth and go-to-market side of B2B SaaS companies and other agencies, and we keep operating them after launch rather than handing over a diagram. Five services: custom AI agents and workflo
Search developer infrastructure deals, free tiers and startup programs, compare vendors, plan stacks and track pricing changes.
AgentDock is a TypeScript-based AI agent development framework for building AI agents capable of delivering complex tasks with configurable determinism. It consists of AgentDock Core (an open-source, backend-first, framework-agnostic, vendor-independent agent core framework) and an open-source Next.js-based client reference implementation. The framework emphasizes simplicity, extensibility, and configurable determinism, making it suitable for building reliable and predictable AI systems that can operate with minimal supervision. It requires Node.js ≥ 20.11.0, pnpm ≥ 9.15.0, and an API key from at least one LLM provider. The framework repository has been retired; the prompt and documentation generator has been migrated to AgentDock/prompt-library, and the book has been migrated to AgentDock/ai-agents-book.
Read, create, update, comment on and share AgentDocs Markdown docs, with full-text and semantic search.
Distributed platform for running agent environments at scale. Standardized, reproducible sandboxed environments for agent execution, evaluation, and RL training workloads. MIT.
Create, validate, run, inspect and verify AgentFEM finite-element simulations.
AgentFlow is a trainable, tool-integrated agent framework developed by lupantech, designed to overcome the scalability and generalization limitations of tool-augmented reasoning methods. It adopts a modular design comprising four specialized modules: Planner, Executor, Verifier, and Generator, which work collaboratively across multiple rounds of interaction through evolving memory and integrated tools. The framework uses Flow-based Group Refined Policy Optimization (Flow-GRPO) to optimize the Planner online, performing excellently on 10 benchmarks spanning search, agentic reasoning, mathematics, and science, with a 7B model even surpassing GPT-4o with around 200B parameters. The framework supports multi-tool integration (such as Python coding, Google search, Wikipedia search, etc.) and provides inference and training pipelines. The project has been accepted by ICLR 2026 and the NeurIPS 2025 workshop, and ranked second in HuggingFace Daily Paper.
NextJS boilerplate for building and deploying AI agent-based applications.
Self-hostable API gateway and marketplace for AI agents with one API key, REST and streaming access, and health monitoring.
AgentForge is a low-code framework for rapidly developing, testing, and iterating AI-driven autonomous agents and cognitive architectures. Its core concepts include flexible Agents, declarative Cogs, and optional Memory, supporting everything from simple first runs to complex multi-agent orchestration. It is compatible with a variety of LLM models, including OpenAI, Google Gemini, Anthropic Claude, as well as local models running via Ollama or LMStudio, and allows different models to be run for different agents.
Query AgentForge Trust Scores for MCP servers before connecting, covering security, code health, behavioral audit, community trust and EU compliance.
Fundraising for AI agents on Solana: register agents, create campaigns, donate via x402 and track on-chain reputation.
Shared, versioned memory and governance for AI coding agents, resolving architectural decision conflicts across agents.
Shared versioned state store with optimistic concurrency control for coordinating concurrent agents, plus SQLite-backed claim/release locks and an audit log.
Let two agents on machines with no public address talk directly: pair with a short code over an end-to-end encrypted relay (hosted or self-hosted), send files, and invite saved contacts by name.
Platform to create, train, and monetize AI agents and chatbots without coding.
Search, integrate and monetize MCP connectors on the AgentHotspot marketplace.
No-code platform for building AI-powered business automations with a visual builder.
Agentic Context Engine (ACE) is an open-source agent learning engine by Kayba that adds a persistent learning loop to AI agents, enabling them to accumulate strategies from experience and avoid repeating mistakes. It requires no fine-tuning, training data, or vector database, and offers a hosted service.
Headless DHI MIKE+ urban-water modelling: model inspection, parameter editing, simulation runs with QA status, .res1d results reading and plotting.
Read-only access to the agentic-os governance, SDLC and QE methodology, with install planning and verification.
Agentic-RAG-R1 (repository name Harness-RL) is a reinforcement learning-based agentic RAG framework, and the official implementation of the paper accepted at PCC 2026. It proposes training language model agents within a central-agent multi-agent execution framework (harness), without flattening the execution process into a single token sequence, but instead constructing black-box trajectories from interface calls and session prefix trees, and employing Conflict-Aware Policy Optimization (CAPO) to route the gradients of action tokens and argument tokens separately to their corresponding parameter subspaces. The framework supports central-only agent training and joint multi-agent training, integrates the production-grade agent framework StackPlanner and the slime distributed training stack, and targets Linux x86_64 + NVIDIA GPU environments.
Long-term memory over a folder of Markdown files: local hybrid retrieval (BM25F, dense vectors, phrase proximity) that reports when an answer is absent.
EPA SWMM stormwater modelling workflow: model building, simulation runs, calibration, QGIS integration, climate scenarios and uncertainty analysis.
Turns your task manager into agent memory with hybrid retrieval over TickTick or an Obsidian vault, without a separate vector database.
LLM vulnerability scanner and AI red teaming kit.