Lets AI assistants query market data and execute/manage trades on MetaTrader 5 using natural language. Implements the MCP bridge with multiple transports (stdio/SSE/HTTP), a WebSocket quote streamer, and local-credentials-first design for prototyping AI-driven trading integrations.
Turns natural-language requirements into a dependency-aware graph of atomic, testable dev tasks for AI coding agents. Adds cross-session memory and a plan-reflect loop that forces the agent to think through each step before writing code.
Brings Gemini models into the terminal as an agent that reads files, runs shell commands, and edits code in place. Includes Google Search grounding, MCP server support, and a free OAuth tier (60 req/min, 1,000 req/day) with a 1M-token context window.
A curated index of community resources for Claude Code — skills, hooks, slash commands, agent orchestrators, and plugins. Entries live in a source-of-truth CSV that generates the README; submissions are bot-checked, then manually vetted by the maintainer.
Provides MCP servers and agent skills that let AI assistants query, correlate and safely manage UniFi controllers (Network, Protect, Access). Includes a Cloud Relay for multi-location access, an independent REST/GraphQL API, secret redaction and preview-then-confirm mutation flows for safer automation.
Official Go implementation of the Model Context Protocol for building MCP servers and clients. Tool handlers are type-safe, with JSON schemas inferred from Go structs via generics. Ships stdio, command, streamable-HTTP, SSE, and in-memory transports.
Builds production-grade AI agents and multi-agent workflows in .NET and Python, with graph-based orchestration for sequential, concurrent, and handoff patterns. Unifies Microsoft's Semantic Kernel and AutoGen lineages, adding durable, checkpointed runs.
Federates MCP, A2A, and REST/gRPC backends behind a single gateway endpoint with centralized discovery, governance, and observability; optimizes agent and tool calling. Includes gRPC→MCP translation, plugin extensibility, OpenTelemetry tracing, and Kubernetes-ready deployment.
Transforms research papers, natural-language specs, and technical descriptions into runnable code via a multi-agent system. Covers Paper2Code, Text2Web, and Text2Backend; scores 75.9% on OpenAI's PaperBench, ahead of top ML PhDs.
Exposes Azure DevOps resources (projects, repos, pipelines, work items, wikis) to AI agents via an MCP server; remote-first (hosted HTTP endpoint) with an optional local stdio Node.js server for VS Code and domain-filtered toolsets.
Builds production AI agents around a model-driven loop with provider abstraction, tools, guardrails, streaming, MCP, tracing, and multi-agent patterns across Python and TypeScript SDKs.
Turns Chromium into a local-first AI browser with an embedded assistant that can summarise pages, extract structured data, automate web tasks, and run scheduled agents. Built as an open-source Chromium fork with 53+ built-in browser tools, 40+ app integrations, and support for BYO AI keys or fully local models (Ollama / LM Studio).