Production-ready AI agent orchestration platform with 66 specialized agents, 213 MCP tools, ReasoningBank learning memory, and autonomous multi-agent swarms. Built by @ruvnet with Claude Agent SDK, neural networks, memory persistence, GitHub integration,
V3 Embedding Service - OpenAI, Transformers.js, Agentic-Flow (ONNX), Mock providers with hyperbolic embeddings, normalization, and chunking
Integration module - agentic-flow@alpha deep integration, ADR-001 compliance, TokenOptimizer
Integration module - agentic-flow@alpha deep integration, ADR-001 compliance, TokenOptimizer
WebAssembly bindings for Midstream temporal comparison, scheduling, and meta-learning + real QUIC transport via agentic-flow
Integration module - agentic-flow@alpha deep integration, ADR-001 compliance, TokenOptimizer
V3 Embedding Service - OpenAI, Transformers.js, Agentic-Flow (ONNX), Mock providers with hyperbolic embeddings, normalization, and chunking
PicoFlow - Agentic Flow Framework
V3 Embedding Service - OpenAI, Transformers.js, Agentic-Flow (ONNX), Mock providers with hyperbolic embeddings, normalization, and chunking
Standalone MCP server with agentic-flow and agentdb integration
Design and visualize agentic orchestration flows with trailer A/B-roll planning support.
Enterprise-grade AI agent orchestration with WASM-powered ReasoningBank memory and AgentDB vector database (always uses latest agentic-flow)
GAFF - Graphical Agentic Flow Framework: Complete MCP server suite for AI agent orchestration (meta-package)
Production-grade E2B sandbox orchestration with agentic-flow swarms and AgentDB caching for distributed AI agent execution
Production-ready AI agent orchestration platform with 66 specialized agents, 213 MCP tools, ReasoningBank learning memory, quantum-resistant Jujutsu VCS, and autonomous multi-agent swarms. Built by @ruvnet with Claude Agent SDK, neural networks, memory pe
Production-ready AI agent orchestration platform with 66 specialized agents, 213 MCP tools, ReasoningBank learning memory, and autonomous multi-agent swarms. Built by @ruvnet with Claude Agent SDK, neural networks, memory persistence, GitHub integration,
A high-fidelity agentic terminal assistant for the Flux Era.
Multi-agent orchestration for Claude Code with automatic task management
🚀 AI-Powered Swarm Intelligence Platform - Gamified MCP Development with 70+ Tools
Ruflo CLI - Enterprise AI agent orchestration with 60+ specialized agents, swarm coordination, MCP server, self-learning hooks, and vector memory for Claude Code
Ruflo - Enterprise AI agent orchestration platform. Deploy 60+ specialized agents in coordinated swarms with self-learning, fault-tolerant consensus, vector memory, and MCP integration
Allow parsing of the flow syntax
Strip flow type annotations from your output code.
A JavaScript parser built from the Hermes engine
AI-powered Jujutsu VCS wrapper for multi-agent collaboration - 10-100x faster than Git with MCP protocol support
Smart Tree - An intelligent, AI-friendly directory visualization tool
ruLake — vector-native federation intermediary over heterogeneous backends (ADR-155)
Vortex physics-inspired & ground-up redesign of FANN (credit to Steffen Nissen). Its original implementation is described in Nissen's 2003 report Implementation of a Fast Artificial Neural Network Library (FANN).
flow org agent patron
Extends the brute gem with a declarative BPMN workflow engine for multi-agent orchestration — parallel branches, conditional routing, loops with timeouts, and pluggable service tasks.
Pocket Flow: A minimalist LLM framework. Let Agents build Agents!
Detects and manages psychological flow states based on challenge-skill balance
Meta-extension that models the agent cognitive architecture as a graph of subsystems, connections, and information flows — enabling self-awareness of its own architecture
Rubagent is a lightweight Ruby framework for building modular, composable AI agents that can interact with LLMs (like OpenAI), tools, and external APIs. It provides a flexible architecture for defining agents, managing prompts, and orchestrating multi-step workflows using functional patterns. Features: - Streamed LLM responses (OpenAI, etc.) - Plug-and-play agent design - Shared context and memory flow - Support for custom tools and HTTP integrations - Built-in dry-rb and Zeitwerk compatibility
An MCP (Model Context Protocol) server that provides LLM agents with access to runtime context of executing Ruby processes. Connect to debug sessions, evaluate code, inspect objects, and control execution flow via MCP tools.
Time-bound cognitive resource model for brain-modeled agentic AI — sand grains flow through a narrowed neck, depleting attention resources until the hourglass is flipped to renew the cycle
Exposes RobotLab robots and networks as A2A agents over HTTP+SSE. Implements the Agent2Agent Protocol v1.0 (Linux Foundation) via the simple_a2a gem. Supports sync and interactive execution modes, bridging RobotLab's AskUser tool to A2A's input_required/resume lifecycle for multi-turn flows without a terminal dependency.
pikuri-vectordb gives a pikuri-core agent a +vectordb_search+ tool over a local document corpus — agentic search, the agent decides when to retrieve. Ships a swappable backend (a pure-Ruby +Backend::InMemory+ for teaching and a thin +Backend::Chroma+ HTTP client for persistence), a chunker, an embedder wrapper over +RubyLLM.embed+, and an optional +Reranker::LlamaServer+ that speaks +/v1/rerank+ against a cross-encoder model. Text extraction goes through +Pikuri::FileType.read_as_text+ in pikuri-core, which handles plain text / Markdown / PDF; HTML extraction is a deferred follow-up. Hosts wire the feature via +c.add_extension Pikuri::VectorDb::Extension.new(...)+ inside the +Agent.new+ block — same opt-in shape as +pikuri-tasks+ / +pikuri-skills+. The bundled +Pikuri::VectorDb::LIBRARIAN+ persona is the privilege-separated sub-agent counterpart for hosts that want recall to flow through a child rather than the parent's context. Three model endpoints in the full setup — chat (via ruby_llm), an embedder (via +RubyLLM.embed+), and an optional reranker (HTTP +/v1/rerank+). A single +llama-server+ in router mode serves all three by default, loading each cached GGUF on demand; see the gem's README for details.
The affixapi.com API documentation. # Introduction Affix API is an OAuth 2.1 application that allows developers to access customer data, without developers needing to manage or maintain integrations; or collect login credentials or API keys from users for these third party systems. # OAuth 2.1 Affix API follows the [OAuth 2.1 spec](https://datatracker.ietf.org/doc/html/draft-ietf-oauth-v2-1-08). As an OAuth application, Affix API handles not only both the collection of sensitive user credentials or API keys, but also builds and maintains the integrations with the providers, so you don't have to. # How to obtain an access token in order to get started, you must: - register a `client_id` - direct your user to the sign in flow (`https://connect.affixapi.com` [with the appropriate query parameters](https://github.com/affixapi/starter-kit/tree/master/connect)) - capture `authorization_code` we will send to your redirect URI after the sign in flow is complete and exchange that `authorization_code` for a Bearer token # Sandbox keys (developer mode) ### dev ``` eyJhbGciOiJFUzI1NiIsImtpZCI6Ims5RmxwSFR1YklmZWNsUU5QRVZzeFcxazFZZ0Zfbk1BWllOSGVuOFQxdGciLCJ0eXAiOiJKV1MifQ.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.VLWYjCQvBS0C3ZA6_J3-U-idZj5EYI2IlDdTjAWBxSIHGufp6cqaVodKsF2BeIqcIeB3P0lW-KL9mY3xGd7ckQ ``` #### `employees` endpoint sample: ``` curl --fail \ -X GET \ -H 'Authorization: Bearer eyJhbGciOiJFUzI1NiIsImtpZCI6Ims5RmxwSFR1YklmZWNsUU5QRVZzeFcxazFZZ0Zfbk1BWllOSGVuOFQxdGciLCJ0eXAiOiJKV1MifQ.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.VLWYjCQvBS0C3ZA6_J3-U-idZj5EYI2IlDdTjAWBxSIHGufp6cqaVodKsF2BeIqcIeB3P0lW-KL9mY3xGd7ckQ' \ 'https://dev.api.affixapi.com/2023-03-01/developer/employees' ``` ### prod ``` eyJhbGciOiJFUzI1NiIsImtpZCI6Ims5RmxwSFR1YklmZWNsUU5QRVZzeFcxazFZZ0Zfbk1BWllOSGVuOFQxdGciLCJ0eXAiOiJKV1MifQ.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.2zdpFAmiyYiYk6MOcbXNUwwR4M1Fextnaac340x54AidiWXCyw-u9KeavbqfYF6q8a9kcDLrxhJ8Wc_3tIzuVw ``` #### `employees` endpoint sample: ``` curl --fail \ -X GET \ -H 'Authorization: Bearer eyJhbGciOiJFUzI1NiIsImtpZCI6Ims5RmxwSFR1YklmZWNsUU5QRVZzeFcxazFZZ0Zfbk1BWllOSGVuOFQxdGciLCJ0eXAiOiJKV1MifQ.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.2zdpFAmiyYiYk6MOcbXNUwwR4M1Fextnaac340x54AidiWXCyw-u9KeavbqfYF6q8a9kcDLrxhJ8Wc_3tIzuVw' \ 'https://api.affixapi.com/2023-03-01/developer/employees' ``` # Webhooks An exciting feature for HR/Payroll modes are webhooks. If enabled, your `webhook_uri` is set on your `client_id` for the respective environment: `dev | prod` Webhooks are configured to make live requests to the underlying integration 1x/hr, and if a difference is detected since the last request, we will send a request to your `webhook_uri` with this shape: ``` { added: <api.v20230301.Employees>[ <api.v20230301.Employee>{ ..., date_of_birth: '2010-08-06', display_full_name: 'Daija Rogahn', employee_number: '57993', employment_status: 'pending', employment_type: 'other', employments: [ { currency: 'eur', effective_date: '2022-02-25', employment_type: 'other', job_title: 'Dynamic Implementation Manager', pay_frequency: 'semimonthly', pay_period: 'YEAR', pay_rate: 96000, }, ], first_name: 'Daija', ... } ], removed: [], updated: [ <api.v20230301.Employee>{ ..., date_of_birth: '2009-11-09', display_full_name: 'Lourdes Stiedemann', employee_number: '63189', employment_status: 'leave', employment_type: 'full_time', employments: [ { currency: 'gbp', effective_date: '2023-01-16', employment_type: 'full_time', job_title: 'Forward Brand Planner', pay_frequency: 'semimonthly', pay_period: 'YEAR', pay_rate: 86000, }, ], first_name: 'Lourdes', } ] } ``` the following headers will be sent with webhook requests: ``` x-affix-api-signature: ab8474e609db95d5df3adc39ea3add7a7544bd215c5c520a30a650ae93a2fba7 x-affix-api-origin: webhooks-employees-webhook user-agent: affixapi.com ``` Before trusting the payload, you should sign the payload and verify the signature matches the signature sent by the `affixapi.com` service. This secures that the data sent to your `webhook_uri` is from the `affixapi.com` server. The signature is created by combining the signing secret (your `client_secret`) with the body of the request sent using a standard HMAC-SHA256 keyed hash. The signature can be created via: - create an `HMAC` with your `client_secret` - update the `HMAC` with the payload - get the hex digest -> this is the signature Sample `typescript` code that follows this recipe: ``` import { createHmac } from 'crypto'; export const computeSignature = ({ str, signingSecret, }: { signingSecret: string; str: string; }): string => { const hmac = createHmac('sha256', signingSecret); hmac.update(str); const signature = hmac.digest('hex'); return signature; }; ``` ## Rate limits Open endpoints (not gated by an API key) (applied at endpoint level): - 15 requests every 1 minute (by IP address) - 25 requests every 5 minutes (by IP address) Gated endpoints (require an API key) (applied at endpoint level): - 40 requests every 1 minute (by IP address) - 40 requests every 5 minutes (by `client_id`) Things to keep in mind: - Open endpoints (not gated by an API key) will likely be called by your users, not you, so rate limits generally would not apply to you. - As a developer, rate limits are applied at the endpoint granularity. - For example, say the rate limits below are 10 requests per minute by ip. from that same ip, within 1 minute, you get: - 10 requests per minute on `/orders`, - another 10 requests per minute on `/items`, - and another 10 requests per minute on `/identity`, - for a total of 30 requests per minute.