30 open-source projects similar to volcengine/openviking, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best OpenViking alternative.
WeKnora is a multi-tenant retrieval-augmented generation (RAG) knowledge platform and autonomous AI agent framework. It transforms raw documents into queryable knowledge bases and integrates large language models with vector databases to provide grounded AI responses. The system also functions as a Model Context Protocol (MCP) tool server, exposing knowledge search and agentic capabilities to external AI clients. The platform distinguishes itself through an autonomous agent framework that utilizes iterative reasoning, tool calling, and web search to solve multi-step tasks. It implements a sta
Koog is an LLM agent framework used to build autonomous entities that execute tool-based workflows. It utilizes a graph-based workflow engine to define agent behaviors and decision paths as a directed graph of nodes and edges. The framework distinguishes itself through a model provider orchestrator that enables dynamic switching, load balancing, and automatic fallbacks between different AI backends. It implements the Model Context Protocol to connect agents to remote tool servers and features a RAG memory system using vector embeddings to maintain long-term conversation context. The project
Weaviate is a cloud-native vector database and distributed vector store designed to save high-dimensional vectors alongside structured data. It functions as a hybrid search engine that combines vector similarity, keyword matching, and structured metadata filtering within a single query. The system is optimized for retrieval-augmented generation, integrating vector search with generative AI and reranking to power question-and-answer workflows. It distinguishes itself through the ability to merge semantic search with traditional keyword queries and structured metadata filters to improve result
PraisonAI is an autonomous AI agent platform that coordinates multiple LLM-powered agents for research, planning, and execution of complex workflows. It functions as a multi-agent orchestration framework, a workflow builder, and a Model Context Protocol server, while also providing retrieval-augmented generation through vector knowledge bases. Agents can interact via CLI, web, or standardized protocols with sandboxed code execution. The platform distinguishes itself with a rich set of agent communication protocols, including A2A, REST, WebSocket, voice and telephony integration, and MCP, allo
Redis is a high-performance in-memory key-value store that functions as a distributed cache, message broker, and NoSQL database. It provides sub-millisecond read and write access to data stored in RAM and can operate as a vector database for indexing high-dimensional embeddings. The system supports a wide range of data storage and synchronization primitives, including the management of strings, hashes, lists, sets, and JSON documents. It enables real-time data operations through atomic transactions, hybrid persistence using snapshots and append-only logs, and high-availability configurations
Letta is a framework for building, deploying, and managing autonomous AI agents that maintain persistent state across long-term interactions. It provides a comprehensive suite of primitives for defining agents with configurable personas, modular memory blocks, and tool-use capabilities, enabling them to retain user preferences and conversation history over extended sessions. The platform distinguishes itself through its advanced memory management and orchestration capabilities. It allows agents to autonomously update their own memory, perform retrieval-augmented generation, and coordinate com
This project provides a translation layer and set of adapters designed to bridge AI agents with the Model Context Protocol. It functions as an integration layer that allows agents to operate as protocol-compliant servers and enables the conversion of protocol-based tools into formats compatible with agent frameworks and logic graphs. The adapters facilitate tool interoperability by wrapping external protocol tools for use within agent workflows and exposing internal agent capabilities to any client implementing the Model Context Protocol. This creates a communication bridge that supports inte
Deepagents is an LLM agent orchestration platform and stateful application server designed for deploying and managing AI agents built with computational graphs. It provides a containerized runtime environment that handles agent execution, state persistence, and the versioning of AI assistants. The platform distinguishes itself through deep integration with the Model Context Protocol, allowing agents to function as servers that expose tools and capabilities to external clients. It features a sophisticated observability suite for capturing execution traces, performing LLM-based evaluations agai
Julep is an LLM agent orchestration platform and multi-tenant AI backend designed for building autonomous agents with persistent memory, tool integration, and complex multi-step workflows. It serves as a framework for configuring agent identities and behavioral settings to automate specialized professional roles. The platform distinguishes itself through its stateful session management and RAG infrastructure engine, which allow agents to maintain long-term interaction history and ground responses in indexed private documents. It provides enterprise-grade infrastructure features, including a s
This project is a Model Context Protocol server and AI agent database connector. It provides a standardized communication layer that allows language models to interact with relational data stores, read database schemas, and manage PostgreSQL database resources. The implementation acts as a serverless host for the Model Context Protocol, deploying on distributed edge functions to connect AI assistants to a project. This enables AI agents to perform database administration, execute SQL queries, and handle schema migrations through an AI-compatible interface. The system covers broader capabilit
Ever Gauzy is an integrated business management suite providing an ERP and CRM framework for professional services automation. It functions as a multi-tenant SaaS platform that combines time tracking, billing, and human resource management into a unified system. The project is distinguished by its headless architecture, utilizing a REST and GraphQL API gateway to expose business operations. It features a Model Context Protocol server that allows AI assistants to interact with system data and execute functional tools for automated business workflows. The platform covers a broad operational su
Cube is a semantic layer data platform that maps raw SQL databases to standardized business metrics and dimensions. It functions as a SQL dialect translator, converting abstract semantic queries into optimized SQL statements for various cloud data warehouses. The platform operates as a multi-tenant data gateway, isolating information and security permissions for different customers within a single deployment. It includes a relational caching engine that stores pre-aggregated query results to reduce latency and decrease the load on primary data warehouses. The system provides a REST-based int
ECC is an LLM agent orchestration framework and cross-platform AI tooling suite designed to coordinate multi-model workflows. It provides a system for managing specialized agent roles, reusable skills, and structured planning to execute complex software development tasks across different AI-powered code editors. The project distinguishes itself as a Model Context Protocol manager, providing a configuration layer to integrate external servers and audit tool execution. It further implements an agentic security sandbox that restricts sensitive file access and scans for secret leakage to secure a
Archestra is a platform for enterprise AI agent deployment and Model Context Protocol orchestration. It provides a centralized system for configuring specialized agents with specific system prompts and toolsets, and managing the deployment of Model Context Protocol servers that provide large language models with external tools and data sources. The system features an AI agent gateway that exposes configured agents as networked services for external clients and integrated development environments. It incorporates a security suite that provides deterministic guardrails to prevent prompt injecti
Kill Bill is a subscription billing platform and usage-based billing engine designed to manage recurring invoicing and automated payment collection. It functions as a multi-tenant billing infrastructure, providing isolated environments for different organizational entities through a dedicated API. The system is distinguished by a plugin-based extension framework that allows for the integration of third-party payment gateways and custom business logic. It includes a payment gateway orchestrator to handle transactions and refunds, as well as a revenue recognition system to allocate contract rev
ABP is an opinionated architectural framework for building enterprise software solutions using .NET and ASP.NET Core. It serves as a structural toolkit for implementing domain-driven design and microservices patterns, providing a modular enterprise architecture where functionality is organized into independent, pluggable modules. The platform is specifically designed to support multi-tenant SaaS architectures, isolating data and configurations for multiple independent customers within a single application instance. It provides enterprise boilerplate infrastructure and pre-configured templates
Mempalace is a long-term memory management system for large language models that orchestrates the storage and retrieval of conversation history and entity relationships. It functions as a memory orchestrator and Model Context Protocol server, providing AI clients with read and write access to structured knowledge. The system utilizes a temporal knowledge graph to track evolving entity relationships and timelines with validity windows. It employs a hierarchical memory partitioning strategy, organizing data into wings and rooms to isolate specialist agent contexts and restrict semantic searches
Model Context Protocol is a standardized framework for connecting large language models to external data sources and executable tools. It enables the creation of a universal interface where servers expose tools, resources, and prompts that can be discovered and utilized by various AI clients. The protocol utilizes a JSON-RPC message system that is transport-agnostic, supporting both standard input/output for local processes and HTTP with server-sent events for remote connections. It emphasizes security and control by delegating model sampling to the client to keep API keys secure from servers
Odysseus is a self-hosted AI workspace and autonomous agent framework designed for deploying and managing large language models. It serves as a centralized platform for orchestrating agentic tasks, utilizing a model context protocol server to connect AI models to external system utilities, browser automation, and local hardware. The system distinguishes itself through a combination of retrieval-augmented generation and a RAG knowledge base, using vector stores and local embeddings to provide persistent semantic memory. It further integrates AI-driven communication management to triage email i
vibe-vibe is an LLM agent engineering framework and toolchain optimizer designed for orchestrating multi-agent systems. It serves as a comprehensive guide and methodology for transforming conceptual ideas into deployed applications through agentic software engineering. The project focuses on the orchestration of specialized AI agent roles with defined collaboration boundaries and iterative feedback loops. It provides frameworks for toolchain optimization, including the selection and evaluation of protocols that extend model capabilities and the design of standardized tool interfaces. The sys
Cognee is an agentic memory management platform designed to provide autonomous agents with long-term semantic recall and structured knowledge. It functions as a framework for building persistent memory systems that connect large language models to graph-based knowledge and vector storage, enabling agents to maintain context across complex tasks and multiple sessions. The platform distinguishes itself through a hybrid approach that combines semantic similarity search with structural graph traversal, allowing for context-aware information retrieval. It features a modular architecture that orche
ZenML is an extensible machine learning orchestration framework designed to manage the end-to-end lifecycle of data pipelines and AI agent workflows. It functions as a durable orchestrator that executes machine learning tasks as directed acyclic graphs, ensuring that every step is containerized for consistent performance across local, cloud, and hybrid infrastructure. By decoupling pipeline code from underlying compute and storage backends, the platform allows developers to define infrastructure-agnostic stacks that remain portable across diverse environments. The project distinguishes itself
OpenFGA is a fine-grained authorization server and policy decision point that implements relationship-based access control. It serves as a centralized authorization service for evaluating access requests and managing relationship tuples across distributed microservices and multi-tenant environments. The engine combines relationship graphs with attribute-based access control, using the Common Expression Language to evaluate dynamic runtime attributes and conditional access rules. It handles complex hierarchies and nested permissions by traversing chains of associations and parent-child links t
LangChain4j is a framework and library for building applications powered by large language models on the JVM. It provides a unified API for developing AI agents, implementing retrieval augmented generation, and integrating generative AI capabilities into professional software built with frameworks like Spring Boot or Quarkus. The project enables the creation of autonomous agents that can reason through tasks, manage memory, and execute external tools to achieve specific goals. It differentiates itself through a unified model interface that allows developers to switch between multiple model pr
OpenSearch is a distributed search and analytics engine designed for indexing, searching, and analyzing massive volumes of structured and unstructured data in real time. It functions as a comprehensive platform that integrates enterprise-grade search capabilities, a vector database for high-dimensional similarity lookups, and a unified observability suite for monitoring logs, metrics, and traces across complex distributed environments. The platform distinguishes itself through its support for agentic workflow automation, allowing users to orchestrate multi-agent tasks and integrate foundation
Rallly is a group scheduling tool and collaborative event planner designed to coordinate meeting dates and collect participant availability. It functions as a multi-tenant meeting coordinator that allows users to propose date options via polls, visualize overlapping free time in a grid, and finalize meeting arrangements across different time zones. The project is built as a self-hosted scheduling application that can be deployed on private infrastructure using a containerized stack. This deployment model enables full data ownership and includes capabilities for corporate identity branding, al
Velociraptor is a digital forensics and incident response platform, endpoint detection and response system, and visibility tool. It provides a query engine and remote forensic collector used to hunt for indicators of compromise and perform triage across a fleet of hosts. The system is distinguished by its specialized query language for interrogating host state and parsing binary files. It features a notebook environment that combines markdown documentation with executable query cells to standardize investigative workflows and enable collaborative reporting. The platform covers a wide range o
This platform is an automated documentation and codebase analysis system designed to generate structured wikis, technical guides, and interactive diagrams from source code repositories. It functions as a retrieval-augmented generation framework that connects codebases to language models, enabling context-aware answers, deep research, and automated documentation updates through semantic vector search. The system distinguishes itself through a self-hosted, containerized architecture that supports both cloud-based and local AI model execution. It provides sophisticated model orchestration, allow
This project is a retrieval-augmented generation pipeline designed for building custom ChatGPT plugins that allow language models to query private or professional documents. It implements a full retrieval workflow, from processing and indexing document chunks to retrieving relevant context for natural language queries. The system distinguishes itself through a hybrid retrieval approach that combines dense vector embeddings with sparse keyword matching, further refined by a two-stage semantic re-ranking process. It includes specialized data privacy tools for screening personally identifiable i
Memori is an AI agent memory middleware platform designed to provide persistent, context-aware recall for language models. It functions as a non-intrusive layer that intercepts outbound model requests to automatically capture interaction history and execution traces, ensuring that agents maintain continuity across sessions without requiring modifications to existing application logic. The platform distinguishes itself through a dual-model storage architecture that maintains information as both structured relational primitives for precise fact retrieval and rolling narrative summaries for situ