OpenFang
UnclaimedThe open-source Agent Operating System for building, running, and deploying autonomous agents.
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TL;DR - OpenFang
- Open-source Agent Operating System built in Rust.
- Features autonomous 'Hands' for scheduled tasks, knowledge graphs, and dashboard reporting.
- Emphasizes security, performance, and broad integration with LLMs and communication channels.
Pricing: Free forever
Best for: Individuals & startups
Pros & Cons
Pros
- High security with 16 distinct layers and sandboxed execution.
- Excellent performance with low cold start time and memory usage.
- Comprehensive channel support with 40 adapters.
- Autonomous 'Hands' that proactively work on tasks.
- Open-source and built in Rust for reliability and efficiency.
Cons
- Requires technical knowledge for installation and configuration (curl command line install).
- Relatively new compared to established frameworks (based on benchmark dates).
Key Features
7 Autonomous Capability Packages (Hands)16 Security Systems (WASM sandbox, Merkle audit trail, prompt injection scanner)Sandboxed Execution with dual metering30 Pre-Built Agents (orchestrators, code reviewers, customer support)38 Built-In Tools + Model Context Protocol (MCP)Persistent Memory (SQLite + vector embeddings, LLM-based compaction)40 Channel Adapters (Telegram, Discord, Slack, WhatsApp, Teams, IRC, Matrix)MCP + A2A + OFP Protocols for agent communication
Pricing
Free
OpenFang is completely free to use with no hidden costs.
About OpenFang
By Toolradar Team·
OpenFang is an open-source Agent Operating System built in Rust, designed to provide the core primitives for building, running, and deploying autonomous agents. It features a robust architecture with 7 autonomous "Hands" that operate on schedules, construct knowledge graphs, and report to a centralized dashboard. The system includes 30 pre-built agents, 40 channel adapters for various communication platforms, 38 built-in tools, and support for 26 LLM providers.
This platform is ideal for developers and organizations looking to implement highly secure and efficient autonomous agents. Its kernel-grade Rust architecture emphasizes performance and security, offering 16 distinct security systems, sandboxed execution environments, and persistent memory with vector embeddings. OpenFang aims to provide a comprehensive and battle-tested solution for agent orchestration, offering a native desktop application for easy management and monitoring.
OpenFang differentiates itself through its focus on security, performance, and comprehensive feature set compared to other agent frameworks. It's built for those who need agents that actively work on tasks, rather than passively waiting for input, making it suitable for automation, data collection, lead generation, and various other intelligent tasks.
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OpenFang FAQ
What are "Hands" in OpenFang, and how do they differ from traditional agents?
Hands are pre-built autonomous capability packages designed to work proactively. Unlike traditional agents that require direct interaction, Hands operate on schedules, construct knowledge graphs, and report their findings to a dashboard. They are designed to perform tasks autonomously without constant user input.
How does OpenFang ensure the security of agent execution and data?
OpenFang incorporates 16 distinct security systems, including a WASM dual-metered sandbox for tool code execution, Ed25519 manifest signing, and a Merkle audit trail. It also features taint tracking, SSRF protection, secret zeroization, and a prompt injection scanner to safeguard against various threats.
What is the Model Context Protocol (MCP) and how does it function within OpenFang?
The Model Context Protocol (MCP) is a communication standard within OpenFang that includes both client and server components. It enables agents to connect to external MCP servers and expose OpenFang's built-in tools to other agents, facilitating broader interoperability and tool access.
Which specific communication channels does OpenFang support for its agents?
OpenFang supports 40 different channel adapters, including popular platforms like Telegram, Discord, Slack, WhatsApp, Teams, IRC, and Matrix. These adapters allow agents to operate across various communication platforms with per-channel model overrides, DM/group policies, and rate limiting.
How does OpenFang manage persistent memory for its agents?
OpenFang utilizes SQLite-backed storage with vector embeddings for persistent memory. This setup enables cross-channel canonical sessions, automatic LLM-based compaction, and JSONL session mirroring, allowing agents to retain context across different conversations and channels.
Source: openfang.sh