NagaAgent
NagaAgent is a Python-based agentic AI framework enabling multi-agent collaboration, tool integration, and knowledge graph memory management. It supports streaming tool calls, MCP protocol, and multiple LLM providers via OpenAI-compatible APIs.
Key facts
Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.
| Field | Value |
|---|---|
| Repository | RTGS2017/NagaAgent |
| Owner | RTGS2017 |
| Primary language | Python |
| License | AGPL-3.0 — OSI-approved |
| Stars | 1.5k |
| Forks | 162 |
| Open issues | 4 |
| Latest release | v5.1.3 (2026-07-08) |
| Last updated | 2026-07-08 |
| Source | https://github.com/RTGS2017/NagaAgent |
What NagaAgent is
NagaAgent implements a streaming tool-call architecture parsing tool invocations from LLM text outputs (```tool``` code blocks or raw JSON), routes them to MCP/OpenClaw agents, executes up to 5 reasoning loops, and persists memory in Neo4j knowledge graphs. Core stack: Python 3.11, Electron frontend, FastAPI backend, SSE streaming, multi-provider LLM support (OpenAI, DeepSeek, Anthropic formats).
Get the NagaAgent source
Clone the repository and explore it locally.
git clone https://github.com/RTGS2017/NagaAgent.gitcd NagaAgent# follow the project's README for install & configurationNeed it deployed, integrated, or customized instead? DEV.co ships production installs.
Best use cases
Implementation considerations
- Dual-license model (AGPL-3.0 open + proprietary closed-source) requires explicit legal review for commercial use; AGPL mandates source disclosure of derivative works.
- Python 3.11 strict version pinning (>=3.11, <3.12) limits compatibility; runtime environment must match exactly. Plan dependency management via uv or venv.
- Neo4j backend is optional but memory graph features require it; self-hosted Neo4j or cloud licensing adds infrastructure cost and operational burden.
- Streaming tool-call architecture relies on LLM text parsing (json5, code block extraction); model prompt engineering and error handling are critical for reliability.
- Multi-port service layout (backend, frontend dev server, Neo4j, MCP, OpenClaw) requires coordinated startup, port management, and network isolation in production.
When to avoid it — and what to weigh
- Proprietary / Closed-Source Deployment Required — Project is dual-licensed AGPL-3.0 (open) and proprietary. AGPL requires source disclosure; commercial use of open version mandates written authorization and is unclear. Requires legal review before enterprise adoption.
- Simple Chatbot Use Case — NagaAgent is over-architected for basic Q&A bots. The tool-call loops, knowledge graph memory, and agent orchestration add operational complexity that simple conversational apps do not need.
- Minimal Python/Dependency Footprint — Requires Python 3.11, Neo4j runtime, Node.js frontend build, Electron packaging, multiple service ports, and deep dependency tree. Not suitable for lightweight, isolated deployments.
- Low-Latency, Real-Time Systems — Streaming SSE, Neo4j queries, and multi-loop reasoning introduce cumulative latency. Not optimized for sub-second response requirements or embedded/edge inference.
License & commercial use
Dual-licensed: AGPL-3.0 (open source—requires source disclosure and derivative work attribution) and proprietary (commercial use requires written authorization from [email protected]). No OSI-compliant permissive license for commercial use without explicit agreement.
AGPL-3.0 open version: commercial use is NOT clearly permitted. AGPL requires source code disclosure of any network-deployed modifications, which is incompatible with proprietary SaaS models. Closed-source proprietary license exists but requires written contract negotiation. DO NOT assume commercial use is allowed under AGPL; engage legal counsel and contact bilibili【柏斯阔落】 or [email protected] for licensing terms before production deployment.
DEV.co evaluation signals
Editorial assessment — not user reviews. Directional, with an explicit confidence level.
| Signal | Assessment |
|---|---|
| Maintenance | Active |
| Documentation | Adequate |
| License clarity | Needs review |
| Deployment complexity | High |
| DEV.co fit | Good |
| Assessment confidence | Medium |
API key storage: config.json written to disk; plaintext keys at risk if file permissions not restricted. AGPL source disclosure requirement means production modifications are legally exposed. ASR/TTS proxy through NagaBusiness introduces third-party data flow. Neo4j and MCP servers may require network security hardening (CORS, authentication). No cryptographic signing, rate limiting, or input sanitization details provided. No formal security audit mentioned. Treat as beta-maturity for sensitive data; conduct threat modeling and penetration testing before handling confidential information.
Alternatives to consider
LangChain + LangGraph
Mature, permissive MIT license, multi-language support (Python, JS, Java), battle-tested in production. No memory graph by default but integrates Neo4j via modules. Larger ecosystem, stronger commercial backing.
AutoGen (Microsoft)
Apache 2.0 license, multi-agent orchestration, streaming support, strong documentation. Less memory-centric but comparable tool-call loops; better for teams with Microsoft ecosystem alignment.
Fully hosted, no deployment overhead, streaming tool calls, file/memory management built-in. Vendor lock-in and per-call costs; simpler for prototypes but less control than self-hosted framework.
Build on NagaAgent with DEV.co software developers
NagaAgent is best for teams building multi-tool AI workflows with persistent memory. Ensure license compliance (AGPL vs. proprietary) and infrastructure readiness (Python 3.11, Neo4j, Electron) before adopting. Contact the maintainers for commercial licensing questions.
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NagaAgent FAQ
Can I use NagaAgent commercially?
Does NagaAgent support my LLM provider?
Is Neo4j required?
What is the deployment model—cloud, on-premise, or desktop only?
Software development & web development with DEV.co
DEV.co helps companies turn open-source tools like NagaAgent into production software. Our software development services cover the full lifecycle — architecture, web development, integration, and maintenance — delivered by software developers and web developers who ship. Engage our software development agency to implement or customize it for your mcp servers stack.
Evaluate NagaAgent for Your Agent Orchestration Needs
NagaAgent is best for teams building multi-tool AI workflows with persistent memory. Ensure license compliance (AGPL vs. proprietary) and infrastructure readiness (Python 3.11, Neo4j, Electron) before adopting. Contact the maintainers for commercial licensing questions.