DeepSeek Harness vs FastAgency
Side-by-side comparison of two AI agent tools
Short answer
- FastAgency has had no commit in 9 months; DeepSeek Harness is actively maintained (19,802 commits in the last 90 days).
- DeepSeek Harness is growing faster: +16,130 GitHub stars in the last 30 days vs +3 for FastAgency.
- Pick DeepSeek Harness for: deepSeek Harness: Everything is a Plugin. Pick FastAgency for: the fastest way to bring multi-agent workflows to production.
From GitHub data refreshed daily.
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DeepSeek Harnessopen-source
DeepSeek Harness: Everything is a Plugin.
FastAgencyopen-source
The fastest way to bring multi-agent workflows to production.
Metrics
| DeepSeek Harness | FastAgency | |
|---|---|---|
| Stars | 242.6k | 548 |
| Star velocity /mo | 16.1k | 2.526315789473684 |
| Commits (90d) | 19.8k | 0 |
| Releases (6m) | 10 | 0 |
| Overall score | 0.9562973226855356 | 0.16848510206411044 |
Pros
- +Unified interface for deploying AG2 workflows to production with minimal code changes
- +Supports both web chat applications and REST API services from the same codebase
- +Built-in scaling capabilities with distributed architecture and message broker coordination
Cons
- -Dependent on AG2 framework, limiting flexibility to other agent frameworks
- -Relatively small community with 532 GitHub stars compared to major frameworks
- -Limited documentation available in the provided materials for advanced features
Use Cases
- •Deploying AG2 multi-agent chatbots as web applications for customer service or support
- •Creating REST API services that expose agent workflows for integration with existing systems
- •Building scalable distributed agent systems that coordinate across multiple servers or datacenters
FAQ
- Which is more popular, DeepSeek Harness or FastAgency?
- DeepSeek Harness has more GitHub stars (242,644 vs 548).
- Which is more actively developed, DeepSeek Harness or FastAgency?
- DeepSeek Harness had more commits in the last 90 days (19,802 vs 0).
- Should I use DeepSeek Harness or FastAgency?
- Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.