Arcade MCP vs IDA Pro MCP
Side-by-side comparison of two AI agent tools
Short answer
- IDA Pro MCP is growing faster: +120 GitHub stars in the last 30 days vs +33 for Arcade MCP.
- Pick Arcade MCP for: the best way to create, deploy, and share MCP Servers. Pick IDA Pro MCP for: aI-powered reverse engineering assistant that bridges IDA Pro with language models through MCP.
From GitHub data refreshed daily.
Arcade MCPopen-source
The best way to create, deploy, and share MCP Servers
I
IDA Pro MCPopen-source
AI-powered reverse engineering assistant that bridges IDA Pro with language models through MCP.
Metrics
| Arcade MCP | IDA Pro MCP | |
|---|---|---|
| Stars | 1.0k | 12.4k |
| Star velocity /mo | 33.333333333333336 | 120 |
| Commits (90d) | 31 | 55 |
| Releases (6m) | 0 | 0 |
| Overall score | 0.478021345690114 | 0.529630674298244 |
Pros
- +CLI-based project scaffolding with `arcade new` command streamlines server creation and setup
- +Built on standardized MCP protocol ensuring compatibility with AI systems that support the standard
- +Part of larger Arcade.dev ecosystem with prebuilt tools, examples, and comprehensive documentation
Cons
- -Requires understanding of MCP protocol concepts and Python development for effective use
- -Relatively niche ecosystem compared to broader API integration approaches
- -Limited to MCP-compatible AI systems and clients
Use Cases
- •Building custom tool servers to extend AI assistant capabilities with domain-specific APIs
- •Creating reusable MCP servers for common integrations like databases, file systems, or web services
- •Developing specialized AI tool ecosystems for enterprise or research environments
FAQ
- Which is more popular, Arcade MCP or IDA Pro MCP?
- IDA Pro MCP has more GitHub stars (12,435 vs 1,044).
- Which is more actively developed, Arcade MCP or IDA Pro MCP?
- IDA Pro MCP had more commits in the last 90 days (55 vs 31).
- Should I use Arcade MCP or IDA Pro MCP?
- 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.