--- title: "arcade-mcp vs MCPJungle" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/arcadeai-arcade-mcp-vs-mcpjungle-mcpjungle" tools: ["arcadeai-arcade-mcp", "mcpjungle-mcpjungle"] --- # arcade-mcp vs MCPJungle *GraphCanon updated Jul 27, 2026* ## Verdict Pick arcade-mcp if arcade-MCP is an MCP Server Framework and Tool Development Library specifically built for incorporating custom capabilities into AI agents using the Model Context Protocol; pick MCPJungle if mCPJungle is a self-hosted Go platform designed for managing and connecting MCP servers within AI agent infrastructure. [arcade-mcp](https://docs.arcade.dev) reports 981 GitHub stars, 101 forks, and 16 open issues, last pushed Jul 26, 2026. [MCPJungle](https://docs.mcpjungle.com) has 1.2k stars, 148 forks, and 92 open issues, last pushed May 20, 2026. Figures are from public GitHub metadata via [arcade-mcp's repository](https://github.com/ArcadeAI/arcade-mcp) and [MCPJungle's repository](https://github.com/mcpjungle/MCPJungle). | | [arcade-mcp](/tools/arcadeai-arcade-mcp.md) | [MCPJungle](/tools/mcpjungle-mcpjungle.md) | | --- | --- | --- | | Tagline | MCP Server Framework and Tool Development Library for Custom Agent Capabilities | A platform to manage and connect MCP servers | | Stars | 981 | 1,174 | | Forks | 101 | 148 | | Open issues | 16 | 92 | | Language | Python | Go | | Adopt for | Arcade-MCP is an MCP Server Framework and Tool Development Library specifically built for incorporating custom capabilities into AI agents using the Model Context Protocol. | MCPJungle is a self-hosted Go platform designed for managing and connecting MCP servers within AI agent infrastructure. | | Persona | - | - | | Runtime | - | - | | License | MIT | MCPJungle is available under the MPL-2.0 license, which permits changes and reuse but mandates that derivative software retain its open status. | | Categories | AI Agents | AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [arcade-mcp](/tools/arcadeai-arcade-mcp.md) | [MCPJungle](/tools/mcpjungle-mcpjungle.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 0d | 67d | | Open issues (now) | 16 | 92 | | Full report | [trust report](/tools/arcadeai-arcade-mcp/trust.md) | [trust report](/tools/mcpjungle-mcpjungle/trust.md) | ## Decision facts: arcade-mcp - **Requirements:** Min 4 GB RAM - **Adopt for:** Arcade-MCP is an MCP Server Framework and Tool Development Library specifically built for incorporating custom capabilities into AI agents using the Model Context Protocol. ## Decision facts: MCPJungle - **Pricing:** freemium - The platform can be used freely due to its open-source license, with no explicit premium or commercial tier information provided. - **Requirements:** Ensure your environment supports the Go language for compatibility.; MCPJungle is designed specifically for managing MCP servers; other server types may not be compatible without additional support. - **Adopt for:** MCPJungle is a self-hosted Go platform designed for managing and connecting MCP servers within AI agent infrastructure. - **License detail:** MCPJungle is available under the MPL-2.0 license, which permits changes and reuse but mandates that derivative software retain its open status. ## Choose when ### Choose arcade-mcp if… - arcade-mcp is primarily Python; MCPJungle is Go. - License: arcade-mcp is MIT, MCPJungle is MPL-2.0. - Requirements: Min 4 GB RAM. - Tags unique to arcade-mcp: ai, arcade-ai, mcp-framework, python. - When you need to build detailed, custom interactions between your AI agent and a structured environment that requires specific context management capabilities through the MCP protocol. ### Choose MCPJungle if… - MCPJungle is primarily Go; arcade-mcp is Python. - License: MCPJungle is MPL-2.0, arcade-mcp is MIT. - Pricing: The platform can be used freely due to its open-source license, with no explicit premium or commercial tier information provided.. - Requirements: Ensure your environment supports the Go language for compatibility.; MCPJungle is designed specifically for managing MCP servers; other server types may not be compatible without additional support.. - Tags unique to MCPJungle: ai-agents, infrastructure, mcp-server, self-hosted. - MCPJungle ships Docker support for self-hosted deployment. - When you require a Go-based solution to manage Model Context Protocol (MCP) servers in your infrastructure, MCPJungle can offer the needed features for self-hosting these servers. ## When NOT to use arcade-mcp - If your project does not involve interaction with an environment that relies on the Model Context Protocol for its core functionality, Arcade-MCP may offer unnecessary complexity. - When working in environments where direct support and integration of tools are crucial, arcade-mcp might have less support compared to more mainstream AI agent frameworks. ## When NOT to use MCPJungle - Do not use MCPJungle if you do not have an existing environment based on the Model Context Protocol; it adds unnecessary complexity. - Avoid MCPJungle if your project requires a language other than Go, as its exclusive development in Go might limit flexibility across different stack requirements. ## Common questions ### What is the difference between arcade-mcp and MCPJungle? arcade-mcp: MCP Server Framework and Tool Development Library for Custom Agent Capabilities. MCPJungle: A platform to manage and connect MCP servers. See the comparison table for live GitHub stats and shared categories. ### When should I choose arcade-mcp over MCPJungle? Choose arcade-mcp over MCPJungle when arcade-mcp is primarily Python; MCPJungle is Go; License: arcade-mcp is MIT, MCPJungle is MPL-2.0; Requirements: Min 4 GB RAM; Tags unique to arcade-mcp: ai, arcade-ai, mcp-framework, python; When you need to build detailed, custom interactions between your AI agent and a structured environment that requires specific context management capabilities through the MCP protocol. ### When should I choose MCPJungle over arcade-mcp? Choose MCPJungle over arcade-mcp when MCPJungle is primarily Go; arcade-mcp is Python; License: MCPJungle is MPL-2.0, arcade-mcp is MIT; Pricing: The platform can be used freely due to its open-source license, with no explicit premium or commercial tier information provided.; Requirements: Ensure your environment supports the Go language for compatibility.; MCPJungle is designed specifically for managing MCP servers; other server types may not be compatible without additional support.; Tags unique to MCPJungle: ai-agents, infrastructure, mcp-server, self-hosted; MCPJungle ships Docker support for self-hosted deployment; When you require a Go-based solution to manage Model Context Protocol (MCP) servers in your infrastructure, MCPJungle can offer the needed features for self-hosting these servers. ### When should I avoid arcade-mcp? If your project does not involve interaction with an environment that relies on the Model Context Protocol for its core functionality, Arcade-MCP may offer unnecessary complexity. When working in environments where direct support and integration of tools are crucial, arcade-mcp might have less support compared to more mainstream AI agent frameworks. ### When should I avoid MCPJungle? Do not use MCPJungle if you do not have an existing environment based on the Model Context Protocol; it adds unnecessary complexity. Avoid MCPJungle if your project requires a language other than Go, as its exclusive development in Go might limit flexibility across different stack requirements. ### Is arcade-mcp or MCPJungle more popular on GitHub? MCPJungle has more GitHub stars (1,174 vs 981). Stars measure visibility, not whether either tool fits your constraints. ### Are arcade-mcp and MCPJungle open source? Yes - both are open-source projects on GitHub (arcade-mcp: MIT, MCPJungle: MPL-2.0). ### Where can I find alternatives to arcade-mcp or MCPJungle? GraphCanon lists graph-backed alternatives at [arcade-mcp alternatives](/tools/arcadeai-arcade-mcp/alternatives) and [MCPJungle alternatives](/tools/mcpjungle-mcpjungle/alternatives) ([arcade-mcp markdown twin](/tools/arcadeai-arcade-mcp/alternatives.md), [MCPJungle markdown twin](/tools/mcpjungle-mcpjungle/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/arcadeai-arcade-mcp-vs-mcpjungle-mcpjungle.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, arcade-mcp or MCPJungle? arcade-mcp: Very active. MCPJungle: Steady. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for arcade-mcp and MCPJungle? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [arcade-mcp trust report](/tools/arcadeai-arcade-mcp/trust); [MCPJungle trust report](/tools/mcpjungle-mcpjungle/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=arcadeai-arcade-mcp`](/api/graphcanon/graph?tool=arcadeai-arcade-mcp) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_