--- title: "arcade-mcp vs witsy" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/arcadeai-arcade-mcp-vs-kochava-studios-witsy" tools: ["arcadeai-arcade-mcp", "kochava-studios-witsy"] --- # arcade-mcp vs witsy *GraphCanon updated Sep 20, 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 witsy if witsy is a desktop AI assistant and universal MCP client that supports numerous LLM providers. It requires users to have API keys for models they wish to use, but also. [arcade-mcp](https://docs.arcade.dev) reports 1.0k GitHub stars, 113 forks, and 22 open issues, last pushed Sep 19, 2026. [witsy](https://github.com/Kochava-Studios/witsy) has 2.0k stars, 171 forks, and 60 open issues, last pushed Apr 23, 2026. Figures are from public GitHub metadata via [arcade-mcp's repository](https://github.com/ArcadeAI/arcade-mcp) and [witsy's repository](https://github.com/Kochava-Studios/witsy). | | [arcade-mcp](/tools/arcadeai-arcade-mcp.md) | [witsy](/tools/kochava-studios-witsy.md) | | --- | --- | --- | | Tagline | MCP Server Framework and Tool Development Library for Custom Agent Capabilities | Desktop AI Assistant and Universal MCP Client | | Stars | 1,030 | 2,026 | | Forks | 113 | 171 | | Open issues | 22 | 60 | | Language | Python | TypeScript | | 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. | Witsy is a desktop AI assistant and universal MCP client that supports numerous LLM providers. It requires users to have API keys for models they wish to use, but also supports local model running through Ollama. | | Persona | - | - | | Runtime | - | - | | License | MIT | AGPL-3.0 | | Categories | AI Agents | AI Agents, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [arcade-mcp](/tools/arcadeai-arcade-mcp.md) | [witsy](/tools/kochava-studios-witsy.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 1d | 149d | | Open issues (now) | 22 | 60 | | Stars delta | +49 (30d) | +10 (30d) | | Open issues delta | +6 (30d) | +5 (30d) | | Full report | [trust report](/tools/arcadeai-arcade-mcp/trust.md) | [trust report](/tools/kochava-studios-witsy/trust.md) | ## Shared compatibility - **Python**: [arcade-mcp](/tools/arcadeai-arcade-mcp.md) - Python runtime; [witsy](/tools/kochava-studios-witsy.md) - Python runtime ## 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: witsy - **Adopt for:** Witsy is a desktop AI assistant and universal MCP client that supports numerous LLM providers. It requires users to have API keys for models they wish to use, but also supports local model running through Ollama. ## Choose when ### Choose arcade-mcp if… - arcade-mcp is primarily Python; witsy is TypeScript. - License: arcade-mcp is MIT, witsy is AGPL-3.0. - Requirements: Min 4 GB RAM. - Tags unique to arcade-mcp: ai, arcade-ai, mcp-framework, model-context-protocol. - 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 witsy if… - witsy is primarily TypeScript; arcade-mcp is Python. - License: witsy is AGPL-3.0, arcade-mcp is MIT. - Tags unique to witsy: anthropic, deepseek, electronjs, gemini. - Also covers Inference & Serving. - witsy ships an MCP server manifest. - If you need an AI solution that can integrate with almost any LLM provider via MCP 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 witsy - If you do not have existing API keys from LLM providers and are not interested in setting up a local model through Ollama. - For users who require an out-of-the-box solution that does not necessitate managing multiple provider integrations or configurations for different services. ## Common questions ### What is the difference between arcade-mcp and witsy? arcade-mcp: MCP Server Framework and Tool Development Library for Custom Agent Capabilities. witsy: Desktop AI Assistant and Universal MCP Client. See the comparison table for live GitHub stats and shared categories. ### When should I choose arcade-mcp over witsy? Choose arcade-mcp over witsy when arcade-mcp is primarily Python; witsy is TypeScript; License: arcade-mcp is MIT, witsy is AGPL-3.0; Requirements: Min 4 GB RAM; Tags unique to arcade-mcp: ai, arcade-ai, mcp-framework, model-context-protocol; 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 witsy over arcade-mcp? Choose witsy over arcade-mcp when witsy is primarily TypeScript; arcade-mcp is Python; License: witsy is AGPL-3.0, arcade-mcp is MIT; Tags unique to witsy: anthropic, deepseek, electronjs, gemini; Also covers Inference & Serving; witsy ships an MCP server manifest; If you need an AI solution that can integrate with almost any LLM provider via MCP 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 witsy? If you do not have existing API keys from LLM providers and are not interested in setting up a local model through Ollama. For users who require an out-of-the-box solution that does not necessitate managing multiple provider integrations or configurations for different services. ### Is arcade-mcp or witsy more popular on GitHub? witsy has more GitHub stars (2,026 vs 1,030). Stars measure visibility, not whether either tool fits your constraints. ### Are arcade-mcp and witsy open source? Yes - both are open-source projects on GitHub (arcade-mcp: MIT, witsy: AGPL-3.0). ### Where can I find alternatives to arcade-mcp or witsy? GraphCanon lists graph-backed alternatives at [arcade-mcp alternatives](/tools/arcadeai-arcade-mcp/alternatives) and [witsy alternatives](/tools/kochava-studios-witsy/alternatives) ([arcade-mcp markdown twin](/tools/arcadeai-arcade-mcp/alternatives.md), [witsy markdown twin](/tools/kochava-studios-witsy/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-kochava-studios-witsy.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, arcade-mcp or witsy? arcade-mcp: Very active. witsy: Slowing. 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 witsy? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [arcade-mcp trust report](/tools/arcadeai-arcade-mcp/trust); [witsy trust report](/tools/kochava-studios-witsy/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/_