--- title: "arcade-mcp vs fastmcp" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/arcadeai-arcade-mcp-vs-prefecthq-fastmcp" tools: ["arcadeai-arcade-mcp", "prefecthq-fastmcp"] --- # arcade-mcp vs fastmcp *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 fastmcp if fastmcp is designed for efficient creation of MCP servers and clients in Python, fitting projects looking to streamline AI agent context handling. [arcade-mcp](https://docs.arcade.dev) reports 981 GitHub stars, 101 forks, and 16 open issues, last pushed Jul 26, 2026. [fastmcp](https://gofastmcp.com) has 27k stars, 2.2k forks, and 265 open issues, last pushed Jul 26, 2026. Figures are from public GitHub metadata via [arcade-mcp's repository](https://github.com/ArcadeAI/arcade-mcp) and [fastmcp's repository](https://github.com/PrefectHQ/fastmcp). | | [arcade-mcp](/tools/arcadeai-arcade-mcp.md) | [fastmcp](/tools/prefecthq-fastmcp.md) | | --- | --- | --- | | Tagline | MCP Server Framework and Tool Development Library for Custom Agent Capabilities | The fast Pythonic way to build MCP servers and clients | | Stars | 981 | 26,846 | | Forks | 101 | 2,187 | | Open issues | 16 | 265 | | Language | Python | Python | | 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. | fastmcp is designed for efficient creation of MCP servers and clients in Python, fitting projects looking to streamline AI agent context handling. | | Persona | - | - | | Runtime | - | - | | License | MIT | FastMCP is licensed under the Apache License 2.0 which allows free use, modification and distribution of the software provided that the original license is included with each copy. | | Categories | AI Agents | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [arcade-mcp](/tools/arcadeai-arcade-mcp.md) | [fastmcp](/tools/prefecthq-fastmcp.md) | | --- | --- | --- | | Open issues (now) | 16 | 265 | | Full report | [trust report](/tools/arcadeai-arcade-mcp/trust.md) | [trust report](/tools/prefecthq-fastmcp/trust.md) | ## Shared compatibility - **Python**: [arcade-mcp](/tools/arcadeai-arcade-mcp.md) - Python runtime; [fastmcp](/tools/prefecthq-fastmcp.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: fastmcp - **Pricing:** freemium - The core FastMCP library is free to use, with no premium tiers available as it is an open-source project. - **Adopt for:** fastmcp is designed for efficient creation of MCP servers and clients in Python, fitting projects looking to streamline AI agent context handling. - **License detail:** FastMCP is licensed under the Apache License 2.0 which allows free use, modification and distribution of the software provided that the original license is included with each copy. ## Choose when ### Choose arcade-mcp if… - License: arcade-mcp is MIT, fastmcp is Apache-2.0. - 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 fastmcp if… - License: fastmcp is Apache-2.0, arcade-mcp is MIT. - Pricing: The core FastMCP library is free to use, with no premium tiers available as it is an open-source project.. - Tags unique to fastmcp: agents, fastmcp, llms, mcp. - Also covers LLM Frameworks. - Use fastmcp if your project demands high-performance Model Context Protocol (MCP) server or client development in Python. ## 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 fastmcp - Avoid fastmcp if your project strictly requires language support beyond Python, as it is solely designed for Python development. - Do not select this tool when the need arises to adhere to licensing terms outside of Apache-2.0. ## Common questions ### What is the difference between arcade-mcp and fastmcp? arcade-mcp: MCP Server Framework and Tool Development Library for Custom Agent Capabilities. fastmcp: The fast Pythonic way to build MCP servers and clients. See the comparison table for live GitHub stats and shared categories. ### When should I choose arcade-mcp over fastmcp? Choose arcade-mcp over fastmcp when License: arcade-mcp is MIT, fastmcp is Apache-2.0; 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 fastmcp over arcade-mcp? Choose fastmcp over arcade-mcp when License: fastmcp is Apache-2.0, arcade-mcp is MIT; Pricing: The core FastMCP library is free to use, with no premium tiers available as it is an open-source project.; Tags unique to fastmcp: agents, fastmcp, llms, mcp; Also covers LLM Frameworks; Use fastmcp if your project demands high-performance Model Context Protocol (MCP) server or client development in Python. ### 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 fastmcp? Avoid fastmcp if your project strictly requires language support beyond Python, as it is solely designed for Python development. Do not select this tool when the need arises to adhere to licensing terms outside of Apache-2.0. ### Is arcade-mcp or fastmcp more popular on GitHub? fastmcp has more GitHub stars (26,846 vs 981). Stars measure visibility, not whether either tool fits your constraints. ### Are arcade-mcp and fastmcp open source? Yes - both are open-source projects on GitHub (arcade-mcp: MIT, fastmcp: Apache-2.0). ### Where can I find alternatives to arcade-mcp or fastmcp? GraphCanon lists graph-backed alternatives at [arcade-mcp alternatives](/tools/arcadeai-arcade-mcp/alternatives) and [fastmcp alternatives](/tools/prefecthq-fastmcp/alternatives) ([arcade-mcp markdown twin](/tools/arcadeai-arcade-mcp/alternatives.md), [fastmcp markdown twin](/tools/prefecthq-fastmcp/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-prefecthq-fastmcp.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, arcade-mcp or fastmcp? arcade-mcp: Very active. fastmcp: Very active. 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 fastmcp? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [arcade-mcp trust report](/tools/arcadeai-arcade-mcp/trust); [fastmcp trust report](/tools/prefecthq-fastmcp/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/_