--- title: "arcade-mcp vs fastapi_mcp" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/arcadeai-arcade-mcp-vs-tadata-org-fastapi-mcp" tools: ["arcadeai-arcade-mcp", "tadata-org-fastapi-mcp"] --- # arcade-mcp vs fastapi_mcp *GraphCanon updated Aug 26, 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 fastapi_mcp if fastapi_mcp enables FastAPI applications to integrate with MCP and includes authentication support. [arcade-mcp](https://docs.arcade.dev) reports 981 GitHub stars, 101 forks, and 16 open issues, last pushed Jul 26, 2026. [fastapi_mcp](https://fastapi-mcp.tadata.com/) has 12k stars, 964 forks, and 166 open issues, last pushed Nov 24, 2025. Figures are from public GitHub metadata via [arcade-mcp's repository](https://github.com/ArcadeAI/arcade-mcp) and [fastapi_mcp's repository](https://github.com/tadata-org/fastapi_mcp). | | [arcade-mcp](/tools/arcadeai-arcade-mcp.md) | [fastapi_mcp](/tools/tadata-org-fastapi-mcp.md) | | --- | --- | --- | | Tagline | MCP Server Framework and Tool Development Library for Custom Agent Capabilities | Expose FastAPI endpoints as MCP tools with authentication | | Stars | 981 | 11,986 | | Forks | 101 | 964 | | Open issues | 16 | 166 | | 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. | fastapi_mcp enables FastAPI applications to integrate with MCP and includes authentication support. | | Persona | - | - | | Runtime | - | - | | License | MIT | The MIT License grants permissive use rights without substantial obligations of any sort. | | Categories | AI Agents | LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [arcade-mcp](/tools/arcadeai-arcade-mcp.md) | [fastapi_mcp](/tools/tadata-org-fastapi-mcp.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 274d | | Open issues (now) | 16 | 166 | | Stars delta | Unknown | +30 (30d) | | Open issues delta | Unknown | +8 (30d) | | Full report | [trust report](/tools/arcadeai-arcade-mcp/trust.md) | [trust report](/tools/tadata-org-fastapi-mcp/trust.md) | ## Shared compatibility - **Python**: [arcade-mcp](/tools/arcadeai-arcade-mcp.md) - Python runtime; [fastapi_mcp](/tools/tadata-org-fastapi-mcp.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: fastapi_mcp - **Adopt for:** fastapi_mcp enables FastAPI applications to integrate with MCP and includes authentication support. - **License detail:** The MIT License grants permissive use rights without substantial obligations of any sort. ## Choose when ### Choose arcade-mcp if… - Requirements: Min 4 GB RAM. - Tags unique to arcade-mcp: arcade-ai, mcp-framework, model-context-protocol, python. - Also covers AI Agents. - 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 fastapi_mcp if… - Tags unique to fastapi_mcp: authentication, authorization, claude, cursor. - Also covers LLM Frameworks. - When you need to expose FastAPI application endpoints following the Model Context Protocol (MCP) guidelines. ## 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 fastapi_mcp - If your project strictly uses non-Python languages or frameworks that are not compatible with FastAPI and do not require integration with the Model Context Protocol (MCP). - When you seek broader support outside MCP protocol, as this tool confines its utility specifically to applications needing MCP compatibility. ## Common questions ### What is the difference between arcade-mcp and fastapi_mcp? arcade-mcp: MCP Server Framework and Tool Development Library for Custom Agent Capabilities. fastapi_mcp: Expose FastAPI endpoints as MCP tools with authentication. See the comparison table for live GitHub stats and shared categories. ### When should I choose arcade-mcp over fastapi_mcp? Choose arcade-mcp over fastapi_mcp when Requirements: Min 4 GB RAM; Tags unique to arcade-mcp: arcade-ai, mcp-framework, model-context-protocol, python; Also covers AI Agents; 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 fastapi_mcp over arcade-mcp? Choose fastapi_mcp over arcade-mcp when Tags unique to fastapi_mcp: authentication, authorization, claude, cursor; Also covers LLM Frameworks; When you need to expose FastAPI application endpoints following the Model Context Protocol (MCP) guidelines. ### 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 fastapi_mcp? If your project strictly uses non-Python languages or frameworks that are not compatible with FastAPI and do not require integration with the Model Context Protocol (MCP). When you seek broader support outside MCP protocol, as this tool confines its utility specifically to applications needing MCP compatibility. ### Is arcade-mcp or fastapi_mcp more popular on GitHub? fastapi_mcp has more GitHub stars (11,986 vs 981). Stars measure visibility, not whether either tool fits your constraints. ### Are arcade-mcp and fastapi_mcp open source? Yes - both are open-source projects on GitHub (arcade-mcp: MIT, fastapi_mcp: MIT). ### Where can I find alternatives to arcade-mcp or fastapi_mcp? GraphCanon lists graph-backed alternatives at [arcade-mcp alternatives](/tools/arcadeai-arcade-mcp/alternatives) and [fastapi_mcp alternatives](/tools/tadata-org-fastapi-mcp/alternatives) ([arcade-mcp markdown twin](/tools/arcadeai-arcade-mcp/alternatives.md), [fastapi_mcp markdown twin](/tools/tadata-org-fastapi-mcp/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-tadata-org-fastapi-mcp.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, arcade-mcp or fastapi_mcp? arcade-mcp: Very active. fastapi_mcp: 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 fastapi_mcp? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [arcade-mcp trust report](/tools/arcadeai-arcade-mcp/trust); [fastapi_mcp trust report](/tools/tadata-org-fastapi-mcp/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/_