AEO Score for fastapi-mcp: 45/100
Hi! I analyzed fastapi-mcp with Clarvia — an AEO (AI Engine Optimization) scanner.
Score: 45/100 (C — Emerging)
AEO measures how easily AI agents discover and use MCP servers. Since fastapi-mcp converts FastAPI endpoints to MCP tools, its discoverability is directly tied to how agents choose which MCP servers to install.
Key improvement areas at this score level: MCP tool descriptions, structured error responses, and well-known endpoint discoverability.
Badge for README:
[](https://clarvia.art/scan?url=https://github.com/tadata-org/fastapi_mcp)
Full report: https://clarvia.art/scan?url=https://github.com/tadata-org/fastapi_mcp
AEO Score for fastapi-mcp: 45/100
Hi! I analyzed fastapi-mcp with Clarvia — an AEO (AI Engine Optimization) scanner.
Score: 45/100 (C — Emerging)
AEO measures how easily AI agents discover and use MCP servers. Since fastapi-mcp converts FastAPI endpoints to MCP tools, its discoverability is directly tied to how agents choose which MCP servers to install.
Key improvement areas at this score level: MCP tool descriptions, structured error responses, and well-known endpoint discoverability.
Badge for README:
Full report: https://clarvia.art/scan?url=https://github.com/tadata-org/fastapi_mcp