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FastMCP vs Cortex

FastMCPCortex

Bottom line: FastMCP for python developers building MCP servers; Cortex for aPI teams with maintained specifications.

FastMCPFastMCP

The fast, Pythonic way to build MCP servers and clients, plus optional cloud hosting.

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CortexCortex

Turn API specifications into docs, typed SDKs, and an MCP server

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Votes00
PricingFreemiumFree
CategoryMcpMcp
Tags
mcppythonframeworkopen-sourceserver-sdk
mcp serverapi documentationsdk generationopenapiopen source
Best for
  • Python developers building MCP servers
  • Teams wrapping internal services as tools
  • Prototyping MCP clients
  • API teams with maintained specifications
  • Teams exposing APIs to agents via MCP
  • Open-source projects needing docs and SDKs
Pros
  • Minimal-boilerplate, decorator-based API
  • Auto-generates schema, validation, and docs
  • Powers a large share of MCP servers
  • Open source and free
  • Handles transport, auth, and lifecycle
  • MIT licensed with a public repository
  • Generates docs, SDKs, and an MCP server from one spec
  • Supports OpenAPI, AsyncAPI, GraphQL, gRPC, and OpenRPC
  • Eleven SDK output languages
  • Fully self-hostable, deployable anywhere Node runs
Cons
  • Python only
  • Fast-moving API across 1.0/2.0/3.0 requires version pinning
  • Hosted FastMCP Cloud/Horizon are separate paid products
  • Relationship between the SDK-bundled version and standalone project can confuse newcomers
  • Production hardening still on the developer
  • Output quality depends entirely on spec quality
  • No hosted service or commercial support
  • Requires a build step in your pipeline
  • No team collaboration features
  • Young project with a small ecosystem

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