Mockzilla vs Decision Node

Detailed side-by-side comparison to help you choose the right tool

Mockzilla

🔴Developer

Developer Tools

MCP server for API mocking — lets coding agents create mock APIs from OpenAPI specs or single endpoints.

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Starting Price

Custom

Decision Node

🔴Developer

Developer Tools

MCP server that records development decisions as structured JSON, embeds them as vectors, and enables semantic search over past decisions.

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Starting Price

Custom

Feature Comparison

Scroll horizontally to compare details.

FeatureMockzillaDecision Node
CategoryDeveloper ToolsDeveloper Tools
Pricing Plans6 tiers315 tiers
Starting Price
Key Features
    • MCP server for AI coding tools
    • Structured JSON decision records
    • Semantic decision search

    Mockzilla - Pros & Cons

    Pros

    • Simplest spec-to-mock workflow available — git push is the only step
    • PR environments solve 'mock out of date' and 'works on my machine' problems
    • Only API mocking tool with native MCP support for AI agents
    • 148,000+ MCP installs demonstrate strong developer adoption
    • Spec-driven approach keeps mocks automatically in sync with API contracts

    Cons

    • Hosted simulations require a Mockzilla account (not fully self-hosted)
    • Limited to REST APIs — no GraphQL or gRPC mocking
    • GitHub-centric workflow — GitLab and Bitbucket support unclear
    • Complex dynamic response logic may require custom configuration beyond specs
    • Newer platform — long-term stability and maintenance commitment unproven

    Decision Node - Pros & Cons

    Pros

    • Semantic search finds relevant decisions even with different terminology
    • Works across all major AI coding tools via MCP
    • Local storage keeps sensitive decisions on-premises
    • Visual UI helps teams explore decision relationships
    • Structured format prevents decisions from becoming unstructured brain dumps

    Cons

    • Requires a Gemini API key for vector embeddings (adds dependency and cost)
    • Only useful if the team consistently records decisions — needs adoption discipline
    • Local-only storage means no built-in team sync or cloud collaboration
    • Vector embeddings are Gemini-specific — no choice of embedding provider
    • No integration with existing decision documentation tools (ADR tools, Notion, etc.)

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