Mockzilla vs Continue
Detailed side-by-side comparison to help you choose the right tool
Mockzilla
🔴DeveloperDeveloper Tools
MCP server for API mocking — lets coding agents create mock APIs from OpenAPI specs or single endpoints.
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Starting Price
Free (MIT license)Continue
🔴DeveloperDeveloper Tools
Open-source AI coding assistant for VS Code and JetBrains — bring any model, any MCP server, and share reusable rules and agents across your team via Continue Hub.
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Starting Price
FreeFeature Comparison
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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- ✓PR environments solve 'mock out of date' and 'works on my machine' problems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
Continue - Pros & Cons
Pros
- ✓Open-source assistant for VS Code and JetBrains. This directly supports the primary workflow.
- ✓Bring-your-own-model: Anthropic, OpenAI, Ollama, local, any provider.
- ✓First-class MCP client — any MCP server becomes callable tools.
- ✓Continue Hub for sharing assistants, rules, prompts across a team.
Cons
- ✗At least one tier requires a sales quote, preventing a complete public budget calculation.
- ✗Features and limits can change by plan, billing interval, region, and release; verify current documentation.
- ✗MCP connectivity expands the permission surface and requires narrow scopes, approvals, logs, and credential rotation.
- ✗A representative pilot is necessary because a feature list does not establish reliability or operational fit.
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