Free Tier
An open-source Python library for validating, documenting, and profiling data to ensure quality and reliability. It provides a framework for defining expectations about data and detecting anomalies or regressions.
#1 of 18 in Data · #1 of 2 in Quality
Checklist Breakdown
14 of 33 checks passed.
14 unscored.
Can an agent find and understand this tool without a web search?
✗
Published OpenAPI/Swagger spec
✗
Has llms.txt or llms-full.txt
✗
Has an MCP server (official or well-maintained)
✗
MCP server listed in a public registry
✓
API reference docs are publicly accessible
✓
Docs include runnable code examples
✓
Has a public changelog or release notes
✓
Has a public status page
Can an agent create an account and get credentials without human intervention?
✓
Signup does not require CAPTCHA
✓
Signup does not require phone verification
✗
Supports API key auth (not only OAuth)
✓
API key obtainable without manual approval
✓
No mandatory billing info to start
✓
Can sign up without creating an organization
Can an agent operate autonomously without upfront payment or contracts?
✓
Has a free tier
✓
Usage-based pricing available
✓
No minimum contract or commitment
✓
Pricing page is public (no 'contact sales')
✓
Free tier sufficient for testing (not just a trial)
How well does the API work for non-human consumers?
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SDK available in 2+ languages
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Structured error responses (JSON with error codes)
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Idempotency support on write endpoints
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Pagination on list endpoints
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Webhook/event support
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Sandbox or test mode available
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Rate limit headers in responses
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Consistent REST resource naming
Does the tool fail gracefully when an agent makes a mistake?
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Meaningful error messages (not just 500)
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429 responses include Retry-After header
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Documented uptime SLA (99.9%+)
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Graceful degradation under rate limits
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Request IDs in responses for debugging
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API versioning supported
Reviewer Notes
Great Expectations is primarily a local Python library with strong documentation and no authentication barriers, making it easily discoverable and deployable by agents in code. However, it lacks MCP/OpenAPI specifications and has limited remote service capabilities—agents must integrate it as a library dependency rather than call a remote API. The tool is well-maintained open-source software with reliable core functionality, but remote orchestration, cloud service discovery, and agentic orchestration workflows are not first-class patterns.
Let your agents find tools like Great Expectations
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