This release includes 4 breaking changes for platform teams planning a safe upgrade.
✓ No known CVEs patched in this version
Affected surfaces
Summary
AI summaryConfiguration schema changed from caps to defaults-only, giving the AI full control over limits.
Full changelog
4.0.0 (2025-12-23)
Features
BREAKING CHANGES
- Configuration schema changed from max*/caps to defaults-only
Changes:
- Config schema: maxResults/maxLogLines → defaultLimit/defaultLogLines/
defaultMetricDataPoints - Environment variables: MCP_MAX_* → MCP_DEFAULT_* pattern
- All tools: Removed Math.min() caps, AI has full control when specifying
limits - Metrics tool: Added pointLimit parameter for AI control over timeseries
resolution - Tests: Updated to verify AI control instead of cap enforcement
(903/903 passing) - README: Documented limit philosophy - env vars are defaults, NOT caps
The environment variables set what value is used when the AI doesn't
specify a limit. They do NOT cap what the AI can request.
Default values:
- defaultLimit: 50 (general tools)
- defaultLogLines: 200 (logs tool)
- defaultMetricDataPoints: 1000 (metrics timeseries)
- defaultTimeRangeHours: 24 (time range fallback)
- refactor: add input validation to prevent invalid limit values
- Add .min(1) validation to all limit/pageSize/count parameters across 16 tool files
- Prevents invalid values (0 or negative) while maintaining AI full control over maximums
- Extract SAMPLE_DIVERSITY_MULTIPLIER constant in logs.ts for clarity
- Remove 25k token limit documentation (Claude Code CLI specific, not universal MCP)
This improves input validation without restricting AI capabilities.
- feat: enhance events tool with nested top action and tag discovery
- Add discover action to find available tag prefixes in events
- Enhance top action with nested context breakdown (by_service array)
- Add contextTags parameter for customizable context extraction
- Implement findFirstContextTag helper for tag matching
- Add comprehensive tests for new functionality
- Update README with examples and usage patterns
- Simplify tool description to be more concise
The enhanced top action now returns monitors with nested structure:
{name, monitor_id, total_count, by_service: [{context, count}]}
- Renamed by_service field to by_context in top action response
Changes:
- Add input validation for contextTags parameter (array of non-empty strings)
- Optimize tag matching with Set for 6x performance improvement (O(1) vs O(n))
- Remove unsafe non-null assertion in topEventsV2
- Filter out monitors with empty context arrays from results
- Add configurable maxEvents parameter (default: 10000, max: 10000)
- Rename by_service → by_context for clearer API semantics
- Document maxEvents behavior and incomplete results scenario
The maxEvents parameter allows AI/users to tune accuracy vs performance based on
query scope. Narrow filters can safely increase limit for better accuracy.
Breaking Changes
- Configuration schema changed from maxResults/maxLogLines caps to defaults-only (defaultLimit, defaultLogLines, defaultMetricDataPoints).
- Environment variable prefixes changed: MCP_MAX_* → MCP_DEFAULT_*.
- Removed Math.min() caps; the AI now has full control when specifying limits.
- Renamed response field `by_service` → `by_context` in events tool top action.
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About TANTIOPE/datadog-mcp-server
MCP server providing comprehensive Datadog observability access for AI assistants. Features grep-like log search, APM trace filtering with duration/status/error queries, smart sampling modes for token efficiency, and cross-correlation between logs, traces, and metrics.
Related context
Beta — feedback welcome: [email protected]