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Implements MCP's tool-calling schema to expose Datadog's metrics API endpoints as callable functions, handling authentication via API key injection and response parsing into structured JSON.","intents":["Query historical metrics from Datadog to analyze application performance trends","Fetch real-time metric values for alerting or dashboard integration","Aggregate metrics across multiple hosts or services in a single query"],"best_for":["DevOps engineers building LLM-powered monitoring dashboards","SRE teams automating incident investigation workflows","Platform teams integrating Datadog metrics into AI-driven decision systems"],"limitations":["Query complexity limited by Datadog API rate limits (default 300 requests/hour per API key)","No local caching of metric results — each query hits Datadog API directly","DQL syntax errors from LLM-generated queries require manual debugging","Time range queries limited to Datadog's retention policy (15 months for standard metrics)"],"requires":["Datadog API key with metrics read permissions","Node.js 16+ runtime","MCP client implementation (Claude Desktop, custom MCP host, or compatible tool)","Network access to api.datadoghq.com or regional Datadog endpoint"],"input_types":["metric query parameters (metric name, time range, aggregation function)","filter expressions (tags, host names, service names)"],"output_types":["JSON array of time-series data points with timestamps","Aggregated metric values with metadata"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-winor30mcp-server-datadog__cap_1","uri":"capability://tool.use.integration.datadog.log.search.and.retrieval.via.mcp","name":"datadog log search and retrieval via mcp","description":"Searches Datadog's log aggregation platform through MCP tool bindings, translating search queries into Datadog's log query syntax and returning matching log entries with metadata. 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Implements event validation and tag formatting to ensure events conform to Datadog's schema, with response handling that returns event IDs for tracking.","intents":["Post deployment events to Datadog timeline for correlation with metrics/logs","Create incident annotations during automated incident response workflows","Send custom events from AI agents to trigger Datadog monitors or dashboards"],"best_for":["DevOps teams automating deployment tracking and correlation","SRE teams building AI-driven incident response systems","Platform teams creating event-driven monitoring workflows"],"limitations":["Event retention limited to 30 days in Datadog (archive required for longer retention)","Event payload size limited to 4KB per event","No bulk event creation — events posted individually (rate limited to 100/minute per API key)","Event deduplication not automatic — duplicate prevention requires client-side logic"],"requires":["Datadog API key with events write permissions","Node.js 16+ runtime","MCP client implementation","Valid Datadog organization and API endpoint"],"input_types":["event title and description","event timestamp","tags (key:value pairs)","alert type (info, warning, error, success)"],"output_types":["event ID (for reference/tracking)","event metadata (created timestamp, URL)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-winor30mcp-server-datadog__cap_3","uri":"capability://tool.use.integration.datadog.monitor.management.and.querying.via.mcp","name":"datadog monitor management and querying via mcp","description":"Queries and manages Datadog monitors (alerts) through MCP tool bindings, allowing agents to list monitors, check monitor status, and retrieve alert history. 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Uses MCP SDK to define tool schemas, validate requests, and serialize responses, with error handling that translates Datadog API errors into MCP-compatible error responses.","intents":["Enable Claude or other LLM clients to call Datadog tools without custom integration code","Securely manage Datadog API credentials without exposing them to LLM context","Provide standardized tool interface for Datadog operations across different MCP clients"],"best_for":["Teams deploying Claude Desktop with Datadog integration","Custom MCP host implementations needing Datadog support","Organizations standardizing on MCP for tool integration"],"limitations":["Single API key per MCP server instance — no multi-tenant support","No request rate limiting at MCP layer (relies on Datadog API limits)","Error messages from Datadog API exposed to client (may leak internal details)","No built-in request/response logging or audit trail"],"requires":["DATADOG_API_KEY environment variable set","Node.js 16+ runtime","MCP client that supports this server (Claude Desktop 0.1+, custom MCP hosts)","Network connectivity to Datadog API endpoints"],"input_types":["MCP tool call requests (JSON-RPC format)","tool parameters as JSON objects"],"output_types":["MCP tool results (JSON-RPC responses)","error responses with Datadog API error details"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-winor30mcp-server-datadog__cap_5","uri":"capability://tool.use.integration.datadog.dashboard.and.widget.querying.via.mcp","name":"datadog dashboard and widget querying via mcp","description":"Queries Datadog dashboards and their widget configurations through MCP tool bindings, enabling agents to retrieve dashboard definitions, widget metrics, and visualization settings. Implements dashboard filtering by name or tag, with response parsing that extracts widget queries, data sources, and layout information for analysis or replication.","intents":["Retrieve dashboard definitions for audit or documentation purposes","Extract metric queries from dashboard widgets for reuse in alerts or reports","Query dashboard metadata to understand monitoring strategy for a service"],"best_for":["Platform teams documenting monitoring configurations","SRE teams analyzing dashboard coverage and metric selection","Teams migrating dashboards between Datadog organizations"],"limitations":["Dashboard creation/modification not supported (read-only)","Widget custom code (JavaScript) not returned in queries","Large dashboards (50+ widgets) may have slow response times","No real-time dashboard data — returns widget definitions, not live metric values"],"requires":["Datadog API key with dashboards read permissions","Node.js 16+ runtime","MCP client with tool-calling support","Dashboards created in Datadog organization"],"input_types":["dashboard filter criteria (name, tag, ID)","pagination parameters"],"output_types":["JSON dashboard definition with widget configurations","widget metric queries and data sources","dashboard metadata (ID, creator, last modified)"],"categories":["tool-use-integration","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":34,"verified":false,"data_access_risk":"high","permissions":["Datadog API key with metrics read permissions","Node.js 16+ runtime","MCP client implementation (Claude Desktop, custom MCP host, or compatible tool)","Network access to api.datadoghq.com or regional Datadog endpoint","Datadog API key with logs read permissions","MCP client with tool-calling support","Logs indexed in Datadog (requires log agent or integration)","Datadog API key with events write permissions","MCP client implementation","Valid Datadog organization and API endpoint"],"failure_modes":["Query complexity limited by Datadog API rate limits (default 300 requests/hour per API key)","No local caching of metric results — each query hits Datadog API directly","DQL syntax errors from LLM-generated queries require manual debugging","Time range queries limited to Datadog's retention policy (15 months for standard metrics)","Log retention depends on Datadog plan (3-30 days for standard, longer with archive)","Complex boolean queries may timeout if result set exceeds 10,000 logs","No streaming results — entire result set buffered before return","Sensitive data in logs (API keys, PII) not automatically redacted by MCP server","Event retention limited to 30 days in Datadog (archive required for longer retention)","Event payload size limited to 4KB per event","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.4978059736137633,"quality":0.22,"ecosystem":0.3,"match_graph":0.25,"freshness":0.52,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:24.483Z","last_scraped_at":"2026-05-03T14:23:32.060Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":15417,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=npm-winor30mcp-server-datadog","compare_url":"https://unfragile.ai/compare?artifact=npm-winor30mcp-server-datadog"}},"signature":"wnSy1XQISIpoL97ah0NzoPYKkYyQyS3GMUOMWmWKb4+KbGACTCyCYVjKagGKWAu2zqFmA8Eg0EwgO8i5GLQzBw==","signedAt":"2026-06-21T13:23:49.226Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/npm-winor30mcp-server-datadog","artifact":"https://unfragile.ai/npm-winor30mcp-server-datadog","verify":"https://unfragile.ai/api/v1/verify?slug=npm-winor30mcp-server-datadog","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}