{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"grafana-mcp-server","slug":"grafana-mcp-server","name":"Grafana MCP Server","type":"mcp","url":"https://github.com/grafana/mcp-grafana","page_url":"https://unfragile.ai/grafana-mcp-server","categories":["mcp-servers"],"tags":["grafana","monitoring","dashboards","official"],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"grafana-mcp-server__cap_0","uri":"capability://tool.use.integration.mcp.protocol.server.with.multi.transport.bridging","name":"mcp protocol server with multi-transport bridging","description":"Implements the Model Context Protocol as a Go-based server using the mark3labs/mcp-go framework, supporting three transport modes (stdio for direct process integration, SSE for server-sent events, and streamable-http for stateless deployments). The server exposes Grafana capabilities as standardized MCP tools that AI assistants can discover and invoke through a unified interface, abstracting away Grafana API complexity behind tool schemas.","intents":["I want to connect Claude or another AI assistant to my Grafana instance without building custom integrations","I need to expose Grafana as a tool that an LLM agent can call programmatically","I want to support multiple transport modes (stdio, SSE, HTTP) depending on my deployment architecture"],"best_for":["DevOps teams integrating Grafana with AI-powered observability workflows","Developers building LLM agents that need standardized access to monitoring data","Organizations deploying MCP servers in containerized or serverless environments"],"limitations":["Transport mode selection is fixed at startup — cannot switch between stdio/SSE/HTTP at runtime","Multi-tenant deployments require SessionManager configuration per HTTP request, adding per-request overhead","MCP protocol version compatibility depends on client implementation — older clients may not support all tool features"],"requires":["Go 1.19+ (for server compilation)","Grafana instance with API access (any version with REST API support)","MCP-compatible client (Claude Desktop, or custom MCP client implementation)","Network connectivity from MCP server to Grafana instance"],"input_types":["MCP tool invocation requests with JSON-serialized parameters","Grafana API credentials (API key or OAuth token)","Query parameters and filter specifications"],"output_types":["MCP tool result responses (JSON-structured data)","Grafana API responses (dashboards, metrics, alerts, annotations)","Error responses with diagnostic information"],"categories":["tool-use-integration","mcp-servers"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"grafana-mcp-server__cap_1","uri":"capability://data.processing.analysis.datasource.agnostic.query.execution.with.multi.provider.support","name":"datasource-agnostic query execution with multi-provider support","description":"Exposes a unified query interface that routes requests to Grafana's datasource abstraction layer, supporting Prometheus, Loki, Pyroscope, Elasticsearch, CloudWatch, and other configured datasources. The server translates MCP tool parameters into datasource-specific query formats, handles authentication delegation to Grafana, and returns results in a normalized structure. This abstraction allows AI assistants to query any datasource without knowing its native query language.","intents":["I want to query metrics from Prometheus without writing PromQL directly","I need to search logs in Loki using natural language that gets translated to LogQL","I want to execute queries across multiple datasources without managing separate API keys or authentication"],"best_for":["Teams with heterogeneous datasource stacks (Prometheus + Loki + Elasticsearch)","Non-expert users who want to query observability data without learning PromQL/LogQL","AI agents that need to dynamically select datasources based on query intent"],"limitations":["Query translation is datasource-specific — complex queries may lose nuance when converted from natural language to PromQL/LogQL","Datasource availability depends on Grafana configuration — if a datasource is not configured in Grafana, it cannot be queried","Authentication is delegated to Grafana, so datasource-level RBAC is inherited from Grafana's permission model","Query timeout and result size limits are inherited from Grafana datasource configuration"],"requires":["Grafana instance with at least one configured datasource","API key or service account token with datasource query permissions","Datasource-specific credentials already configured in Grafana (MCP server does not manage datasource auth directly)"],"input_types":["Query parameters (datasource ID, query string, time range)","Optional: datasource-specific query format (PromQL, LogQL, etc.)","Time range specifications (relative or absolute)"],"output_types":["Time series data (metrics with timestamps and values)","Log entries (structured or unstructured text with metadata)","Trace data (from Pyroscope or similar)","Structured query results in JSON format"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"grafana-mcp-server__cap_10","uri":"capability://automation.workflow.opentelemetry.tracing.and.prometheus.metrics.observability","name":"opentelemetry tracing and prometheus metrics observability","description":"Integrates OpenTelemetry tracing and Prometheus metrics collection into the MCP server itself, allowing operators to observe MCP server behavior, tool execution latency, and error rates. The server exports traces to configured OpenTelemetry backends and exposes Prometheus metrics on a metrics endpoint. This enables operators to monitor the MCP server's health and performance without external instrumentation.","intents":["I want to monitor the latency of MCP tool executions","I need to track error rates and failure modes in the MCP server","I want to understand which tools are being used most frequently"],"best_for":["Operators managing production MCP server deployments","Teams that need to monitor MCP server performance and reliability","Organizations with existing OpenTelemetry and Prometheus infrastructure"],"limitations":["Tracing and metrics are opt-in — require explicit configuration to enable","OpenTelemetry export adds overhead to request processing — may impact latency for high-frequency queries","Metrics are exposed on a separate HTTP endpoint — requires additional network configuration","Trace sampling is configurable but not adaptive — no automatic sampling based on error rates"],"requires":["OpenTelemetry collector or backend (optional, for trace export)","Prometheus scrape configuration (optional, for metrics collection)","Environment variables or configuration file for OpenTelemetry setup"],"input_types":["OpenTelemetry configuration (collector endpoint, sampling rate)","Prometheus metrics configuration (port, path)"],"output_types":["OpenTelemetry traces (exported to configured backend)","Prometheus metrics (exposed on metrics endpoint)","Structured logs with trace context"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"grafana-mcp-server__cap_11","uri":"capability://tool.use.integration.tool.schema.discovery.and.dynamic.tool.registration","name":"tool schema discovery and dynamic tool registration","description":"Implements a tool management framework that dynamically discovers and registers MCP tools based on Grafana configuration and datasource availability. The server exposes tool schemas through the MCP protocol, allowing clients to discover available tools, their parameters, and expected outputs. Tools are registered at startup based on configured datasources and Grafana features, and the schema includes validation rules, parameter descriptions, and example usage.","intents":["I want to discover what tools are available in the MCP server without reading documentation","I need to understand the parameters and expected outputs of a specific tool","I want to dynamically adapt my AI agent based on available tools"],"best_for":["AI agents that need to discover available tools at runtime","Developers building MCP clients that need to adapt to different server configurations","Teams that want to expose different tools based on Grafana configuration"],"limitations":["Tool schemas are static after server startup — changes to Grafana configuration require server restart","Tool discovery is limited to tools exposed by the MCP server — no discovery of Grafana UI features","Schema validation is basic — complex parameter constraints may not be expressible in tool schemas","Tool availability depends on Grafana permissions — some tools may not be available to all users"],"requires":["MCP client that supports tool discovery (most modern MCP clients)","Grafana instance with configured datasources and features"],"input_types":["MCP tool list request"],"output_types":["Tool schema list (tool names, parameters, descriptions, examples)"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"grafana-mcp-server__cap_12","uri":"capability://data.processing.analysis.grafana.variable.resolution.and.dashboard.context.propagation","name":"grafana variable resolution and dashboard context propagation","description":"Provides tools to resolve Grafana dashboard variables (template variables) and propagate them through query execution. The server retrieves variable definitions from dashboards, resolves variable values based on current selections or defaults, and injects resolved values into queries executed against dashboard panels. This enables AI assistants to execute queries with the correct variable context without manually managing variable resolution.","intents":["I want to execute a dashboard panel query with the current variable selections","I need to resolve a dashboard variable to its current value","I want to execute a query with different variable values than the dashboard default"],"best_for":["Incident investigation workflows that need to execute dashboard queries with current context","AI agents analyzing dashboards with complex variable configurations","Automation that needs to programmatically resolve and use dashboard variables"],"limitations":["Variable resolution is limited to variables defined in the dashboard — no cross-dashboard variable references","Dynamic variable values (from queries) require executing the variable query — adds latency","Variable cascading (where one variable depends on another) requires sequential resolution","Some variable types (e.g., custom) may not be resolvable without user input"],"requires":["Dashboard ID with variable definitions","Grafana API key with dashboard read permissions"],"input_types":["Dashboard ID","Variable name (optional, for resolving specific variables)","Variable value overrides (optional, for custom variable values)"],"output_types":["Variable definitions (name, type, default value)","Resolved variable values","Variable options (for multi-select variables)"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"grafana-mcp-server__cap_13","uri":"capability://search.retrieval.grafana.folder.and.permission.aware.resource.navigation","name":"grafana folder and permission-aware resource navigation","description":"Provides tools to navigate Grafana's folder hierarchy and respect permission boundaries when listing resources (dashboards, datasources, alert rules). The server queries Grafana's folder API and applies RBAC filters based on the authenticated user's permissions, ensuring that only accessible resources are returned. This enables AI assistants to navigate Grafana's resource hierarchy while respecting organizational access controls.","intents":["I want to list all folders and their contents that I have access to","I need to find a dashboard within a specific folder hierarchy","I want to understand the permission structure of Grafana resources"],"best_for":["Large Grafana deployments with complex folder hierarchies and RBAC","Teams that need to enforce permission boundaries in AI-driven workflows","Automation that needs to respect Grafana's access control model"],"limitations":["Folder navigation is limited to folders the user has read access to — no discovery of restricted folders","Permission inheritance is complex — folder permissions may be overridden at resource level","Folder hierarchy depth may be large — listing all folders could be slow for deeply nested structures","Permission changes are not reflected in real-time — cached permission data may be stale"],"requires":["Grafana instance with folder structure configured","API key with folder and resource read permissions"],"input_types":["Folder ID (optional, for listing folder contents)","Resource type filter (optional, for filtering by resource type)"],"output_types":["Folder list (with hierarchy and permissions)","Resource list (dashboards, datasources, alert rules within folder)","Permission information (user/team permissions for resources)"],"categories":["search-retrieval","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"grafana-mcp-server__cap_14","uri":"capability://data.processing.analysis.pyroscope.profiling.data.querying.and.trace.analysis","name":"pyroscope profiling data querying and trace analysis","description":"Provides specialized tools for querying Pyroscope profiling datasources, including profile data retrieval, flame graph generation, and performance hotspot identification. The server translates MCP tool parameters into Pyroscope API calls and returns profiling data in a format suitable for analysis. This enables AI assistants to analyze application performance profiles and identify optimization opportunities.","intents":["I want to retrieve CPU profiling data for a specific service and time range","I need to identify performance hotspots in application code","I want to compare profiling data across different time periods or versions"],"best_for":["Performance engineering teams that need programmatic access to profiling data","AI agents analyzing application performance for optimization recommendations","Incident response workflows that need to correlate performance issues with metrics"],"limitations":["Profiling data is only available if Pyroscope is configured as a datasource in Grafana","Profile data can be large — result size limits may truncate detailed profiling information","Flame graph generation requires client-side rendering — MCP server returns raw profiling data","Profile comparison requires manual data processing — no built-in comparison tools"],"requires":["Grafana instance with Pyroscope datasource configured","Pyroscope instance with profiling data collection enabled","API key with Pyroscope query permissions"],"input_types":["Service or application name","Profile type (cpu, memory, goroutine, etc.)","Time range (relative or absolute timestamps)"],"output_types":["Profiling data (stack traces with sample counts)","Flame graph data (hierarchical call stacks)","Performance metrics (CPU usage, memory allocation, etc.)"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"grafana-mcp-server__cap_15","uri":"capability://data.processing.analysis.grafana.user.and.organization.management.querying","name":"grafana user and organization management querying","description":"Provides tools to query Grafana user and organization information, including user lists, organization membership, and role assignments. The server queries Grafana's admin API to expose user and organization data. This enables AI assistants to understand Grafana's organizational structure and user permissions without accessing the Grafana UI.","intents":["I want to see all users in a Grafana organization","I need to understand a user's role and permissions","I want to list all organizations in a Grafana instance"],"best_for":["Grafana administrators that need programmatic access to user and organization data","Automation workflows that need to manage Grafana users and permissions","AI agents that need to understand organizational structure for access control"],"limitations":["User and organization management (create/update/delete) is not supported — read-only access only","User data is limited to information exposed by Grafana API — no custom user attributes","Organization membership queries are limited to organizations the user has access to","Role information is limited to Grafana's built-in roles — no custom role support"],"requires":["Grafana instance with admin API enabled","API key with admin permissions (for user and organization queries)"],"input_types":["Organization ID (optional, for querying organization-specific users)","User ID or email (optional, for querying specific user)"],"output_types":["User list (with email, role, organization membership)","User details (permissions, teams, last login)","Organization list (with name and user count)","Organization details (members and roles)"],"categories":["data-processing-analysis","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"grafana-mcp-server__cap_16","uri":"capability://memory.knowledge.context.window.optimization.and.token.usage.tracking","name":"context window optimization and token usage tracking","description":"Implements context window management strategies to optimize LLM token usage when working with large dashboard definitions, query results, and profiling data. The server provides tools to estimate token usage, truncate results intelligently, and summarize large datasets. Token usage is tracked and exposed through observability metrics, allowing operators to understand and optimize context consumption.","intents":["I want to understand how many tokens a dashboard definition will consume","I need to retrieve large query results without exceeding my LLM's context window","I want to summarize large profiling datasets for analysis"],"best_for":["Teams using expensive LLM APIs that charge per token","AI agents with limited context windows that need to work with large datasets","Operators that need to track and optimize token usage"],"limitations":["Token estimation is approximate — actual token usage depends on LLM tokenizer","Result truncation may lose important data — intelligent summarization requires domain knowledge","Context window optimization is not automatic — requires explicit tool invocation","Token tracking requires observability infrastructure — not available without OpenTelemetry setup"],"requires":["OpenTelemetry setup (optional, for token tracking)","LLM tokenizer configuration (for accurate token estimation)"],"input_types":["Data to estimate (dashboard definition, query results, etc.)","Target context window size (optional, for result truncation)"],"output_types":["Token count estimate","Truncated results (if result size exceeds context window)","Summarized data (high-level overview of large datasets)"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"grafana-mcp-server__cap_2","uri":"capability://search.retrieval.dashboard.discovery.and.metadata.retrieval.with.search.filtering","name":"dashboard discovery and metadata retrieval with search filtering","description":"Provides tools to list all dashboards accessible to the authenticated user, search dashboards by name/tag/folder, and retrieve full dashboard definitions including panel configurations, datasource references, and variable definitions. The server queries Grafana's dashboard API and returns structured metadata that AI assistants can use to understand available observability resources and select relevant dashboards for analysis.","intents":["I want to find dashboards related to 'database performance' without manually browsing Grafana UI","I need to retrieve the full definition of a dashboard to understand which metrics it uses","I want to list all dashboards in a specific folder or with a specific tag"],"best_for":["AI agents that need to discover relevant dashboards before executing queries","Teams with large numbers of dashboards (100+) that need programmatic discovery","Automation workflows that need to reference dashboard definitions"],"limitations":["Search is limited to dashboard name, tags, and folder — does not search panel content or queries","Dashboard definitions can be large (100KB+) for complex dashboards with many panels, impacting token usage in LLM context","Folder hierarchy is flattened in search results — no tree-based folder navigation","Dashboard permissions are inherited from Grafana RBAC — user can only see dashboards they have read access to"],"requires":["Grafana API key or service account token with dashboard read permissions","Grafana instance with at least one dashboard"],"input_types":["Search query string (optional, for filtering by name)","Tag filter (optional, for filtering by tags)","Folder ID (optional, for filtering by folder)","Dashboard ID (for retrieving specific dashboard definition)"],"output_types":["Dashboard list with metadata (ID, title, tags, folder, last modified)","Full dashboard definition (JSON) including panels, datasources, variables, annotations"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"grafana-mcp-server__cap_3","uri":"capability://data.processing.analysis.panel.data.extraction.and.visualization.query.execution","name":"panel data extraction and visualization query execution","description":"Allows retrieval of data from specific dashboard panels by executing the panel's configured queries against its datasources. The server extracts query definitions from a dashboard panel, executes them with the specified time range, and returns the raw data that would be visualized in the panel. This enables AI assistants to analyze the exact data powering a dashboard visualization without needing to understand the underlying query language.","intents":["I want to get the raw data from a specific panel in a dashboard","I need to execute a panel's query with a different time range than what's currently displayed","I want to understand what data is being visualized in a dashboard panel"],"best_for":["Incident investigation workflows that need to extract data from specific dashboard panels","AI agents analyzing dashboard data to generate insights or alerts","Automation that needs to programmatically access panel data for further processing"],"limitations":["Panel data extraction is limited to panels with queryable datasources — visualization-only panels (text, static content) return no data","Query execution inherits datasource timeout and result size limits — very large result sets may be truncated","Panel variables must be resolved before query execution — dynamic variable resolution requires additional context","Some panel types (e.g., Piechart with transformations) may require transformation logic that is not exposed through the API"],"requires":["Dashboard ID and panel ID","Grafana API key with dashboard and datasource query permissions","Time range specification (relative or absolute)"],"input_types":["Dashboard ID (string)","Panel ID (string or number)","Time range (relative like '1h' or absolute timestamps)","Optional: variable overrides for dashboard variables"],"output_types":["Time series data (metrics with timestamps and values)","Table data (rows and columns)","Log entries (from log panels)","Raw query results in JSON format"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"grafana-mcp-server__cap_4","uri":"capability://data.processing.analysis.prometheus.native.metric.querying.with.promql.support","name":"prometheus-native metric querying with promql support","description":"Provides specialized tools for querying Prometheus datasources using PromQL, including metric name completion, label value lookup, and instant/range query execution. The server translates MCP tool parameters into Prometheus API calls (instant queries, range queries, label queries) and returns results in Prometheus native format. This enables AI assistants to leverage Prometheus's full query capabilities while maintaining the MCP abstraction.","intents":["I want to execute a PromQL query against Prometheus without managing the HTTP API directly","I need to discover available metric names and labels in Prometheus","I want to get metric values at a specific point in time or over a time range"],"best_for":["Teams using Prometheus as their primary metrics backend","AI agents that need to execute complex PromQL queries for analysis","Incident response workflows that need rapid metric exploration"],"limitations":["PromQL query validation is delegated to Prometheus — invalid queries fail at execution time, not at tool invocation","Metric cardinality limits are inherited from Prometheus configuration — high-cardinality queries may timeout","Label value lookups are limited to labels present in the Prometheus instance — no cross-datasource label discovery","Query results are limited by Prometheus max_samples_limit — very large result sets are truncated"],"requires":["Grafana instance with Prometheus datasource configured","Prometheus instance accessible from MCP server","API key with Prometheus query permissions"],"input_types":["PromQL query string","Time range (relative or absolute timestamps)","Optional: step parameter for range queries"],"output_types":["Instant query results (single value per metric)","Range query results (time series with multiple samples)","Metric names (from metric completion)","Label values (from label lookup)"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"grafana-mcp-server__cap_5","uri":"capability://data.processing.analysis.loki.log.querying.with.logql.and.log.stream.filtering","name":"loki log querying with logql and log stream filtering","description":"Provides specialized tools for querying Loki datasources using LogQL, including log stream label discovery, log entry retrieval, and metric extraction from logs. The server translates MCP tool parameters into Loki API calls (query_range, query, labels, label_values) and returns results in Loki native format. This enables AI assistants to search and analyze logs programmatically without requiring knowledge of LogQL syntax.","intents":["I want to search logs for a specific error message or pattern","I need to retrieve logs from a specific service or pod over a time range","I want to discover available log labels and streams in Loki"],"best_for":["Teams using Loki for log aggregation and analysis","Incident investigation workflows that need to correlate logs with metrics","AI agents analyzing logs to identify root causes or patterns"],"limitations":["LogQL query validation is delegated to Loki — invalid queries fail at execution time","Log result size is limited by Loki max_cache_freshness_per_query — very large log volumes may be truncated","Label discovery is limited to labels present in Loki — no cross-datasource label discovery","Log parsing and extraction requires LogQL pipeline operators — complex transformations may not be expressible through the tool interface"],"requires":["Grafana instance with Loki datasource configured","Loki instance accessible from MCP server","API key with Loki query permissions"],"input_types":["LogQL query string or log stream selector","Time range (relative or absolute timestamps)","Optional: limit parameter for result size"],"output_types":["Log entries (with timestamps and labels)","Log stream labels (available label names)","Label values (for a specific label)","Metric results (from metric extraction queries)"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"grafana-mcp-server__cap_6","uri":"capability://data.processing.analysis.alert.rule.management.and.alert.state.querying","name":"alert rule management and alert state querying","description":"Provides tools to list alert rules configured in Grafana, retrieve alert rule definitions, query current alert states, and retrieve alert history. The server queries Grafana's alerting API (unified alerting) to expose alert rules, their conditions, and current firing status. This enables AI assistants to understand the alerting landscape and investigate active alerts without accessing the Grafana UI.","intents":["I want to see all active alerts and their current status","I need to understand the conditions and thresholds of a specific alert rule","I want to retrieve the history of a specific alert over a time range"],"best_for":["Incident response teams that need programmatic access to alert state","AI agents that need to correlate alerts with metrics and logs","Automation workflows that need to query alert status for decision-making"],"limitations":["Alert rule management (create/update/delete) is not supported — read-only access only","Alert history is limited by Grafana's retention policy — older alerts may not be available","Alert state is point-in-time — no streaming or real-time alert notifications through MCP","Alert rule conditions are returned as-is from Grafana — no normalization or simplification for AI consumption"],"requires":["Grafana instance with unified alerting enabled","API key with alert rule read permissions"],"input_types":["Alert rule ID or name (for retrieving specific rule)","Time range (for alert history queries)","Optional: filter by alert state (firing, resolved, etc.)"],"output_types":["Alert rule definitions (conditions, thresholds, notification channels)","Current alert instances (firing alerts with values)","Alert history (state changes over time)"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"grafana-mcp-server__cap_7","uri":"capability://data.processing.analysis.annotation.creation.and.retrieval.with.time.series.correlation","name":"annotation creation and retrieval with time-series correlation","description":"Provides tools to create annotations (events/markers) in Grafana dashboards and retrieve existing annotations within a time range. The server translates MCP tool parameters into Grafana annotation API calls, allowing AI assistants to mark significant events (deployments, incidents, etc.) on dashboards and retrieve annotations for correlation with metrics and logs. Annotations are stored in Grafana's annotation storage and can be visualized across dashboards.","intents":["I want to create an annotation marking a deployment event on a dashboard","I need to retrieve all annotations within a time range to correlate with metric anomalies","I want to add incident markers to dashboards for post-incident analysis"],"best_for":["Incident response workflows that need to mark events for correlation analysis","Automation that needs to record deployment or configuration change events","AI agents analyzing time-series data and needing to correlate with external events"],"limitations":["Annotation creation requires write permissions — read-only API keys cannot create annotations","Annotations are dashboard-specific or global — no cross-dashboard annotation queries","Annotation storage is limited by Grafana's retention policy — old annotations may be deleted","Annotation text is limited to plain text — no structured metadata or custom fields"],"requires":["Grafana instance with annotation storage enabled","API key with annotation write permissions (for creation) or read permissions (for retrieval)"],"input_types":["Annotation text (event description)","Timestamp (when the event occurred)","Optional: dashboard ID (for dashboard-specific annotations)","Optional: tags (for filtering annotations)"],"output_types":["Annotation ID (for created annotations)","Annotation list (with timestamps, text, and tags)","Annotation details (full annotation object)"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"grafana-mcp-server__cap_8","uri":"capability://data.processing.analysis.oncall.incident.management.and.escalation.policy.querying","name":"oncall incident management and escalation policy querying","description":"Provides tools to query Grafana OnCall incident management data, including on-call schedules, escalation policies, current incidents, and incident history. The server queries Grafana OnCall's API to expose incident state, on-call assignments, and escalation information. This enables AI assistants to understand incident context and on-call status without accessing the OnCall UI.","intents":["I want to see who is currently on-call for a specific service","I need to retrieve the current incident status and escalation chain","I want to understand the on-call schedule and escalation policies"],"best_for":["Incident response teams that need programmatic access to on-call information","AI agents that need to route incidents to the correct on-call engineer","Automation workflows that need to query on-call status for decision-making"],"limitations":["OnCall integration requires Grafana Cloud or self-hosted OnCall instance — not available in open-source Grafana","Incident creation/update is not supported — read-only access only","On-call schedule queries are point-in-time — no future schedule predictions","Escalation policy execution is managed by OnCall — MCP server cannot trigger escalations"],"requires":["Grafana Cloud or self-hosted OnCall instance","OnCall API key with read permissions","OnCall integration configured in Grafana"],"input_types":["Service or team ID (for on-call schedule queries)","Incident ID (for incident details)","Time range (for incident history)"],"output_types":["On-call schedule (current and upcoming assignments)","Escalation policies (escalation chain and timing)","Incident details (status, severity, assigned user)","Incident history (state changes and timeline)"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"grafana-mcp-server__cap_9","uri":"capability://tool.use.integration.multi.organization.and.multi.tenant.session.management","name":"multi-organization and multi-tenant session management","description":"Implements SessionManager pattern for HTTP-based transports (SSE, streamable-http) that allows per-request configuration of Grafana instance URL, API key, and organization context. The server maintains session state per HTTP request, enabling multi-tenant deployments where different clients connect to different Grafana instances or organizations. Session configuration is passed through MCP request headers or initialization parameters, allowing dynamic tenant switching without server restart.","intents":["I want to deploy a single MCP server that serves multiple Grafana instances or organizations","I need to route requests from different clients to different Grafana instances dynamically","I want to support per-request authentication without hardcoding credentials"],"best_for":["Multi-tenant SaaS platforms that need to serve multiple Grafana instances","Enterprise deployments with multiple Grafana organizations","Managed service providers offering Grafana access to multiple customers"],"limitations":["Session management is HTTP-only — stdio transport does not support multi-tenant configuration","Session state is per-request — no cross-request session persistence (stateless design)","Organization context is inherited from Grafana API key permissions — no additional RBAC enforcement at MCP layer","Session initialization overhead adds latency per request — not suitable for very high-frequency queries"],"requires":["HTTP-based transport (SSE or streamable-http)","Per-request session configuration (Grafana URL, API key, organization ID)","Grafana instances with API access for each tenant"],"input_types":["Session configuration (Grafana URL, API key, organization ID)","MCP tool invocation parameters"],"output_types":["MCP tool results scoped to the session's Grafana instance"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"grafana-mcp-server__headline","uri":"capability://tool.use.integration.mcp.server.for.grafana.observability","name":"mcp server for grafana observability","description":"The Grafana MCP Server is a specialized implementation of the Model Context Protocol that enables AI assistants to interact programmatically with Grafana for enhanced observability, allowing users to query data sources, manage dashboards, and access alerting features seamlessly.","intents":["best MCP server for Grafana","MCP server for observability tasks","how to integrate AI with Grafana","MCP framework for monitoring dashboards","Grafana tools for AI assistants"],"best_for":["AI integration with Grafana","observability solutions"],"limitations":[],"requires":[],"input_types":[],"output_types":[],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":60,"verified":false,"data_access_risk":"high","permissions":["Go 1.19+ (for server compilation)","Grafana instance with API access (any version with REST API support)","MCP-compatible client (Claude Desktop, or custom MCP client implementation)","Network connectivity from MCP server to Grafana instance","Grafana instance with at least one configured datasource","API key or service account token with datasource query permissions","Datasource-specific credentials already configured in Grafana (MCP server does not manage datasource auth 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