Grafana MCP vs Qdrant MCP Server

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

	Grafana MCP MCP Servers	Qdrant MCP Server MCP Servers
Tagline	Official Grafana Labs MCP server — dashboards, Prometheus, Loki, alerts and incidents in your LLM client	Official Qdrant MCP server that turns a vector database into a semantic memory layer for Claude, Cursor, Windsurf, and any MCP client.
Category	MCP Servers	MCP Servers
Pricing	Free· Free and open source (Apache 2.0). You still need a Grafana instance — OSS Grafana is free; Grafana Cloud has a free tier plus paid Pro/Advanced/Enterprise plans.	Free· Free and open source (Apache-2.0). Qdrant itself can be self-hosted for free or used via Qdrant Cloud (free tier available, paid plans from ~$25/mo for managed clusters).
Model	—	FastEmbed (default: sentence-transformers/all-MiniLM-L6-v2); pairs with any MCP-capable LLM such as Claude 3.5/4, GPT-4o, or local models
Editorial score	—	—
Use cases	Incident investigation from Claude DesktopConversational PromQL and LogQL queryingDashboard search and summarisationPanel screenshot analysis by vision LLMsAlert rule and notification policy reviewOn-call schedule lookupsSift automated error-pattern triageCursor / VS Code observability copilotMulti-tenant SSE server for internal agentsGrafana Incident timeline updates from an agent	Persistent memory for Claude Desktop agentsSemantic code snippet search in Cursor and WindsurfPrivate documentation retrieval for internal LLM copilotsTeam knowledge base backed by Qdrant CloudLocal offline vector memory via QDRANT_LOCAL_PATHRead-only knowledge lookup skill for customer-support agentsCross-session context store for autonomous coding agents
Pros	Official Grafana Labs project, actively developed with 3k+ GitHub stars and Apache-2.0 licensing Broad coverage: dashboards, alerts, incidents, on-call, Sift, annotations, snapshots, plus native query support for Prometheus, Loki, and eight SQL/timeseries backends Panel PNG rendering lets vision-capable LLMs actually see charts, not just JSON Three transports (stdio, SSE, Streamable HTTP) cover single-user desktop and multi-client server deployments Per-tool enable list and --disable-write flag make it safe to hand to autonomous agents against production Grafana Works out of the box with Claude Desktop, Cursor, VS Code and any MCP-spec client via uvx or Docker	Official, actively maintained by the Qdrant team with 1.4k+ stars and frequent releases Two-tool surface (store/find) is small enough that models actually use it correctly Bundled FastEmbed means no separate OpenAI/Cohere embedding key is required to get started Configurable tool descriptions let you rebrand the same server as memory, code search, or docs lookup Works across the major MCP clients: Claude Desktop, Cursor, Windsurf, VS Code, and custom agents Apache-2.0 with local, Docker, and uvx install paths including a fully offline QDRANT_LOCAL_PATH mode Read-only mode makes it safe to expose a curated knowledge base without letting the model write to it
Cons	Requires Grafana 9.0+ and a service account token — no value without an existing Grafana deployment Many powerful tools are disabled by default and must be explicitly enabled, which is safer but adds config friction Broad tool surface can flood a model's context window; you often need to curate which tools are exposed per assistant PromQL/LogQL/SQL responses are raw datasource output — the LLM still has to reason about large result sets, which burns tokens fast Not a hosted service: you run and secure the process yourself, and network reachability to Grafana is your problem	Only FastEmbed is supported today, so you cannot plug in OpenAI, Cohere, or Voyage embeddings without forking Just two tools: no filtering, hybrid search, payload updates, or collection management surfaced to the model Single active collection per server process; multi-collection agents need multiple server instances or wrapping Assumes you already run and secure a Qdrant instance (self-hosted or Cloud) — not a turnkey managed product Chunking, ingestion pipelines, and re-ranking are entirely your problem; this is a thin bridge, not a RAG framework
Website	github.com	github.com

Pick Grafana MCP if

✅ Official Grafana Labs project, actively developed with 3k+ GitHub stars and Apache-2.0 licensing
✅ Broad coverage: dashboards, alerts, incidents, on-call, Sift, annotations, snapshots, plus native query support for Prometheus, Loki, and eight SQL/timeseries backends
✅ Panel PNG rendering lets vision-capable LLMs actually see charts, not just JSON
✅ Three transports (stdio, SSE, Streamable HTTP) cover single-user desktop and multi-client server deployments

Pick Qdrant MCP Server if

✅ Official, actively maintained by the Qdrant team with 1.4k+ stars and frequent releases
✅ Two-tool surface (store/find) is small enough that models actually use it correctly
✅ Bundled FastEmbed means no separate OpenAI/Cohere embedding key is required to get started
✅ Configurable tool descriptions let you rebrand the same server as memory, code search, or docs lookup

Compare a different pair →