Chroma MCP vs Qdrant MCP Server

Chroma MCP

MCP Servers

Qdrant MCP Server

MCP Servers

Tagline

Chroma MCP

Official MCP server that gives LLM clients direct access to the Chroma vector database.

Qdrant MCP Server

Official Qdrant MCP server that acts as a semantic memory layer for keeping and retrieving memories in the Qdrant vector search engine.

Pricing

Chroma MCP

Free· Open source (Apache 2.0). Free to run locally or self-hosted; embedding-function API keys (OpenAI, Cohere, Jina, VoyageAI, Roboflow) billed by those providers. Chroma Cloud pricing set separately by Chroma.

Qdrant MCP Server

Free

API

Chroma MCP

Yes

Qdrant MCP Server

Yes

Open source

Chroma MCP

Yes · Apache-2.0

Qdrant MCP Server

Yes · Apache-2.0

GitHub stars

Chroma MCP

600

checked 2026-10-29

Qdrant MCP Server

1,559

checked 2026-10-29

Last GitHub push

Chroma MCP

2025-09-17

Qdrant MCP Server

2026-09-04

First commit

Chroma MCP

2025-02

Qdrant MCP Server

2024-12

Model used

Chroma MCP

—

Qdrant MCP Server

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

Best for

Chroma MCP

Developers who already use Chroma (or want to) and need to give Claude Desktop, Cursor, or another MCP client durable vector memory or a searchable knowledge base with minimal glue code.

Qdrant MCP Server

—

Not for

Chroma MCP

Teams needing hosted, multi-tenant vector search with auth and quotas out of the box, or anyone who wants an opinionated end-to-end RAG framework rather than a database bridge.

Qdrant MCP Server

—

Editorial score

Chroma MCP

—

Qdrant MCP Server

—

Use cases

Chroma MCP

Long-term memory for Claude DesktopTeam knowledge base shared across agentsRAG over local documentsSemantic code search in Cursor or ContinueVector store for custom MCP agentsPersonal notes and journal recallMetadata-filtered document retrievalChroma Cloud access from LLM clients

Qdrant MCP Server

Keeping and retrieving memories in a vector search engine.Semantic code snippet search in Cursor and Windsurf.Semantic search over an existing codebase in Claude Code.Automatic collection creation for new data stores.

Pros

Chroma MCP

• Official server from the Chroma team, tracks the database's features closely
• Four deployment modes (ephemeral, persistent, HTTP, Chroma Cloud) from one binary
• Twelve well-scoped MCP tools cover the full collection and document lifecycle
• Supports six embedding functions including OpenAI, Cohere, Jina, and VoyageAI with per-collection persistence
• Zero-config install via uvx - drops into Claude Desktop or Cursor in a couple of JSON lines
• Apache 2.0 licensed and readable Python source; easy to fork or extend
• Query tools expose HNSW tuning and metadata/full-text filters, not just naive semantic search

Qdrant MCP Server

• Official implementation from the Qdrant team.
• Compatible with any MCP-compatible client.
• Supports local Qdrant database paths for offline or local development.
• Includes a read-only mode that disables the store tool.

Cons

Chroma MCP

• You still have to run and back up the Chroma store yourself unless you pay for Chroma Cloud
• Command-line API key arguments are convenient but leak into process lists; env/.env path is safer but extra setup
• No built-in access control or multi-tenant isolation - anything the MCP client sees, it can delete
• Embedding-function persistence only works for collections created on Chroma v1.0.0+; older stores need migration
• Python-only server; teams on pure Node stacks add a runtime dependency
• MCP tool surface is CRUD-shaped - no higher-level RAG primitives like chunking, re-ranking, or hybrid fusion

Qdrant MCP Server

• Only FastEmbed models are currently supported for embeddings.
• Users cannot provide both a remote Qdrant URL and a local path simultaneously.

Website

Chroma MCP

github.com

Qdrant MCP Server

github.com

Editorial score: rule-based, 0–10, from AI-assisted profile inputs (see /methodology) — not a user rating; “—” means unscored. “Not listed” means we have no record of it, not that it is absent. GitHub figures and prices carry the date they were checked or captured; prices are shown as published, unconverted.