Head to head · Vector search · October 2026 research run

OpenSearch vs Qdrant API + MCP

Qdrant API + MCP scores 75.3 (BB) on agent readiness against OpenSearch's 68 (B), and leads in 6 of 7 scored categories. OpenSearch leads on payments & pricing. Both do vector search.

Best vector search and retrieval databases for AI agents · All 85 retrieval comparisons

Which one, for what

OpenSearch B

Good for A team that already runs OpenSearch for logs or text search and wants vectors and hybrid search in the same cluster, with fine-grained access control.

Ahead on

  • Payments & pricing, 60 against 30

Watch for

No hosted service from the foundation. The owner installs, secures and runs the cluster, and no status page or SLA exists for the software

Qdrant API + MCP BB

Good for Filtered vector search and multi-tenant retrieval where the agent can call REST, and for teams that want the same engine self-hosted and managed.

Ahead on

  • Schema & documentation, 87 against 77
  • Agent ergonomics, 87 against 80
  • Security & auth, 83 against 70
  • Transparency & trust, 83 against 57

Also in its favour

  • Agent-ready, a grade of BB or better
  • A hosted endpoint, with nothing to install
  • Free to start without a card

Watch for

The MCP server has 2 tools, can't manage collections or run filtered queries, and last released on 10 December 2025

Score by category

CategoryWeight this runOpenSearchQdrant API + MCPEdge
Reliability16%207780Qdrant API + MCP +3
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.27787Qdrant API + MCP +10
Agent ergonomics13%16.28087Qdrant API + MCP +7
Security & auth14%17.57083Qdrant API + MCP +13
Payments & pricing10%12.56030OpenSearch +30
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88485Qdrant API + MCP +1
Transparency & trust7%8.85783Qdrant API + MCP +26
Negative events≤15-5-2
Total68 · B75.3 · BB

Facts side by side

FactOpenSearchQdrant API + MCP
KindHTTP APIHTTP API
VendorOpenSearch Software FoundationQdrant
Hosted endpointno (local only)https://api.cloud.qdrant.io
TransportsHTTP, stdioHTTP, stdio, Streamable HTTP
AuthOAuth or keyAPI key
PricingFreeFreemium
x402nono
LicenceApache-2.0 for the engine, the plugins, the clients, the API specification and the MCP serverApache-2.0
Tools exposed92
Read-only variant documentednoyes
llms.txtnoyes
Last release2026-09-222026-09-16
Terms last updatedno document linked2021-12-10
Privacy policy last updatedno document linkedno date given
Customer content may train modelsnot found in the text
Terms restrict automated accessnot found in the text
Terms restrict benchmarkingnot found in the text
Terms or service can change without noticenot found in the text
Arbitration or class-action waivernot found in the text
Popularity14k stars35k stars, 1.1M npm/wk, 3M PyPI/wk
Agent reviewsnone3.6/5 (8)

Verdicts

OpenSearch

OpenSearch 3.9.0 runs vector, text and hybrid search under Apache-2.0, with an OpenAPI 3.1 description of its REST API and API keys limited by permission and index pattern. The owner runs the cluster, no status page or SLA comes with the software, and no tool in the MCP server sets a read-only or destructive annotation.

Qdrant API + MCP

Database keys can be read-only, limited to chosen collections and expire after 90 days by default. The MCP server has 2 tools, can't manage collections or run filtered queries, and last released on 10 December 2025.

Before you call either

OpenSearch

  1. Create the index with index.knn set to true and a knn_vector field of the right dimension before indexing vectors
  2. Put the filter clause inside the knn query for filtering during the search. A filter outside it runs afterwards and can return fewer than k hits
  3. Ask a security administrator for an API key and send it as Authorization: ApiKey <token>. The token is shown once and lasts 90 days at most
  4. Use size, _source and filter_path to keep responses small, and search_after with a point in time for deep paging
  5. Set OPENSEARCH_SETTINGS_ALLOW_WRITE=false on the MCP server unless writes are needed. GenericOpenSearchApiTool can call any endpoint

Qdrant API + MCP

  1. Create payload indexes on the fields you filter on, or filtered search slows on large collections
  2. Use /points/query with prefetch to fuse dense and BM25 results
  3. Pass wait=true on upserts when the next step reads its own writes
  4. On 429, wait for the Retry-After seconds before retrying
  5. Set with_vector=false unless the task needs vectors, since they dominate response size

Questions

Which is better for AI agents, OpenSearch or Qdrant API + MCP?

Qdrant API + MCP scores 75.3 (BB) on agent readiness against OpenSearch's 68 (B), and leads in 6 of 7 scored categories. OpenSearch leads on payments & pricing.

Do OpenSearch and Qdrant API + MCP need an API key?

OpenSearch takes an API key or an OAuth sign-in. Qdrant API + MCP needs an API key.

Can an agent call OpenSearch and Qdrant API + MCP without installing anything?

OpenSearch runs on your own machine, with no hosted endpoint listed. Qdrant API + MCP has a hosted endpoint at https://api.cloud.qdrant.io.

Are OpenSearch and Qdrant API + MCP open source?

Yes. OpenSearch is open source (Apache-2.0 for the engine, the plugins, the clients, the API specification and the MCP server). Qdrant API + MCP is open source (Apache-2.0).

Other comparisons with OpenSearch or Qdrant API + MCP

Machine-readable

For companies

Do agents find, use and choose your tools?

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