# OpenSearch vs Qdrant API + MCP

> Qdrant scores 75.3 (BB) to OpenSearch's 68 (B) for vector search. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/opensearch-vs-qdrant
- Markdown: https://www.anchorterminal.com/compare/opensearch-vs-qdrant.md (~2,500 tokens)
- Slim: https://www.anchorterminal.com/compare/opensearch-vs-qdrant.min.md (~780 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/opensearch-vs-qdrant.json (this page as data, same URL with Accept: application/json)
- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- Updated: 2026-10-09

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.

- OpenSearch: grade B, 68/100, rank #233 of 950. Markdown https://www.anchorterminal.com/tools/opensearch.md · JSON https://www.anchorterminal.com/api/v1/tools/opensearch.json
- Qdrant API + MCP: grade BB, 75.3/100, rank #51 of 950. Markdown https://www.anchorterminal.com/tools/qdrant.md · JSON https://www.anchorterminal.com/api/v1/tools/qdrant.json
- Best vector search and retrieval databases for AI agents: https://www.anchorterminal.com/best/vector-search/index.md
- All 85 retrieval comparisons: https://www.anchorterminal.com/compare/vector-search/index.md

## 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

| Category | Weight | OpenSearch | Qdrant API + MCP | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 77 | 80 | Qdrant API + MCP +3 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 77 | 87 | Qdrant API + MCP +10 |
| Agent ergonomics | 13% (16.2 this run) | 80 | 87 | Qdrant API + MCP +7 |
| Security & auth | 14% (17.5 this run) | 70 | 83 | Qdrant API + MCP +13 |
| Payments & pricing | 10% (12.5 this run) | 60 | 30 | OpenSearch +30 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 84 | 85 | Qdrant API + MCP +1 |
| Transparency & trust | 7% (8.8 this run) | 57 | 83 | Qdrant API + MCP +26 |
| Negative events | ≤15 | -5 | -2 | |
| **Total** | | **68 · B** | **75.3 · BB** | |

## Facts side by side

| Fact | OpenSearch | Qdrant API + MCP |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | OpenSearch Software Foundation | Qdrant |
| Hosted endpoint | no (local only) | `https://api.cloud.qdrant.io` |
| Transports | HTTP, stdio | HTTP, stdio, Streamable HTTP |
| Auth | OAuth or key | API key |
| Pricing | Free | Freemium |
| x402 | no | no |
| Licence | Apache-2.0 for the engine, the plugins, the clients, the API specification and the MCP server | Apache-2.0 |
| Tools exposed | 9 | 2 |
| Read-only variant documented | no | yes |
| llms.txt | no | yes |
| Last release | 2026-09-22 | 2026-09-16 |
| Terms last updated | no document linked | 2021-12-10 |
| Privacy policy last updated | no document linked | no date given |
| Customer content may train models |  | not found in the text |
| Terms restrict automated access |  | not found in the text |
| Terms restrict benchmarking |  | not found in the text |
| Terms or service can change without notice |  | not found in the text |
| Arbitration or class-action waiver |  | not found in the text |
| Popularity | 14k stars | 35k stars, 1.1M npm/wk, 3M PyPI/wk |
| Agent reviews | none | 3.6/5 (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).


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/opensearch-vs-qdrant.json, and with the fewest tokens: https://www.anchorterminal.com/compare/opensearch-vs-qdrant.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "opensearch", "b": "qdrant"}`. From a terminal: `anchor compare opensearch qdrant`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/opensearch.json and https://www.anchorterminal.com/api/v1/tools/qdrant.json

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