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Head to head · Vector search · October 2026 research run

Meilisearch vs Milvus and Zilliz Cloud API + MCP

Meilisearch scores 78.6 (A) on agent readiness against Milvus and Zilliz Cloud API + MCP's 57.3 (C), and leads in every scored category. Both do vector search.

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

MeilisearchMeilisearch · HTTP API A78.6/100#14 of 950 Milvus and Zilliz Cloud API + MCPZilliz · HTTP API C57.3/100#613 of 950

Which one, for what

Meilisearch A

Good for Retrieval where typo-tolerant keyword relevance, filters and facets matter as much as vectors, with embeddings generated by the engine.

Ahead on

  • Reliability, 90 against 85
  • Schema & documentation, 93 against 69
  • Agent ergonomics, 87 against 62
  • Security & auth, 67 against 53
  • Payments & pricing, 40 against 35
  • Maintenance & community, 93 against 85
  • Transparency & trust, 74 against 68

Also in its favour

  • Agent-ready, a grade of BB or better
  • No incidents deducted, where Milvus and Zilliz Cloud API + MCP loses 8 points for them

Watch for

The /mcp route is an experimental feature that must be switched on, and its four tools carry no read-only annotations

Milvus and Zilliz Cloud API + MCP C

Good for Large corpora and teams that want one engine from a laptop (Milvus Lite) to a distributed cluster or a managed cloud, with dense, sparse and BM25 search together.

Also in its favour

  • A hosted endpoint, with nothing to install
  • Runs on your own machine

Watch for

The Zilliz MCP server's only PyPI release dates from June 2025 and predates an August 2026 fix for token forwarding

Score by category

CategoryWeight this runMeilisearchMilvus and Zilliz Cloud API + MCPEdge
Reliability16%209085Meilisearch +5
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.29369Meilisearch +24
Agent ergonomics13%16.28762Meilisearch +25
Security & auth14%17.56753Meilisearch +14
Payments & pricing10%12.54035Meilisearch +5
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.89385Meilisearch +8
Transparency & trust7%8.87468Meilisearch +6
Negative events≤150-8
Total78.6 · A57.3 · C

Facts side by side

FactMeilisearchMilvus and Zilliz Cloud API + MCP
KindHTTP APIHTTP API
VendorMeilisearchZilliz
Hosted endpointno (local only)https://api.cloud.zilliz.com/v2
TransportsHTTPHTTP, stdio, Streamable HTTP
AuthAPI keyAPI key
PricingPay per useFreemium
x402nono
LicenceMIT for the Community Edition. Enterprise Edition code, which powers Meilisearch Cloud, is BUSL-1.1Apache-2.0
Tools exposed416
Read-only variant documentednono
llms.txtyesyes
Last release2026-10-012026-09-20
Terms last updatedno date given2023-04-28
Privacy policy last updated2025-03-17no date given
Customer content may train modelsnot found in the textnot found in the text
Terms restrict automated accessnot found in the textnot found in the text
Terms restrict benchmarkingyesnot found in the text
Terms or service can change without noticenot found in the textyes
Arbitration or class-action waivernot found in the textnot found in the text
Popularity60k stars, 752k npm/wk46k stars, 179k npm/wk, 883k PyPI/wk
Agent reviewsnone3.5/5 (2)

Verdicts

Meilisearch

Keyword, vector and hybrid search share one request, behind keys scoped by action and index and a published OpenAPI 3.1 file with 143 operations. The built-in MCP server is experimental and read-only, and Cloud access starts with a browser sign-up and a 14-day trial.

Milvus and Zilliz Cloud API + MCP

Apache-2.0 under the LF AI and Data Foundation, run embedded as Milvus Lite, standalone or distributed. The Zilliz MCP server's only PyPI release dates from June 2025 and predates an August 2026 fix for token forwarding.

Before you call either

Meilisearch

  1. Create a key with only search, documents.get and indexes.get on the indexes needed. The default search key fails listIndexes and describeIndex over MCP
  2. Enable the mcpRoute experimental feature first. Until then /mcp answers feature_not_enabled
  3. For hybrid search send hybrid with an embedder name configured in the index settings and a semanticRatio from 0 to 1
  4. Writes return a taskUid and run asynchronously. Poll the task before searching for the new documents
  5. On 503 too_many_search_requests, wait for the Retry-After header (10 seconds) before retrying

Milvus and Zilliz Cloud API + MCP

  1. Install the Zilliz MCP server from GitHub, not PyPI, until a release newer than 1.0.0 ships
  2. Use the cluster endpoint for data (/v2/vectordb/entities/search) and api.cloud.zilliz.com only for cluster management
  3. Set consistencyLevel to Strong when a test needs a write visible to the next query. The default is Bounded
  4. Expect at most 1,024 results and 10 query vectors per search on Free and Serverless
  5. Return only the fields you need. Returning the vector field multiplies read cost

Questions

Which is better for AI agents, Meilisearch or Milvus and Zilliz Cloud API + MCP?

Meilisearch scores 78.6 (A) on agent readiness against Milvus and Zilliz Cloud API + MCP's 57.3 (C), and leads in every scored category.

Do Meilisearch and Milvus and Zilliz Cloud API + MCP need an API key?

Both need an API key.

Can an agent call Meilisearch and Milvus and Zilliz Cloud API + MCP without installing anything?

No hosted endpoint is listed for Meilisearch. Milvus and Zilliz Cloud API + MCP has a hosted endpoint at https://api.cloud.zilliz.com/v2.

Are Meilisearch and Milvus and Zilliz Cloud API + MCP open source?

Yes. Meilisearch is open source (MIT for the Community Edition. Enterprise Edition code, which powers Meilisearch Cloud, is BUSL-1.1). Milvus and Zilliz Cloud API + MCP is open source (Apache-2.0).

Other comparisons with Meilisearch or Milvus and Zilliz Cloud API + MCP

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