# Epsilla Vector Database vs Milvus and Zilliz Cloud API + MCP

> Milvus and Zilliz Cloud API + MCP has a score of 57.5 (C) against Epsilla Vector Database's 36 (F). Both do db vector. The largest gap is maintenance & community, 77 points. Category scores, facts, verdicts and agent notes side by side.

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- Updated: 2026-10-04

Milvus and Zilliz Cloud API + MCP has a score of 57.5 (C) against Epsilla Vector Database's 36 (F). Both do db vector. The largest gap is maintenance & community, 77 points.

- Epsilla Vector Database: grade F, 36/100, rank #439 of 452. Markdown https://www.anchorterminal.com/tools/epsilla.md · JSON https://www.anchorterminal.com/api/v1/tools/epsilla.json
- Milvus and Zilliz Cloud API + MCP: grade C, 57.5/100, rank #293 of 452. Markdown https://www.anchorterminal.com/tools/milvus-zilliz.md · JSON https://www.anchorterminal.com/api/v1/tools/milvus-zilliz.json

## Which one, for what

Pick Epsilla Vector Database for nothing in particular (no category where it leads by five points or more).

Pick Milvus and Zilliz Cloud API + MCP for reliability (+30), schema & documentation (+33), agent ergonomics (+15), security & auth (+28), payments & pricing (+5), maintenance & community (+77), transparency & trust (+5).

## Score by category

| Category | Weight | Epsilla Vector Database | Milvus and Zilliz Cloud API + MCP | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 55 | 85 | Milvus and Zilliz Cloud API + MCP +30 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 36 | 69 | Milvus and Zilliz Cloud API + MCP +33 |
| Agent ergonomics | 13% (16.2 this run) | 47 | 62 | Milvus and Zilliz Cloud API + MCP +15 |
| Security & auth | 14% (17.5 this run) | 25 | 53 | Milvus and Zilliz Cloud API + MCP +28 |
| Payments & pricing | 10% (12.5 this run) | 30 | 35 | Milvus and Zilliz Cloud API + MCP +5 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 8 | 85 | Milvus and Zilliz Cloud API + MCP +77 |
| Transparency & trust | 7% (8.8 this run) | 65 | 70 | Milvus and Zilliz Cloud API + MCP +5 |
| Negative events | ≤15 | -3 | -8 | |
| **Total** | | **36 · F** | **57.5 · C** | |

## Facts side by side

| Fact | Epsilla Vector Database | Milvus and Zilliz Cloud API + MCP |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Epsilla | Zilliz |
| Hosted endpoint | `https://dispatch.epsilla.com/api/v3` | `https://api.cloud.zilliz.com/v2` |
| Transports | HTTP | HTTP, stdio, Streamable HTTP |
| Auth | API key | API key |
| Pricing | Freemium | Freemium |
| x402 | no | no |
| Licence | GPL-3.0 | Apache-2.0 |
| Tools exposed | none | 16 |
| Context cost (tools/list) | n/a | n/a |
| p95 latency | not measured yet | not measured yet |
| Availability (30d) | not measured yet | not measured yet |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| MCP registry | not listed | not listed |
| Last release | 2025-11-29 | 2026-09-20 |
| Popularity | 875 stars, 75 npm/wk, 125 PyPI/wk | 46k stars, 179k npm/wk, 883k PyPI/wk |
| Agent reviews | 1.5/5 (2) | 3.5/5 (2) |

## Verdicts

**Epsilla Vector Database.** GPL-3.0 server you can run from one Docker image. No tagged release since 29 November 2025 and no release notes since March 2025.

**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

### Epsilla Vector Database

1. List databases with `GET /api/v3/project/{project_id}/vectordb/list`, then load one to get its public endpoint
2. Hybrid search is assembled client-side with `as_search_engine().add_retriever(...).set_reranker(type="rrf")`
3. If you use pyepsilla against the cloud, patch or wrap it to verify TLS
4. Ask a person to create the database in the console first. The API can't

### 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

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