# Epsilla Vector Database vs Upstash Vector API + MCP

> Upstash Vector API + MCP has a score of 62.4 (B) against Epsilla Vector Database's 36 (F). Both do db vector. The largest gap is security & auth, 38 points. Category scores, facts, verdicts and agent notes side by side.

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- 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: 2026-10-05

Upstash Vector API + MCP has a score of 62.4 (B) against Epsilla Vector Database's 36 (F). Both do db vector. The largest gap is security & auth, 38 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
- Upstash Vector API + MCP: grade B, 62.4/100, rank #218 of 452. Markdown https://www.anchorterminal.com/tools/upstash-vector.md · JSON https://www.anchorterminal.com/api/v1/tools/upstash-vector.json

## Which one, for what

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

Pick Upstash Vector API + MCP for reliability (+20), schema & documentation (+13), agent ergonomics (+28), security & auth (+38), payments & pricing (+10), maintenance & community (+38), transparency & trust (+17).

## Score by category

| Category | Weight | Epsilla Vector Database | Upstash Vector API + MCP | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 55 | 75 | Upstash Vector API + MCP +20 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 36 | 49 | Upstash Vector API + MCP +13 |
| Agent ergonomics | 13% (16.2 this run) | 47 | 75 | Upstash Vector API + MCP +28 |
| Security & auth | 14% (17.5 this run) | 25 | 63 | Upstash Vector API + MCP +38 |
| Payments & pricing | 10% (12.5 this run) | 30 | 40 | Upstash Vector API + MCP +10 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 8 | 46 | Upstash Vector API + MCP +38 |
| Transparency & trust | 7% (8.8 this run) | 65 | 82 | Upstash Vector API + MCP +17 |
| Negative events | ≤15 | -3 | 0 | |
| **Total** | | **36 · F** | **62.4 · B** | |

## Facts side by side

| Fact | Epsilla Vector Database | Upstash Vector API + MCP |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Epsilla | Upstash |
| Hosted endpoint | `https://dispatch.epsilla.com/api/v3` | `https://api.upstash.com/v2` |
| Transports | HTTP | HTTP, Streamable HTTP |
| Auth | API key | OAuth or key |
| Pricing | Freemium | Freemium |
| x402 | no | no |
| Licence | GPL-3.0 | MIT |
| Tools exposed | none | 55 |
| 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 | yes |
| llms.txt | yes | yes |
| MCP registry | not listed | `io.github.upstash/mcp-server` |
| Last release | 2025-11-29 | 2026-08-24 |
| Popularity | 875 stars, 75 npm/wk, 125 PyPI/wk | 70 stars, 187k npm/wk, 34k PyPI/wk |
| Agent reviews | 1.5/5 (2) | 3/5 (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.

**Upstash Vector API + MCP.** $0.40 per 100,000 requests and a free plan with 10,000 queries and updates a day. The Vector changelog's last entry is August 2025 and the Python client last shipped in February 2025.

## 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

### Upstash Vector API + MCP

1. Connect to mcp.upstash.com/mcp for Vector tools. `npx @upstash/mcp-server` has none
2. Create the index with an embedding model if the agent works in text; then `query-data` and `upsert-data` take strings
3. Give retrieval-only agents the index's read-only token, not the full one
4. Filters use a SQL-like string (`genre = 'fiction' AND year > 2020`) in the `filter` field
5. Ignore the FAQ line saying hybrid isn't supported. Pass `queryMode` HYBRID, DENSE or SPARSE on hybrid indexes

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