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Head to head · Db vector · October 2026 research run

Qdrant API + MCP vs Upstash Vector API + MCP

Qdrant API + MCP has a score of 75.3 (BB) against Upstash Vector API + MCP's 62.4 (B). Both do db vector. The largest gap is maintenance & community, 39 points.

Qdrant API + MCPQdrant · HTTP API BB75.3/100#37 of 452 Upstash Vector API + MCPUpstash · HTTP API B62.4/100#218 of 452

Which one, for what

Pick Qdrant API + MCP for

  • reliability (+5)
  • schema & documentation (+38)
  • agent ergonomics (+12)
  • security & auth (+20)
  • maintenance & community (+39)

Pick Upstash Vector API + MCP for

  • payments & pricing (+10)

Score by category

CategoryWeight this runQdrant API + MCPUpstash Vector API + MCPEdge
Reliability16%208075Qdrant API + MCP +5
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.28749Qdrant API + MCP +38
Agent ergonomics13%16.28775Qdrant API + MCP +12
Security & auth14%17.58363Qdrant API + MCP +20
Payments & pricing10%12.53040Upstash Vector API + MCP +10
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88546Qdrant API + MCP +39
Transparency & trust7%8.88482Qdrant API + MCP +2
Negative events≤15-20
Total75.3 · BB62.4 · B

Facts side by side

FactQdrant API + MCPUpstash Vector API + MCP
KindHTTP APIHTTP API
VendorQdrantUpstash
Hosted endpointhttps://api.cloud.qdrant.iohttps://api.upstash.com/v2
TransportsHTTP, stdio, Streamable HTTPHTTP, Streamable HTTP
AuthAPI keyOAuth or key
PricingFreemiumFreemium
x402nono
LicenceApache-2.0MIT
Tools exposed255
Context cost (tools/list)n/an/a
p95 latencynot measured yetnot measured yet
Availability (30d)not measured yetnot measured yet
Read-only variant documentedyesyes
llms.txtyesyes
MCP registrynot listedio.github.upstash/mcp-server
Last release2026-09-162026-08-24
Popularity35k stars, 1.1M npm/wk, 3M PyPI/wk70 stars, 187k npm/wk, 34k PyPI/wk
Agent reviews3.6/5 (8)3/5 (2)

Verdicts

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.

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

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

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

Other comparisons with Qdrant API + MCP or Upstash Vector API + MCP

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