Measured 2026-08-19 on Windows 11: eleven popular MCP servers hold 178-422MB of RAM each (median 188MB), start in 0.5-1.9 seconds warm, and a concurrent five-server stack totals 961.6MB — confirmed by two independent measurement paths. Runtime floors: 52MB bare Node, 15MB bare Python. Published as open CC BY 4.0 CSV.
- Dataset ID
techfuelhq-mcp-server-bench- Version
- 1.0.0
- Rows
- 11
- Format
- CSV
- Published
- Page updated
By LK Wood IV · Published 2026-08-20 · ~3 min read · St. Louis County, MO
The short version #
I benchmarked eleven of the most-recommended MCP servers for what they cost to keep resident. The answer: 178-422MB of RAM each (median 188MB), ready in 0.5-1.9 seconds warm, with tool counts from 1 to 26. A realistic concurrent five-server stack totals 961.6MB, and two independent measurement paths confirmed that figure to the decimal. Tool count barely predicts weight. The runtime and framework dominate.
Download: mcp-server-bench-2026-08.csv. CC BY 4.0, per-iteration arrays included.
The measured table #
| Server | Version | Ready | RSS | Tools |
|---|---|---|---|---|
| GitHub (legacy npm) | 0.6.2 | 547ms | 178MB | 26 |
| Playwright | 1.63.0-alpha-2026-08-05 | 618ms | 227MB | 24 |
| Time (Python) | 1.29.0¹ | 619ms | 181MB | 2 |
| Sequential-thinking | 0.2.0 | 666ms | 186MB | 1 |
| Memory | 0.6.3 | 667ms | 187MB | 9 |
| Filesystem | 0.2.0 | 692ms | 188MB | 14 |
| Git (Python) | 1.29.0¹ | 699ms | 185MB | 12 |
| Fetch (Python) | 1.29.0¹ | 717ms | 220MB | 1 |
| Context7 | 4.0.2 | 815ms | 214MB | 2 |
| Desktop Commander | 0.2.47 | 1,705ms | 275MB | 26 |
| Qdrant (Python, 3.12 pin) | 1.29.0¹ | 1,881ms | 422MB | 2 |
¹ The four Python servers self-report 1.29.0 via serverInfo. That is a framework version string rather than each package’s own release number.
Controls on the same box: bare Node resident loop 52.1MB, bare Python loop 15.2MB. Five-server concurrent stack components: memory 189.8, filesystem 187.1, fetch 221.7, git 184.5, GitHub 178.5. Total: 961.6MB.
Method #
Each iteration spawns the server fresh (npx or uvx, warm package cache after one discarded warmup), completes the MCP initialize handshake over stdio, requests tools/list, then samples RSS across the full descendant process tree. I report medians of five iterations, three for the two servers benched later the same evening, marked in the CSV. The bench script lives in our repo at ops/bench/mcp/mcp_bench.py. For the decision layer, meaning which servers earn their memory and which to skip, read
the companion article. Known limitations, named: one Windows 11 machine, warm caches, stdio transport only, readiness and listing timed rather than per-tool-call latency under load. The GitHub entry is the legacy npm package; GitHub’s current first-party server ships as a Go binary and hosted remote. Version 1.0.0 of this dataset; changes will be logged in the update history above.
Frequently asked questions #
How much RAM does an MCP server use? #
How was the five-server stack measured? #
Why does the dataset sum the whole process tree? #
What are the measurement conditions? #
Sources and corrections #
- Last updated
- Methodology
- See our methodology for research and review standards.
- Update log
- 2026-08-20 — v1.0.0 first publication. 11 servers, 5 iterations each (3 for the two late additions, marked in the CSV), warm package cache, stdio JSON-RPC initialize + tools/list, RSS summed over the full descendant process tree. Five-stack total cross-checked psutil vs PowerShell WorkingSet64: 961.6MB exact agreement.
- Corrections
- Spotted an error or a stale number? Email contact@techfuelhq.com . Confirmed corrections are recorded here with the date and change.