Quick answer

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.

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

ServerVersionReadyRSSTools
GitHub (legacy npm)0.6.2547ms178MB26
Playwright1.63.0-alpha-2026-08-05618ms227MB24
Time (Python)1.29.0¹619ms181MB2
Sequential-thinking0.2.0666ms186MB1
Memory0.6.3667ms187MB9
Filesystem0.2.0692ms188MB14
Git (Python)1.29.0¹699ms185MB12
Fetch (Python)1.29.0¹717ms220MB1
Context74.0.2815ms214MB2
Desktop Commander0.2.471,705ms275MB26
Qdrant (Python, 3.12 pin)1.29.0¹1,881ms422MB2

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?
In this dataset, 178-422MB resident per server with a median of 188MB, measured across 11 popular servers on Windows 11 with warm package caches. The floor is the runtime rather than the server code: a bare Node process idles at 52MB and bare Python at 15MB on the same machine.
How was the five-server stack measured?
Five servers (memory, filesystem, fetch, git, GitHub) were spawned concurrently, initialized over stdio JSON-RPC, and their full process trees summed: 961.6MB by psutil, and an independent PowerShell WorkingSet64 walk over the same trees returned 961.6MB — exact agreement between two measurement paths. All five were ready in 803ms.
Why does the dataset sum the whole process tree?
Because npx and uvx are launchers: the parent process holds almost nothing while a child holds the real footprint. Measured directly, the npx parent alone reports 10.3MB while its full tree holds 189.3MB — an 18x undercount. Every RSS figure in the CSV is the descendant-tree sum, sampled 0.4 seconds after tools/list returned.
What are the measurement conditions?
Fresh process per iteration, five iterations per server (three for the two late additions, marked in the CSV’s iterations column), one discarded warmup spawn so npm and uv caches are warm, MCP protocol 2024-11-05 over stdio, and medians reported. Single Windows 11 machine — Linux numbers will differ, likely with a lower Node floor.

Evidence ledger

Last updated
Methodology
This guide was written and edited by Lowell K. Wood IV in St. Louis County, MO. Specs and prices verified against vendor and project documentation current on the date above. Full editorial standard: methodology.
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 hello@techfuelhq.com. Confirmed corrections are added to the update log above.

About the author

Written by Lowell K. Wood IV, who builds and runs TechFuelHQ from St. Louis, Missouri.