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YedanYagami
YedanYagami

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real costs of running 9 MCP servers for 30 days: $0.00

everyone asks the same question when i show them the system: "yeah but how much does it cost?"

here's the honest answer after 30 days of running 9 MCP servers, 60+ cloudflare workers, 2 databases, a knowledge graph, and a local GPU inference stack.

total monthly cost: $11.

not $11 for the MCP servers. those are free. the $11 is for the VM that runs ollama. let me break it down.


the $0 tier: cloudflare workers

all 9 MCP servers run on cloudflare workers free tier. every single one. no credit card required.

here's what free tier gives you:

resource free limit my actual usage
requests/day 100,000 ~2,000-5,000
CPU time/invocation 10ms 2-8ms avg
workers unlimited 60+ deployed
KV reads/day 100,000 ~500
KV storage 1 GB ~12 MB

i'm using roughly 3-5% of the free tier limits on a busy day. the 10ms CPU limit sounds scary until you realize most tool operations finish in 2-3ms. the constraint forces you to write efficient code, which is a feature not a bug.


the $0 tier: D1 databases

i run 2 D1 databases on free tier. D1 is sqlite at the edge. i store 4,300+ knowledge graph entities, full audit trails, and A/B experiment results. all on free tier.

resource free limit my usage
storage 5 GB per database ~400 MB total
reads/day 5,000,000 ~10,000
writes/day 100,000 ~1,000

the $0 tier: LLM inference

this is the part that makes people do a double-take. three free LLM API providers with multi-provider routing:

provider model free tier rate limit
groq llama-3.3-70b unlimited* 30 req/min
cerebras llama-3.3-70b unlimited* 30 req/min
sambanova llama-3.3-70b unlimited* varies

the trick: when groq rate-limits me, requests cascade to cerebras, then sambanova. circuit breaker pattern (3 failures = 1 min cooldown) means the system self-heals.

is this sustainable? honestly, probably not forever. but llama-3.3-70b inference is heading toward $0.05-0.10 per million tokens.


the $11/month: the VM

oracle cloud VM with RTX 3060. runs ollama (7 local models), 3 AI brains, 48 skills. flash attention, KV cache, 24/7.

could i skip it? yes. the VM is a luxury, not a necessity.


the real cost breakdown (30 days)

item monthly cost
9 MCP servers (cloudflare workers) $0.00
50+ additional workers $0.00
2 D1 databases $0.00
R2 + KV storage $0.00
groq + cerebras + sambanova APIs $0.00
domain + SSL $0.00
oracle cloud VM (RTX 3060) $11.00
total $11.00

honest limitations

  • no cron triggers on free tier (workaround: systemd timer on VM)
  • 10ms CPU tight for heavy computation
  • no websocket without durable objects (SSE works fine for MCP)
  • D1 sqlite write contention at ~100 writes/sec
  • free LLM APIs have no SLA
  • workers AI free = ~100 small inference calls/day

the punchline

the model is becoming a commodity. infrastructure is becoming a commodity. the real cost is your time.

$11/month for 9 MCP servers, 60+ workers, 2 databases, a GPU inference box, and edge deployment across 300+ cities.

the expensive part was never the servers. it was always figuring out what to build.

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