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| try { | ||
| // Get current count | ||
| const value = await kv.get(key); | ||
| const currentCount = value ? parseInt(value, 10) : 0; | ||
| const newCount = currentCount + 1; | ||
|
|
||
| // Store with TTL and metadata | ||
| await kv.put( | ||
| key, |
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Use atomic counter for KV-based rate limiter
The new rate limiting logic increments the request count by performing a kv.get followed by a kv.put with the incremented value. Cloudflare KV does not guarantee atomicity for this read–modify–write pattern, so when multiple requests from the same IP arrive concurrently they can all read the same count and overwrite each other’s updates. In practice the counter can remain at 1 even after dozens of parallel requests, allowing attackers to bypass the limit and continue creating Durable Objects. Consider using kv.atomic() or moving the counter into a Durable Object to ensure increments are serialized.
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This PR implements three critical production features for the 10x Rules MCP Server:
These changes make the MCP server production-ready, prevent abuse, reduce costs, and follow industry best practices.
Problem Statement
The MCP server was missing essential production features:
1. No Health Check Endpoint
2. No Request Validation
Acceptheader3. No Rate Limiting
4. Discovery: Per-Session Rate Limiting Issue
During initial implementation, we discovered that DO-level rate limiting:
Solution
Architecture: Worker-Level Rate Limiting
We implemented a two-phase approach, ultimately landing on global IP-based rate limiting at the Worker level:
Key Decision: Rate limiting BEFORE DO routing prevents abuse and cost overruns.