I measured what 14 MCP servers cost a context window. Claude counts them 64% higher than tiktoken
A developer measured how 14 MCP servers impact context window usage, finding Claude counts them 64% higher than tiktoken.
- Claude’s tokenizer reports MCP server costs 64% higher than tiktoken in context window usage.
- The discrepancy was measured across 72 trials involving 14 MCP servers.
- The findings highlight potential inefficiencies in tokenization or overhead tracking for MCP-based applications.
- Developers may need to adjust their token usage estimates when using MCP servers with Claude.
A developer conducted 72 trials to quantify the cost of 14 MCP servers in terms of context window usage. The results show a significant discrepancy between how Claude and tiktoken measure this overhead. Specifically, Claude’s tokenizer counts the MCP server calls 64% higher than tiktoken, suggesting potential inefficiencies in tokenization or overhead tracking.
The experiment was motivated by a maintainer’s refusal to provide a definitive answer on MCP server costs, prompting the developer to run their own tests. The findings could have implications for developers building MCP-based applications, particularly those concerned with optimizing token usage and managing costs in large-scale deployments.
While the study focuses on a niche but growing area of AI tooling, it underscores the importance of accurate tokenization benchmarks in AI development workflows.
Developers using MCP servers with Claude must account for higher token costs than previously estimated.
Benchmarking tools like tiktoken and Claude’s tokenizer may yield inconsistent results for MCP server overhead.
- MCP servers
- Model Context Protocol servers that provide tools or functions to AI models during execution.
- Context window
- The maximum amount of text an AI model can process at once, measured in tokens.
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