chohyerinn/filter-mcp-server

Overview

A collection of MCP servers that implement approximate membership filters including Bloom, Counting Bloom, Cuckoo, and SuRF. Each server exposes a standardized interface for comparing the performance and accuracy of these probabilistic data structures.

Best for

Best for
Developers researching or comparing approximate membership filters for data-intensive applications

Use cases

• Benchmarking filter accuracy and memory tradeoffs
• Integrating probabilistic membership checks into MCP-based workflows
• Evaluating filter suitability for large-scale deduplication or set membership tasks

Notes

A collection of MCP servers that implement approximate membership filters including Bloom, Counting Bloom, Cuckoo, and SuRF. Each server exposes a standardized interface for comparing the performance and accuracy of these probabilistic data structures.

0 stars on GitHub. Last updated 2026-06-20. Licensed MIT.

Use cases

• Benchmarking filter accuracy and memory tradeoffs
• Integrating probabilistic membership checks into MCP-based workflows
• Evaluating filter suitability for large-scale deduplication or set membership tasks

Pros

• Provides multiple filter types in a unified MCP interface
• Useful for empirical comparison without manual implementation
• Lightweight Python codebase easy to extend or modify

Cons

• Zero community adoption or stars suggests limited validation
• No documentation beyond the repository description
• Requires MCP runtime environment to operate

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.