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io.github.robinlidberg-dot/cap-shield

Official

by robinlidberg-dot · Python

Context selection and compression for AI agents - recall measured, not claimed.

cap-shield MCP Server

This MCP server provides context selection and compression for AI agents. It emphasizes “recall measured, not claimed,” and is designed to reduce agent context while aiming to keep sufficient information. It is distributed as a single file with no dependencies and no SDK required.

🛠️ Key Features

  • Context selection for AI agents
  • Compression and decompression
  • Recall measured (per documentation phrasing)
  • Zero-dependency, one-file setup
  • Topics include MCP tools and vector-search engine approaches

🚀 Use Cases

  • AI agent memory/context handling via MCP
  • Reducing inference cost caused by excessive context
  • Tool-augmented workflows where “mcp-server” and “mcp-tools” are relevant
  • Privacy-first AI and privacy-first technical stacks

⚡ Developer Benefits

  • No SDK required
  • No dependencies
  • Python-focused tooling (listed topic)
  • Uses zstd Zstandard compression/decompression (listed topic)

⚠️ Limitations

  • Documentation excerpt does not specify supported languages beyond the provided “python” topic, or detailed benchmark scope and implementation details beyond the stated motivation.

Topics

agent-memory-mcpai-agentsai-agents-and-toolsai-agents-automationai-agents-mcpcompression-algorithmllm-agentsllm-evaluationllm-inferencellm-toolsmcpmcp-servermcp-toolsprivacy-firstprivacy-first-aiprivacy-first-techpythonvector-search-enginezero-dependencyzstd-zstandard-compress-decompress