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SCP — Selective Context Protocol

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    • A
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      maintenance
      Intelligent MCP proxy server that reduces context bloat by serving only the tools your AI actually needs through semantic search and a fixed two-tool surface.
      14
      MIT
    • A
      license
      A
      quality
      C
      maintenance
      Provides reversible context compression for AI agents, reducing token usage while preserving the ability to retrieve original content, and serves as an MCP server for integration with tools like GitHub Copilot and Claude Code.
      3
      1
      Apache 2.0
    • A
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      A
      maintenance
      Enables MCP-compatible developer environments to shrink verbose tool outputs—test logs, git diffs, directory listings, and file dumps—before they reach the context window, preserving compiler errors, failure signatures, and decisive anchors. It runs either as direct callable tools or as a transparent proxy wrapping other MCP servers such as filesystem, git, or terminal providers.
      1
      MIT
    • A
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      A
      maintenance
      A proxy server that wraps existing MCP servers to significantly reduce token consumption by compressing tool descriptions into a two-step interface. It enables users to integrate extensive toolsets without exceeding context limits or incurring high API costs.
      138
      Apache 2.0
    • A
      license
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      quality
      C
      maintenance
      MCP server that reduces AI agent token usage by up to 90% through intelligent context compression. Enables efficient code exploration, multi-file refactoring, and debugging by providing tools for smart reading, searching, and managing code context.
      4
      MIT
    • A
      license
      A
      quality
      A
      maintenance
      Token-saving MCP proxy. Hides your MCP servers' tool lists behind a search tool and shrinks large tool results (GitHub, Playwright, logs, test output), keeping the full result available on request. One-command setup for Claude Code, Codex, Claude Desktop and Cursor.
      10
      1
      MIT