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"How to increase a model's context window for handling large files" matching MCP servers:

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    Stdio MCP server for sandboxed file access — read files, search content, safely edit with checksums, and manage file structure.
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    ISC
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    Enables AI agents to safely explore directories, read files, search content by pattern or filename, and edit files with checksum verification and dry-run preview within sandboxed filesystem access.
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    ISC
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    A plugin that intercepts large MCP tool outputs, indexes them into a local FTS5 knowledge base, and replaces them with summaries, enabling searchable retrieval to save context window space.
    3
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    Provides MCP tools to profile and optimize LLM conversation context, identifying token waste and applying deterministic fixes to reduce context window usage.
    MIT
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    A very simple vector store that provides capability to watch a list of directories, and automatically index all the markdown, html and text files in the directory to a vector store to enhance context.
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    MIT
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    Enables interaction with the FVWM3 window manager for configuration generation, window management, and debugging. Provides access to config files, runtime state, and control tools for managing desktops, monitors, and tiling operations.
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    An MCP server that preserves LLM context by intercepting large data outputs and returning only concise summaries or relevant sections. It enables efficient sandboxed code execution, file processing, and documentation indexing across multiple programming languages and authenticated CLIs.
    11
    19,534
    19,859
    Elastic 2.0
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    Give your AI agents access to 8,500+ community curated awesome lists with over 1 million curated resources.
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    MIT
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    Provides AI assistants with real-time visibility into your codebase's internal libraries, team patterns, naming conventions, and usage frequencies to generate code that matches your team's actual practices.
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    Elastic 2.0
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    Aggregator MCP proxy that collapses N downstream MCP servers into 4 meta-tools with progressive tool discovery, and compresses large tool outputs (HTML→Markdown, JSON summarization) with full-output retrieval via read_more and a per-session token-savings report.
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    MIT
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    Long AI conversations fail in predictable ways. Context-First fixes all four: Failure Mode What Goes Wrong Context-First Solution Context Drift AI forgets earlier decisions and intent as the conversation grows context_loop + detect_drift continuously re-anchor every turn Silent Contradiction New inputs silently overrule established facts — the AI doesn't notice detect_conflicts compares every inp
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    MIT
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    Intelligent context manager for AI coding assistants that uses a three-level memory system (core, active, archive) to remember project context across conversations.
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    MIT
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    Provides LLMs with secure, read-only access to local documentation by scanning directories, extracting content from PDF, DOCX, Markdown, and text files, and performing keyword searches.
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    MIT
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    Enables agents to quickly find and edit code in a codebase with surgical precision. Find symbols, edit them everywhere with tools for reading code blocks, searching/replacing text, and making precise line-based modifications.
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