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"Understanding File System Operations: Read, Write, and Edit Directories" matching MCP servers:

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    A file management system powered by Claude AI that provides document access and manipulation through MCP protocol and Telegram bot integration, enabling users to interact with files via natural language commands.
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    Connect AI agents like Claude, Cursor, and Gemini to historical Windows performance and privacy data gathered by the AppControl Windows app. This server enables natural language queries into CPU, GPU, and temperature history alongside system security events for deep local auditing.
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    31
    MIT
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    Encoding-aware, indentation-smart file tools for AI coding agents. 20+ tools including read/edit with automatic encoding detection, smart indentation conversion, SSH, SFTP, process management, and system utilities.
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    MIT
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    Operations toolchain for SQLite, Cloudflare D1, and Turso. Every command is available as both a CLI and an MCP tool: inspect, diff, migrate, monitor, back up, and repair databases. 22 stdio tools, read-only by default.
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    AGPL 3.0
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    Model Context Protocol (MCP) server for GitLab — exposes 1006 GitLab REST & GraphQL API operations as MCP tools (42 meta-tools / 57 enterprise), 24 resources, 38 prompts, and 17 completion types for AI assistants. Written in Go, single static binary, stdio and HTTP transport.
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    35
    MIT
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    Self-hostable, markdown-native team wiki with a built-in MCP server: agents search, read, and write your wiki pages (ranked Postgres full-text + semantic search, backlink traversal). Plus Atlas, which auto-generates a cited, coverage-checked wiki from your git repos and Jira.
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    AGPL 3.0
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    MCP server — read-only log access for AI assistants. Debug your Linux server with AI, without giving the AI shell access.
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    Local-first dev memory: indexes Git commits, PRs, Jira/Linear tickets, Confluence docs, Slack threads, and Calendar events into a local SQLite/FTS5/ONNX index, and exposes them as MCP tools so Claude Code, Cursor, and Codex can search and cite your past work.
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    15
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    MIT
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    An MCP server that gives AI agents structured read/write access to a story-based project backlog. Agents can list stories, read content, update status, and append notes — all backed by plain markdown files that live inside your project repository. There is no shared server. The backlog files live in your repo under requirements/, committed and versioned alongside your code
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    16
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    The Unlicense
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    Persistent, consensus-validated institutional memory for AI agents. Gives LLMs real memory that survives across sessions - validated through BFT consensus, not just dumped to a file.
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    Apache 2.0
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    Read-only MCP server for aggregate HitKeep analytics and official documentation, including traffic, events, goals, funnels, ecommerce, Search Console, and AI visibility reporting.
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    MIT
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    Indexes the session histories Claude Code, Codex CLI and opencode already write into a local searchable memory. MCP recall tools, session-start auto-recall, secret redaction at index time, cross-machine sync over SSH.
    Last updated
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    448
    MIT
  • A
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    MCP server that keeps language server sessions warm and routes multiple languages through one process. Agents get persistent cross-file awareness, speculative execution (simulate edits before writing to disk), and 20 skills that encode correct multi-step operations like safe rename, blast-radius analysis, and end-to-end refactoring. Single Go binary, no runtime dependencies.
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    MIT
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    MCP server for patent search and prior art discovery powered by Google Patents public dataset on BigQuery. Supports searching patents, fetching full patent details with CPC codes and citations, and retrieving legal claims text.
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    3
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    MIT
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    A Zotero MCP server built for agent safety: a capability-tagged tool registry (every command carries operation/requires/destructive annotations), preview-first writes behind a mutation journal, and read-only defaults. Single Go binary with an MCPB one-click manifest for Claude Desktop.
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    MCP server for managing interactive processes, enabling AI agents to start, interact with, and terminate long-running programs like SSH sessions, REPLs, and installers via read/write operations.
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    8
    8
    MIT