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    Enables coding agents to search and retrieve persistent repository memory created by Cliper, providing context, gaps, architecture, and timeline information via MCP tools.
    6
    MIT
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    A project-local MCP bridge that allows Codex Desktop to plan tasks and OpenCode to execute them within the current project directory, with session reuse and native OpenCode background subagents.
    4
    1
    MIT
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    Enables coding agents to navigate and query source code by providing context, symbols, and call graph information through a graph index.
    4
    MIT
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    Enables users to run shell commands with compressed output, extract information from large files, drive local opencode and Codex agents, perform browser-automation tasks, and monitor runs via a live dashboard.
    MIT
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    Enables coding agents like Cursor to access Figma design data, fetch layout and styling information, and implement designs in any framework.
    140,026 npm
    MIT
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    https://gopls-mcp.org/ MCP server for golang projects development: Expand AI Code Agent ability boundary to have a semantic understanding and determinisic information for golang projects.
    60
    BSD 3-Clause
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    Lets users explicitly hand off coding tasks to a single DeepSeek sub-agent that writes directly into the current project without Git, while Codex handles task setup and reviews the resulting diff.
    1
    MIT
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    Bridges Large Language Models with Language Server Protocol interfaces, allowing LLMs to access LSP's hover information, completions, diagnostics, and code actions for improved code suggestions.
    2,705 npm
    128
    MIT
  • F
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    Enables AI coding agents to access real-time VSCode LSP diagnostics, type information, and code navigation without slow tsc/eslint checks, plus symbol renaming and file operations.
    -
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    Plori runs AI agents in Workspaces. A Workspace is a project folder in the cloud. Several agents can work in it at the same time, each on its own copy of the files, and Plori merges their work back into the folder. Every version of the files is kept.
    24
    56 npm
    MIT
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    An MCP server giving coding agents context-window-aware code search and safe, atomic multi-file edits — built to cut token usage on large codebases without sacrificing correctness.
    3
    20 npm
    5
    MIT
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    Enables structured, step-by-step problem-solving through dynamic thinking processes that can be revised, branched, and adjusted as understanding deepens. Supports breaking down complex problems into manageable steps with the ability to revise previous thoughts and explore alternative reasoning paths.
    1
    199,738 npm
    MIT
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    Enables LLMs to apply Martin Fowler's 71+ refactoring patterns to codebases through a pluggable, language-agnostic architecture. Supports previewing and applying refactorings, analyzing code smells, and inspecting code structure with safe-by-default operations.
    5
    39 PyPI
    5
    MIT
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    Provide a human vision statement. The AI autonomously researches, audits your codebase, generates specs and plans, implements, and validates — with bi-directional verification at every junction to ensure nothing is missed or invented.
    15
    2
    MIT
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    Enables AI coding agents to retrieve relevant execution context before a task, compare candidate paths, log outcomes, and search past experiences stored locally in SQLite. It lets agents reuse what worked on similar tasks and get live alerts when a run stagnates or repeats failures.
    14
    103 PyPI
    3
    MIT