原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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Codelogic MCP Server

作者:CodeLogicIncEngineering版本 1.3.0i★ –i在你的电脑上运行
注册名称io.github.CodeLogicIncEngineering/codelogic-mcp-server

安装

概览

作者提供的说明(英文原文)

An MCP Server to utilize Codelogic's rich software dependency data in your AI programming assistant.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 其他
  • 你需要填写:CODELOGIC_SERVER_HOST, CODELOGIC_USERNAME, CODELOGIC_PASSWORD, CODELOGIC_WORKSPACE_NAME

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: CODELOGIC_SERVER_HOST, CODELOGIC_USERNAME, CODELOGIC_PASSWORD, CODELOGIC_WORKSPACE_NAME, CODELOGIC_DEBUG_MODE

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "codelogic": {
      "command": "uvx",
      "args": [
        "codelogic-mcp-server"
      ],
      "env": {
        "CODELOGIC_SERVER_HOST": "your-value",
        "CODELOGIC_USERNAME": "your-value",
        "CODELOGIC_PASSWORD": "your-value",
        "CODELOGIC_WORKSPACE_NAME": "your-value",
        "CODELOGIC_DEBUG_MODE": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add codelogic --env CODELOGIC_SERVER_HOST=your-value --env CODELOGIC_USERNAME=your-value --env CODELOGIC_PASSWORD=your-value --env CODELOGIC_WORKSPACE_NAME=your-value --env CODELOGIC_DEBUG_MODE=your-value -- uvx codelogic-mcp-server

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "codelogic": {
      "command": "uvx",
      "args": [
        "codelogic-mcp-server"
      ],
      "env": {
        "CODELOGIC_SERVER_HOST": "your-value",
        "CODELOGIC_USERNAME": "your-value",
        "CODELOGIC_PASSWORD": "your-value",
        "CODELOGIC_WORKSPACE_NAME": "your-value",
        "CODELOGIC_DEBUG_MODE": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "codelogic": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "codelogic-mcp-server"
      ],
      "env": {
        "CODELOGIC_SERVER_HOST": "your-value",
        "CODELOGIC_USERNAME": "your-value",
        "CODELOGIC_PASSWORD": "your-value",
        "CODELOGIC_WORKSPACE_NAME": "your-value",
        "CODELOGIC_DEBUG_MODE": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • CODELOGIC_SERVER_HOST 必填 env
    url to the CodeLogic server e.g. https://myco.app.codelogic.com
  • CODELOGIC_USERNAME 必填 env
    CodeLogic server username
  • CODELOGIC_PASSWORD 机密 必填 env
    CodeLogic server password
  • CODELOGIC_WORKSPACE_NAME 必填 env
    the workspace name that your code is scanned into
  • CODELOGIC_DEBUG_MODE env
    When enabled, additional debug files such as timing_log.txt and impact_data*.json will be generated. Defaults to false

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 CodeLogicIncEngineering 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32461 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32461 个服务器的 20% 更新
  • 基础检查结果等于或优于此分类中其他 32461 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Codelogic MCP Server 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

你需要填写:CODELOGIC_SERVER_HOST, CODELOGIC_USERNAME, CODELOGIC_PASSWORD, CODELOGIC_WORKSPACE_NAME

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(1.3.0)于3个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, dotnet-mcp

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211昨天更新
安装

dotnet-mcp

作者:Skymly

MCP server for .NET symbols, XAML, source generators, and restricted workspace edit

在你的电脑上运行今天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

lineai-mcp-server

An MCP Server to utilize Lineai's rich software dependency data in your AI programming assistant.

Documentation

Code-derived architecture documentation lives in docs/ (added in LIN-737; updated for the LIN-699 changes — PR #61 / neo4cape #1860):

  • docs/architecture.md — full architecture analysis: module map, tool surface and the Lineai /api/... endpoints each tool calls, auth flow, caching, error-handling taxonomy, configuration, packaging/release, and findings.
  • docs/architecture-diagrams.md — Mermaid diagram set (ecosystem, module map, call sequence, auth/caching, error taxonomy).
  • docs/rendered-diagrams/ — committed SVG renders of every diagram.

Components

Tools

The server implements eight tools: two impact tools plus six graph tools backed by the Lineai graph HTTP API.

Code Analysis Tools
  • lineai-method-impact: Pulls an impact assessment from the Lineai server's APIs for your code.
  • Takes the given "method" that you're working on. Pass the fully-qualified class name in "class" (e.g. com.acme.shell.AnalyzeCommands) when the simple name may exist in several repositories: a fully-qualified class selects exactly that class, while a simple name that matches several classes returns an ambiguity page listing the candidates instead of silently analyzing another repository's class.
  • The impact is a bounded upstream traversal from the Lineai graph impact endpoint (depth argument, default 3, max 10). The report's Impact scope section says where the data came from (graph, or the legacy full-chain endpoint when the graph endpoint is not deployed) and whether it is complete (ok) or a lower bound (partial) — a partial result is never "no impact".
  • lineai-database-impact: Analyzes impacts between code and database entities.
  • Takes the database entity type (column, table, or view) and its name.

All eight tools also accept optional workspace and materialized_view_id arguments to scope a single call; when neither is given (and LINEAI_WORKSPACE_NAME is unset) the server's default workspace's latest materialized view is used automatically.

Graph API tools

These call POST / GET endpoints under /api/ai-retrieval/graph/ on the same host as LINEAI_SERVER_HOST, using the same session auth as other MCP tools. If graph routes are not deployed, the server returns a clear “graph not available” style message (often after HTTP 404).

  • lineai-graph-capabilities: GET — discover supported relationship types, limits, and flags for the workspace materialized view (materializedViewId resolved like every other tool: explicit id → workspace argument → LINEAI_WORKSPACE_NAME → server default).
  • lineai-graph-search: Search nodes by text query / q and/or identity_prefix; optional scan_space (scan space id or display name), prefer_latest_scan, limit. Results are ranked by the server (exact short name → exact fully-qualified name → class-like labels → text score → newest scan) and data.hits[i] describes data.nodes[i] (score, matchKind, labelTier); data.totalHitCount is the real total, so a full page means "narrow the query", not "absent".
  • lineai-graph-impact: Bounded dependency / blast-radius traversal from seed_node_ids with direction (upstream = what depends on the seeds, downstream, both) and depth (server default 3, max 10). The response carries status (ok | partial), truncated, nodeCount, staticAnalysisGap and assumptionsApplied markers; the tool prints a note above the JSON whenever the result is partial, degraded, or an older server ignored an option.
  • lineai-graph-path-explain: Shortest-path style explanation between from_node_id and to_node_id.
  • lineai-graph-validate-change-scope: Heuristic checklist / risk summary for a proposed change given seed nodes and proposed_change_summary.
  • lineai-graph-owners: Resolve a node by node_id or identity_prefix and surface property fields whose names contain "owner".

Tool arguments accept snake_case aliases (for example materialized_view_id, seed_node_ids) where noted in the MCP schema; request bodies sent to Lineai use camelCase JSON keys.

Install
Pre Requisites

The MCP server relies upon Astral UV to run, please install

MacOS Workaround for uvx

There is a known issue with uvx on MacOS where the Lineai MCP server may fail to launch in certain IDEs (such as Cursor), resulting in errors like: See issue #11

Failed to connect client closed

This appears to be a problem with Astral uvx running on MacOS. The following can be used as a workaround:

  1. Clone this project locally.
  2. Configure your mcp.json to use uv instead of uvx. For example:
{

"mcpServers": { "lineai-mcp-server": { "type": "stdio", "command": " /uv", "args": [ "--directory", " /lineai-mcp-server-main", "run", "lineai-mcp-server" ], "env": { "LINEAI_SERVER_HOST": " ", "LINEAI_USERNAME": " ", "LINEAI_PASSWORD": " ", "LINEAI_WORKSPACE_NAME": " ", "LINEAI_DEBUG_MODE": "true" } } } }

  1. Restart Cursor.
  2. Ensure the Cursor Global Rule for Lineai is in place.
  3. Open the MCP tab in Cursor and refresh the lineai-mcp-server.
  4. Ask Cursor to make a code change in an existing class. The MCP server should now run the impact analysis successfully.

Configuration for Different IDEs

Visual Studio Code Configuration

To configure this MCP server in VS Code:

  1. First, ensure you have GitHub Copilot agent mode enabled in VS Code.
  1. Create a .vscode/mcp.json file in your workspace with the following configuration:
{

"servers": { "lineai-mcp-server": { "type": "stdio", "command": "uvx", "args": [ "lineai-mcp-server@latest" ], "env": { "LINEAI_SERVER_HOST": " ", "LINEAI_USERNAME": " ", "LINEAI_PASSWORD": " ", "LINEAI_WORKSPACE_NAME": " ", "LINEAI_DEBUG_MODE": "true" } } } }

Note: On some systems, you may need to use the full path to the uvx executable instead of just "uvx". For example: /home/user/.local/bin/uvx on Linux/Mac or C:\Users\username\AppData\Local\astral\uvx.exe on Windows.

  1. Alternatively, you can run the MCP: Add Server command from the Command Palette and provide the server information.
  1. To manage your MCP servers, use the MCP: List Servers command from the Command Palette.
  1. Once configured, the server's tools will be available to Copilot agent mode. You can toggle specific tools on/off as needed by clicking the Tools button in the Chat view when in agent mode.
  1. To use the Lineai tools in agent mode, you can specifically ask about code impacts or database relationships, and the agent will utilize the appropriate tools.
Claude Desktop Configuration

Configure Claude Desktop by editing the configuration file:

  • On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
  • On Windows: %APPDATA%/Claude/claude_desktop_config.json
  • On Linux: ~/.config/Claude/claude_desktop_config.json

Add the following to your configuration file:

"mcpServers": {

"lineai-mcp-server": { "command": "uvx", "args": [ "lineai-mcp-server@latest" ], "env": { "LINEAI_SERVER_HOST": " ", "LINEAI_USERNAME": " ", "LINEAI_PASSWORD": " ", "LINEAI_WORKSPACE_NAME": " " } } }

Note: On some systems, you may need to use the full path to the uvx executable instead of just "uvx". For example: /home/user/.local/bin/uvx on Linux/Mac or C:\Users\username\AppData\Local\astral\uvx.exe on Windows.

After adding the configuration, restart Claude Desktop to apply the changes.

Windsurf IDE Configuration

To run this MCP server with Windsurf IDE:

Configure Windsurf IDE:

To configure Windsurf IDE, you need to create or modify the ~/.codeium/windsurf/mcp_config.json configuration file.

Add the following configuration to your file:

"mcpServers": {

"lineai-mcp-server": { "command": "uvx", "args": [ "lineai-mcp-server@latest" ], "env": { "LINEAI_SERVER_HOST": " ", "LINEAI_USERNAME": " ", "LINEAI_PASSWORD": " ", "LINEAI_WORKSPACE_NAME": " " } } }

Note: On some systems, you may need to use the full path to the uvx executable instead of just "uvx". For example: /home/user/.local/bin/uvx on Linux/Mac or C:\Users\username\AppData\Local\astral\uvx.exe on Windows.

After adding the configuration, restart Windsurf IDE or refresh the tools to apply the changes.

Cursor Configuration

To configure the Lineai MCP server in Cursor:

  1. Configure the MCP server by creating a .cursor/mcp.json file:
{

"mcpServers": { "lineai-mcp-server": { "command": "uvx", "args": [ "lineai-mcp-server@latest" ], "env": { "LINEAI_SERVER_HOST": " ", "LINEAI_USERNAME": " ", "LINEAI_PASSWORD": " ", "LINEAI_WORKSPACE_NAME": " ", "LINEAI_DEBUG_MODE": "true" } } } }

Note: On some systems, you may need to use the full path to the uvx executable instead of just "uvx". For example: /home/user/.local/bin/uvx on Linux/Mac or C:\Users\username\AppData\Local\astral\uvx.exe on Windows.

  1. Restart Cursor to apply the changes.

The Lineai MCP server tools will now be available in your Cursor workspace.

AI Assistant Instructions/Rules

To help the AI assistant use the Lineai tools effectively, you can add the following instructions/rules to your client's configuration. We recommend customizing these instructions to align with your team's specific coding standards, best practices, and workflow requirements:

When the graph API is available on your Lineai host, extend your rules with the same guidance the server already advertises in its MCP instructions: use **lineai-graph-* tools (search, impact, path-explain, validate-change-scope, owners, capabilities) for bounded graph discovery; if graph calls fail with “not available”, fall back to lineai-method-impact / lineai-database-impact**.

VS Code (GitHub Copilot) Instructions

Create a .vscode/copilot-instructions.md file with the following content:

# Lineai MCP Server Instructions

When modifying existing code methods:

  • Use lineai-method-impact to analyze code changes
  • Use lineai-database-impact for database modifications
  • When the Lineai graph API is available, use lineai-graph-* tools (search, impact, path-explain, validate-change-scope, owners, capabilities) for bounded graph discovery; otherwise rely on method/database impact tools
  • Highlight impact results for the modified methods

When modifying SQL code or database entities:

  • Always use lineai-database-impact to analyze potential impacts
  • Highlight impact results for the modified database entities

To use the Lineai tools effectively:

  • For code impacts: Ask about specific methods or functions
  • For database relationships: Ask about tables,

只显示了开头部分;其余内容请在仓库中阅读

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