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Codelogic MCP Server

by CodeLogicIncEngineeringversion 1.3.0i★ –iRuns on your computer
Registry nameio.github.CodeLogicIncEngineering/codelogic-mcp-server

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other
  • You need to fill in: CODELOGIC_SERVER_HOST, CODELOGIC_USERNAME, CODELOGIC_PASSWORD, CODELOGIC_WORKSPACE_NAME

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: CODELOGIC_SERVER_HOST, CODELOGIC_USERNAME, CODELOGIC_PASSWORD, CODELOGIC_WORKSPACE_NAME, CODELOGIC_DEBUG_MODE

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into 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"
      }
    }
  }
}

Run this in your terminal

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

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.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"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "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"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • CODELOGIC_SERVER_HOST required env
    url to the CodeLogic server e.g. https://myco.app.codelogic.com
  • CODELOGIC_USERNAME required env
    CodeLogic server username
  • CODELOGIC_PASSWORD secret required env
    CodeLogic server password
  • CODELOGIC_WORKSPACE_NAME required 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

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account CodeLogicIncEngineering, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32433 servers in this category
  • Published to the registry more recently than 21% of the other 32433 servers in this category
  • Basic checks equal to or better than 100% of the other 32433 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Codelogic MCP Server safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: CODELOGIC_SERVER_HOST, CODELOGIC_USERNAME, CODELOGIC_PASSWORD, CODELOGIC_WORKSPACE_NAME

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.3.0) reached the registry 3 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Symantec Cloud DLP AIops

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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Runs on your computer★ 440MITUpdated 14 months ago
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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,

Only the beginning is shown; read the rest in the repo

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