Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
An MCP Server to utilize Codelogic's rich software dependency data in your AI programming assistant.
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We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
CODELOGIC_SERVER_HOST, CODELOGIC_USERNAME, CODELOGIC_PASSWORD, CODELOGIC_WORKSPACE_NAME, CODELOGIC_DEBUG_MODEValues marked secret are keys to your account. Never share them or paste them into a chat.
You need
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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-serverFill in the empty values before running it.
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.
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.
CODELOGIC_DEBUG_MODE envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
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
The registry name was verified with the GitHub account CodeLogicIncEngineering, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
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.
You need to fill in: CODELOGIC_SERVER_HOST, CODELOGIC_USERNAME, CODELOGIC_PASSWORD, CODELOGIC_WORKSPACE_NAME
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).
The GitHub repo last changed –, and the latest version (1.3.0) reached the registry 3 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, Symantec Cloud DLP AIops
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
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Governed Symantec Cloud DLP — 14 MCP tools, read-only with audit.
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.
An MCP Server to utilize Lineai's rich software dependency data in your AI programming assistant.
Code-derived architecture documentation lives in docs/ (added in LIN-737; updated for the LIN-699 changes — PR #61 / neo4cape #1860):
/api/... endpoints each tool calls, auth flow, caching, error-handling taxonomy, configuration, packaging/release, and findings.The server implements eight tools: two impact tools plus six graph tools backed by the Lineai graph HTTP API.
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.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".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.
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).
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).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".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.from_node_id and to_node_id.proposed_change_summary.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.
The MCP server relies upon Astral UV to run, please install
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:
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" } } } }
lineai-mcp-server.To configure this MCP server in VS Code:
.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/uvxon Linux/Mac orC:\Users\username\AppData\Local\astral\uvx.exeon Windows.
MCP: Add Server command from the Command Palette and provide the server information.MCP: List Servers command from the Command Palette.Configure Claude Desktop by editing the configuration file:
~/Library/Application\ Support/Claude/claude_desktop_config.json%APPDATA%/Claude/claude_desktop_config.json~/.config/Claude/claude_desktop_config.jsonAdd 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/uvxon Linux/Mac orC:\Users\username\AppData\Local\astral\uvx.exeon Windows.
After adding the configuration, restart Claude Desktop to apply the changes.
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/uvxon Linux/Mac orC:\Users\username\AppData\Local\astral\uvx.exeon Windows.
After adding the configuration, restart Windsurf IDE or refresh the tools to apply the changes.
To configure the Lineai MCP server in Cursor:
.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/uvxon Linux/Mac orC:\Users\username\AppData\Local\astral\uvx.exeon Windows.
The Lineai MCP server tools will now be available in your Cursor workspace.
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**.
Create a .vscode/copilot-instructions.md file with the following content:
# Lineai MCP Server Instructions
When modifying existing code methods:
When modifying SQL code or database entities:
To use the Lineai tools effectively:
Only the beginning is shown; read the rest in the repo