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Lineai MCP Server

Connects AI coding assistants to Lineai dependency data for code, database, and graph impact analysis.

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Install Lineai MCP Server

Pick your client, then add it in one click or paste the config.

STDIOPython
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "lineai-mcp-server": {
      "command": "uvx",
      "args": [
        "executable"
      ],
      "env": {
        "LINEAI_SERVER_HOST": "YOUR_VALUE_HERE",
        "LINEAI_USERNAME": "YOUR_VALUE_HERE",
        "LINEAI_PASSWORD": "YOUR_VALUE_HERE",
        "LINEAI_WORKSPACE_NAME": "YOUR_VALUE_HERE",
        "LINEAI_DEBUG_MODE": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

Install not yet sandbox-tested— we haven't run this command through our automated sandbox yet. Not a red flag; we're working through the catalog.

Overview

The lineai-mcp-server MCP server connects AI programming assistants to Lineai's software dependency data through a stdio MCP process. It provides method and database impact analysis alongside graph search, dependency traversal, path explanation, ownership lookup, and change-scope validation. Calls use Lineai server APIs with session authentication and can be scoped to a workspace or materialized view. Reach for it when an assistant needs dependency context before changing code or evaluating database relationships.

Use cases

  • Assess the impact of changing a method
  • Trace dependencies from selected code nodes
  • Analyze relationships between code and database entities
  • Explain paths between graph nodes
  • Review ownership and change-scope risks

Key features

  • Method impact assessment
  • Database entity impact analysis
  • Dependency graph search and traversal
  • Shortest-path explanations
  • Heuristic change-scope validation
  • Graph ownership lookup

Tools8

What Lineai MCP Server lets your agent do. Expand a tool for its parameters.

Self-reported~246 tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 3d ago

Recent health check succeeded.

6/6 checks healthy over the last 41d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 13d ago via OSV.dev · executable (PyPI)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars37Stargazers on the source repository.
Last commit10d agoMost recent push to the default branch.
Tools exposed8Callable tools this server registers over MCP.

How Lineai MCP Server works

What lineai-mcp-server MCP server does

The lineai-mcp-server MCP server exposes Lineai dependency information as tools for an AI programming assistant. It covers two code-analysis workflows and six graph workflows. The impact tools assess a method or database entity, while the graph tools query and traverse relationships in a workspace materialized view.

Method impact accepts a method name and an optional class filter. Database impact works with a column, table, or view name and evaluates relationships between code and database entities. These tools are intended for questions about the likely effects of modifying existing code or database-backed behavior.

How it works

The process runs as a stdio MCP server and sends requests to Lineai APIs. Graph operations use the graph HTTP API under the /api/ai-retrieval/graph/ routes on the host configured for Lineai. The same session authentication is used for the impact and graph operations.

Each tool can receive a workspace and materialized-view scope for an individual call. If those values are not supplied, the server resolves them from LINEAI_WORKSPACE_NAME and then falls back to the default workspace's latest materialized view. Tool schemas accept snake_case argument names where applicable, while outbound Lineai request bodies use camelCase fields.

The graph tools support several forms of dependency investigation:

  • Discover available relationship types, limits, and feature flags.
  • Find graph nodes by text or identity prefix.
  • Traverse dependencies from seed nodes to inspect likely blast radius.
  • Explain a shortest path between two nodes.
  • Produce a heuristic checklist and risk summary for a proposed change.
  • Find owner-related properties for a resolved node.

Setup and configuration

The lineai-mcp-server MCP server requires Astral UV. Published configurations use uvx with the lineai-mcp-server@latest package, while a local checkout can be launched with uv run. Configure the MCP client with the Lineai host, username, password, and, when needed, workspace name. LINEAI_DEBUG_MODE is also shown in some examples for diagnostic output.

The repository documents configurations for Claude Desktop, Visual Studio Code, Windsurf, and Cursor. After editing the relevant MCP configuration, restart the client or refresh its MCP tools. VS Code requires GitHub Copilot agent mode for the documented setup.

On macOS, uvx may fail to start the process in some IDEs, including Cursor, with a client-closed connection error. The documented workaround is to clone the repository, invoke uv directly with the repository directory, and restart or refresh the client.

Limitations and notes

Graph functionality depends on the graph routes being deployed on the Lineai host. If those routes are unavailable, graph calls return a graph-unavailable style response, commonly following an HTTP 404.

The graph change-scope result is heuristic: it provides a checklist and risk summary rather than a guaranteed assessment. Workspace and materialized-view selection should be checked when results need to apply to a particular environment or graph snapshot.

The documented client setup uses local environment configuration for Lineai credentials. The material does not specify a separate token-based authentication option or a license for the package.

Read the full README View source on GitHub

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Frequently Asked Questions about Lineai MCP Server

lineai-mcp-server is an MCP server that connects AI programming assistants to Lineai software dependency data. Its main tools assess method and database impact, search and traverse dependency graphs, explain paths between nodes, validate proposed change scope, discover graph capabilities, and find owner-related node properties.

Install Astral UV, then configure your MCP client to run `uvx` with `lineai-mcp-server@latest`. Set the Lineai host, username, password, and optional workspace environment variables. A local repository can instead be launched with `uv run`.

Yes, lineai-mcp-server has documented Cursor configuration using `.cursor/mcp.json`. On macOS, `uvx` may fail in some IDEs; the documented workaround is to clone the repository and run it with `uv` from the local checkout.

It needs the Lineai server host, username, and password; a workspace name can optionally select the default scope. The server uses the configured host for impact and graph API calls and applies the same session authentication to both.

Yes, its `lineai-database-impact` tool analyzes impacts between code and a named database column, table, or view. Workspace and materialized-view arguments can scope the call when a specific Lineai graph context is required.

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