Codelogic Mcp Server
Pull CodeLogic dependency and impact context into Claude Code while refactoring or reviewing legacy codebases.
Overview
CodeLogic MCP Server is a Build-phase MCP integration that exposes CodeLogic dependency and impact data to your AI programming assistant over stdio.
What is this MCP server?
- PyPI package `codelogic-mcp-server` v1.1.1 with stdio transport
- Requires CodeLogic host URL, username, password, and workspace name via env vars
- Surfaces rich software dependency data inside the AI programming assistant
- Optional CODELOGIC_DEBUG_MODE for troubleshooting MCP calls
- Enterprise-oriented: needs an existing CodeLogic-scanned workspace
- MCP server version 1.1.1 on PyPI
- 4 required environment variables for host, user, password, and workspace
- Transport type stdio per server schema
Community signal: 36 GitHub stars.
What problem does it solve?
Agents refactor blind without trustworthy dependency graphs when the codebase was scanned elsewhere in CodeLogic.
Who is it for?
Developers with a CodeLogic account and scanned workspace who want dependency-aware answers inside the agent.
Skip if: Hobby repos with no CodeLogic tenant or builders who refuse hosted credentials in MCP env config.
What do I get? / Deliverables
After configuration, your MCP client can query CodeLogic workspace dependency intelligence while you code or review changes.
- Authenticated MCP bridge to CodeLogic dependency data
- Agent-queryable dependency context from the named workspace
- Debug-capable stdio server when CODELOGIC_DEBUG_MODE is set
Recommended MCP Servers
Journey fit
Dependency intelligence is most often wired during build integrations, though the same data supports review before ship and safer changes in operate. This server authenticates to a hosted CodeLogic workspace—classic third-party integration tooling for the integrations subphase.
How it compares
Hosted dependency-graph MCP, not a local-only API indexer like CodeSurface.
Common Questions / FAQ
Who is codelogic-mcp-server for?
Teams and solo maintainers already using CodeLogic who want that dependency data available to Claude Code, Cursor, or other stdio MCP clients.
When should I use codelogic-mcp-server?
Use it when planning refactors, integration work, or reviews where CodeLogic’s scanned graph is more reliable than the model inferring couplings.
How do I add codelogic-mcp-server to my agent?
Install `codelogic-mcp-server` from PyPI, set CODELOGIC_SERVER_HOST, CODELOGIC_USERNAME, CODELOGIC_PASSWORD, and CODELOGIC_WORKSPACE_NAME, then add the stdio server block in your MCP client config.