CodeSherlock
Run AI-powered static and contextual code analysis from your agent so reviews surface issues with repo-aware context instead of one-off paste reviews.
Overview
io.github.FGC-Shreyansh-Chachaundiya/codesherlock-mcp-server is a Ship-phase MCP server that provides AI-powered static and contextual code analysis for agents.
What is this MCP server?
- CodeSherlock-branded MCP server for static plus contextual code analysis
- npm scope package @codesherlock/codesherlock-mcp-server with stdio transport
- Combines traditional static signals with AI contextual understanding of the codebase
- Registry lists server 0.1.1 with npm package 0.1.0—confirm installed version in lockfile
- Developer-tool MCP integration—not a hosted CI dashboard replacement by itself
- MCP server metadata version 0.1.1
- npm package @codesherlock/codesherlock-mcp-server (listed 0.1.0)
- Transport: stdio
What problem does it solve?
Solo shipping means reviews are shallow or skipped because paste-into-chat analysis loses project context and does not scale across files.
Who is it for?
Indie developers who want MCP-native code review assistance on real repos during pre-ship review passes.
Skip if: Greenfield codegen-only workflows, infrastructure-only changes with no application code, or teams that require licensed SAST with formal sign-off only.
What do I get? / Deliverables
Your agent invokes CodeSherlock tools to return static and context-aware findings you can fix before merge or release.
- Agent-triggered CodeSherlock analysis runs on selected code
- Findings blending static rules with AI contextual interpretation
- Review artifacts you can turn into fix commits before ship
Recommended MCP Servers
Journey fit
Automated analysis before merge or release belongs in Ship when you are reviewing quality and risk, not when you are sketching features. Review is the canonical shelf for MCP servers that analyze existing code rather than generate greenfield scaffolds.
How it compares
AI code analysis MCP—not ExposureGuard-style domain scanning and not a planning skill.
Common Questions / FAQ
Who is io.github.FGC-Shreyansh-Chachaundiya/codesherlock-mcp-server for?
Solo builders and small teams using MCP agents who want structured static and contextual analysis on their codebase.
When should I use io.github.FGC-Shreyansh-Chachaundiya/codesherlock-mcp-server?
During Ship review before merging risky changes, cutting releases, or when an agent is doing a systematic quality pass on a module.
How do I add io.github.FGC-Shreyansh-Chachaundiya/codesherlock-mcp-server to my agent?
Install @codesherlock/codesherlock-mcp-server via npm, add stdio MCP config per CodeSherlock-MCP-Server GitHub docs, then run analysis tools against your workspace paths.