SharpLensMcp

A Model Context Protocol (MCP) server providing 62 AI-optimized tools for .NET/C# semantic code analysis, navigation, refactoring, and code generation using Microsoft Roslyn.

Built for AI coding agents - provides compiler-accurate code understanding that AI cannot infer from reading source files alone.

Installation

Via NuGet (Recommended)

dotnet tool install -g SharpLensMcp

Then run with:

sharplens

Via npm

npx -y sharplens-mcp

Build from Source

dotnet build -c Release
dotnet publish -c Release -o ./publish

Claude Code Setup

1. Install the tool (pick one):

dotnet tool install -g SharpLensMcp
# or
npx -y sharplens-mcp

2. Create .mcp.json in your project root:

{
  "mcpServers": {
    "sharplens": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "sharplens-mcp"],
      "env": {
        "DOTNET_SOLUTION_PATH": "/path/to/your/Solution.sln (or .slnx)"
      }
    }
  }
}

3. Restart Claude Code to load the MCP server

4. Verify by asking Claude to run a health check on the Roslyn server

Why Use This with Claude Code?

Claude Code has native LSP support for basic navigation (go-to-definition, find references). SharpLensMcp adds deep semantic analysis:

| Capability | Native LSP | SharpLensMcp | |------------|------------|--------------| | Go to definition | ✅ | ✅ | | Find references | ✅ | ✅ | | Find async methods missing CancellationToken | ❌ | ✅ | | Impact analysis (what breaks?) | ❌ | ✅ | | Dead code detection | ❌ | ✅ | | Complexity metrics | ❌ | ✅ | | Safe refactoring with preview | ❌ | ✅ | | Batch operations | ❌ | ✅ |

Configuration

| Environment Variable | Description | Default | |---------------------|-------------|---------| | DOTNET_SOLUTION_PATH | Path to .sln or .slnx file to auto-load on startup | None (must call load_solution) | | SHARPLENS_ABSOLUTE_PATHS | Use absolute paths instead of relative | false (relative paths save tokens) | | ROSLYN_LOG_LEVEL | Logging verbosity: Trace, Debug, Information, Warning, Error | Information | | ROSLYN_TIMEOUT_SECONDS | Timeout for long-running operations | 30 | | ROSLYN_MAX_DIAGNOSTICS | Maximum diagnostics to return | 100 | | ROSLYN_ENABLE_SEMANTIC_CACHE | Enable semantic model caching | true (set to false to disable) |

If DOTNET_SOLUTION_PATH is not set, you must call the load_solution tool before using other tools.

AI Agent Configuration Tips

AI models may have trained bias toward using their native tools (Grep, Read, LSP) instead of MCP server tools, even when SharpLensMcp provides better capabilities.

To ensure optimal tool usage:

1. Claude Code: Add to your project's CLAUDE.md:

   For C# code analysis, prefer SharpLensMcp tools over native tools:
   - Use `roslyn:search_symbols` instead of Grep for finding symbols
   - Use `roslyn:get_method_source` instead of Read for viewing methods
   - Use `roslyn:find_references` for semantic (not text) references
   

2. Other MCP clients: Configure tool priority in your agent's system prompt

The semantic analysis from Roslyn is more accurate than text-based search, especially for overloaded methods, partial classes, and inheritance hierarchies.

Agent Responsibility: Document Synchronization

Important: SharpLensMcp maintains an in-memory representation of your solution for fast queries. When files are modified externally (via Edit/Write tools), the agent is responsible for synchronizing changes.

When to call sync_documents:

| Action | Call sync_documents? | |--------|---------------------| | Used E

... View full README on GitHub