A local knowledge graph + MCP server that gives AI coding agents a map of your .NET codebase
Slnmap (sln-map) — a semantic map of your .sln for AI coding agents.
Your AI agent can't refactor .NET code it can't see. Ask an agent "what breaks if I change this interface?" and it guesses from the files in its context — missing callers in other projects and files it never opened. Slnmap gives the agent a precise, compiler-accurate map of your whole solution, so it answers correctly: every caller, every implementation, across every project. Fewer broken changes, no hallucinated dependencies. It runs locally and serves the map to your agent or editor over MCP.
1. Install the global tool (requires the .NET SDK 9.0+):
2. Analyze your solution (or a single .csproj) — this builds slnmap.db in the current folder:
3. Connect your MCP client. For Claude Code, add this to .mcp.json in your project. Use an absolute path to the slnmap.db you just built — an MCP client's working directory is usually not your project folder, so a relative path can silently resolve to the wrong (or a missing) file:
On macOS/Linux, use a POSIX absolute path instead, e.g. /home/you/project/slnmap.db.
That's it. Ask your agent an architecture question and it will call Slnmap. (Run slnmap doctor first if anything looks off — see Troubleshooting.)
The server exposes five read-only tools. Give them fully qualified names; results are capped and counts-first. (A note the tools also carry: an FQN does not reveal whether a member is an explicit interface implementation.)
From the project README.
Add the radar badge to your README — it shows your project was picked up by MCP Radar and links to this page:
[](https://mcp.liqiwa.com/s/EMahmoudNabil--slnmap.html)
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