TokenSaver
A structural warm start for AI coding agents in .NET. Instead of loading whole files into your assistant, TokenSaver hands it a cheap map of your code — every type and member as a signature, each tagged with its line range — so the model reads only the slice it needs instead of slurping the file. Built on the Roslyn compiler platform.
Where it pays off: outlining a file costs 70–95% fewer tokens than reading it — up to 90% on a large file. The end-to-end win is biggest on smaller / cheaper models (which over-read the most) and on large codebases: on real tasks it trims a Haiku-class model's token use by ~8%, and the savings climb with file size. A top-tier model already reads tightly, so it sees less benefit — the leaner the model, the more a warm start helps.
Works with Visual Studio 2026 (GitHub Copilot Chat), Claude Code, VS Code Copilot, Claude Desktop, and any other MCP client that speaks stdio.
→ Full docs and setup guide: mcp/README.md
→ Changelog: CHANGELOG.md
Install
See tokensavermcp.com/install for one-click install buttons, per-client config snippets, upgrade/uninstall instructions, and troubleshooting.
What the tools do
Single-file tools
| Tool | What it does | Reduction |
|---|---|---|
OutlineCSharpFile | Signatures of every type and member — no bodies. Best for "what's in this file?" | 70–95% |
MinifyFile | Lossless minify of an entire file — strips comments and whitespace, logic unchanged. Auto-dispatches by extension (C#, Razor, JS/TS, Python, HTML, CSS, JSON, YAML, XML, C, C++, X++, VB.NET). | 20–50% |
* Reductions are measured against reading the whole file — the real alternative when you'd otherwise load it. The end-to-end saving on a task is smaller, because a capable model already reads somewhat selectively; it is largest on smaller/cheaper models and large files (see Token savings in practice below).
Cross-file traversal tools
These scan an entire project directory in one call — no need to know which file to look in first.
| Tool | What it does |
|---|---|
TraceDiRegistrations | Finds every Dependency-Injection registration referencing a type (interface or concrete) and returns a compact table of file:line, method, ServiceType -> ImplType, and key. Answers "where is IFoo wired, and to what?" |
Both accept a directory path or .csproj file — obj/ and bin/ are excluded automatically.
Token savings in practice
Measured against this project's own FocusedEmitter.cs (9,261 tokens raw):
| Question type | Tool | Tokens sent | Reduction |
|---|---|---|---|
| "What's in this file?" | OutlineCSharpFile | 1,039 | 89% |
| "Read one method body" | OutlineCSharpFile + narrow Read of the // L.. range | ~300 | ~95% |
| "Audit the whole file" | MinifyFile | 5,525 | 40% |
Those are per-read figures versus loading the whole file. The end-to-end saving on a real task is smaller, because a capable model already reads somewhat selectively — and that's the honest part of the story:
| Model running the agent | Real-task token saving vs no tool |
|---|---|
| Top-tier (reads tightly already) | ~1% — negligible |
| Mid-tier (Sonnet-class) | ~5–7% |
| Smaller / cheaper (Haiku-class) | ~8% |
The leaner the model, the more it over-reads on its own — and the more a warm start saves. TokenSaver is most worth it for agents running on small/cheap models, large files, or any workflow that would otherwise read whole files. It won't make a top model meaningfully cheaper, and it won't make a model write better code — it curbs wasteful reading, which is where cheap-model token budgets actually leak.
Collective impact
Every invocation is counted at tokensavermcp.com — a live dashboard showing total tokens saved by the community. Fewer tokens processed means less GPU compute and a smaller carbon footprint for AI-assisted development.
Language support
| Tier | Languages |
|---|---|
| Primary (Roslyn, full support) | C# .cs, Razor .razor, VB.NET .vb, .NET project files .csproj .props .config .xml |
| Basic (comment-strip + whitespace collapse) | JavaScript, TypeScript, Python, HTML, CSS/SCSS/LESS, JSON/JSONC, YAML, C, C++, X++ |
OutlineCSharpFile and TraceDiRegistrations are C# only; MinifyFile works across every supported language.