Compiler-as-a-service for AI agents.
Lifeblood gives AI agents direct access to what compilers know. Type resolution, call graphs, diagnostics, reference finding, code execution. All over a standard MCP connection. No IDE required. Load a project, ask the compiler, get verified answers. Compilers already know everything about your code, just pipe that truth to AI agents instead of letting them grep and guess.
Roslyn (C#) ──┐ ┌── Execute code against project types
TypeScript ──┤ ┌────────────────────────┐ ├── Diagnose / compile-check
JSON graph ──┼→ │ Semantic Graph │ →┤── Find references / rename / format
──┤ │ (symbols / edges / │ ├── Blast radius / file impact
community ──┘ │ evidence / trust) │ └── Context packs / architecture rules
adapters └────────────────────────┘
Born from shipping a 400k LOC Unity project with AI assistance and realizing that AI writes code but does not verify what it wrote.
dotnet tool install --global Lifeblood
dotnet tool install --global Lifeblood.Server.McpRequires .NET 8 SDK.
Add to your project's .mcp.json:
{
"mcpServers": {
"lifeblood": {
"command": "lifeblood-mcp",
"args": []
}
}
}See MCP Setup Guide for Claude Desktop, VS Code, Cursor, and raw stdio configs.
lifeblood_analyze projectPath="/path/to/your/project" → load semantic graph
lifeblood_blast_radius symbolId="type:MyApp.AuthService" → what breaks if I change this?
lifeblood_file_impact filePath="src/AuthService.cs" → what files are affected?
lifeblood_find_references symbolId="type:MyApp.IRepo" → every caller, every consumer
lifeblood_execute code="typeof(MyApp.Foo).GetMethods()" → run C# against your types
After the first analysis, use incremental: true for fast re-analysis (seconds instead of minutes).
lifeblood analyze --project /path/to/your/project
lifeblood analyze --project /path/to/your/project --rules hexagonal
lifeblood context --project /path/to/your/project
lifeblood export --project /path/to/your/project > graph.jsongit clone https://github.com/user-hash/Lifeblood.git
cd Lifeblood
dotnet build
dotnet testConnect an MCP client. Load a project. The AI agent gets 17 tools: 7 read, 10 write.
| Tools | |
|---|---|
| Read | Analyze, Context, Lookup, Dependencies, Dependants, Blast Radius, File Impact |
| Write | Execute, Diagnose, Compile-check, Find References, Find Definition, Find Implementations, Symbol at Position, Documentation, Rename, Format |
Hexagonal. Pure domain core with zero dependencies. Language adapters on the left, AI connectors on the right.
LEFT SIDE CORE RIGHT SIDE
(Language Adapters) (The Pipe) (AI Connectors)
Roslyn (C#) ──┐ ┌── MCP Server (17 tools)
TypeScript ──┼→ Domain → Application →┤── Context Pack Generator
JSON graph ──┘ ↑ ├── Instruction File Generator
Analysis (optional) └── CLI / CI
14 port interfaces, all wired. Boundaries enforced by architecture invariant tests and 11 frozen ADRs.
Full architecture | Interactive diagram
| Adapter | How it works | Confidence |
|---|---|---|
| C# / Roslyn | Compiler-grade semantic analysis. Cross-module resolution. Bidirectional: analysis + code execution. | Proven |
| TypeScript | Standalone Node.js. ts.createProgram + TypeChecker. |
High |
| Python | Standalone ast module. Zero dependencies. |
Structural |
| Any language | Output JSON conforming to schemas/graph.schema.json. Adapter guide. |
Varies |
Lifeblood runs as a sidecar alongside Unity MCP. All 17 tools available in the Unity Editor via [McpForUnityTool] discovery. Runs as a separate process, so no assembly conflicts, no domain reload interference.
Self-analysis: 1,148 symbols, 3,196 edges, 11 modules, 150 types, 0 violations.
Production-verified on a 75-module Unity project: 43,800 symbols, 70,600+ edges, 2,404 types.
Six sessions found 45 real bugs invisible to unit tests.
- Community adapters: contribution guides for Go and Rust. Contract and checklist ready, no implementation code yet.
- REST / LSP bridge: expose the graph to IDE extensions and web services.
| Page | Description |
|---|---|
| Tools | All 17 tools with descriptions, symbol ID format, incremental usage |
| MCP Setup | Copy-paste configs for Claude Code, Cursor, VS Code, Claude Desktop, Unity |
| Unity Integration | Sidecar architecture, setup guide, incremental, memory |
| Architecture | Hexagonal structure, dependency flow, port interfaces, invariants |
| Architecture Decisions | 11 frozen ADRs |
| Status | Component table, test counts, self-analysis, production stats |
| Adapters | How to build a language adapter (13-item checklist) |
| Dogfood Findings | 45 bugs found by self-analysis |
- LivingDocFramework: The methodology that shaped the architecture
- Roslyn: The C# compiler platform
- DAWG | itch.io: The 400k LOC project where we proved these ideas
AGPL v3