Wisegit
@Sandip124
About Wisegit
MCP server that extracts decision intent from git history and protects intentional code from AI modification.
Basic information
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"wisegit": {
"command": "npx",
"args": [
"-y",
"@sandip124/wisegit",
"serve"
]
}
}
}Tools
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Overview
What is Wisegit?
Wisegit is a local MCP server that extracts decision intent from git history, so AI agents respect intentional code rather than treating all code equally. It indexes commits, computes per-function “freeze scores,” and serves decision manifests—marking functions as frozen, stable, or open—before any file edit.
How to use Wisegit?
Run npx @sandip124/wisegit setup in any repository—zero configuration. After indexing, AI agents call MCP tools such as get_file_decisions to retrieve decision manifests, and create_override to override frozen functions with user approval in Claude Code.
Key features of Wisegit
- Zero config setup with a single command
- SQLite database (no Docker or external services)
- Team support via
.wisegit/directory tracked by git - AI-era commit origin detection (human, AI reviewed, AI unreviewed)
- Theory holder tracking per function (healthy / fragile / critical)
- HTML codebase health report (
wisegit report) - Grounded in 12 published software engineering papers
Use cases of Wisegit
- Prevent AI agents from removing manually‑tested workarounds (e.g.,
sleep(350)for race conditions) - Identify functions lacking active theory holders to mitigate institutional knowledge loss
- Safely modify code by respecting frozen/stable/open zones with auditable overrides
- Search past decisions across the entire git history for context during code reviews
FAQ from Wisegit
What are the runtime requirements?
Only a local SQLite database—no Docker, PostgreSQL, or any external services needed.
How does Wisegit classify commits?
It parses diffs at the AST level using Tree‑sitter for C#, TypeScript, JavaScript, Python, Go, and Rust, then labels commits as STRUCTURED, DESCRIPTIVE, or NOISE.
What is a freeze score?
A 0–1 score per function derived from seven signal categories including git history, issue enrichment, code structure, test signals, and structural importance.
How does team collaboration work?
The .wisegit/ directory is tracked by git; JSONL files within it merge cleanly, enabling shared override audit trails and decision histories.
What MCP tools does Wisegit expose?
Eight tools: get_file_decisions, get_freeze_score, get_function_history, get_theory_gaps, get_branch_context, search_decisions, create_override, and extract_intent.
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