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MCP server · Official registry · stdio · No API key

Your AI agents, with a real Git engine on tap.

GitWand's MCP server exposes its deterministic conflict engine to AI agents. GitWand resolves the trivial 95% instantly and deterministically; your agent takes over the complex cases with full context — ours/theirs/base content, classification trace and confidence scores. AI is always opt-in, always auditable.

How an agent uses GitWand

Three steps: the engine handles the deterministic work, the agent handles the judgment calls.

1

Preview

The agent calls gitwand_preview_merge to assess the number of conflicts, their complexity, and the percentage GitWand can resolve on its own.

2

Auto-resolve

GitWand instantly resolves trivial patterns (whitespace, one-side-change, same-change…) and returns ambiguous hunks with their classification trace.

AI

AI resolution

For each complex conflict, the agent has full context: ours/theirs/base content, classification trace and confidence scores — then proposes a resolution you can accept or reject.

One command to wire it up

With Claude Code: claude mcp add gitwand -- npx -y @gitwand/mcp. For Claude Desktop, Cursor or Windsurf, drop the config block into your client. The server is also on the official MCP Registry, so registry-aware clients discover it automatically.

Claude CodeClaude DesktopCursorWindsurfopencodeContinue
claude_desktop_config.json
{
  "mcpServers": {
    "gitwand": {
      "command": "npx",
      "args": [
        "@gitwand/mcp",
        "--cwd",
        "/path/to/repo"
      ]
    }
  }
}

LLM fallback, when you get stuck

For the hunks patterns can't resolve, opt in to LLM resolution via Claude, OpenAI-compatible endpoints, Ollama, or MCP — your model, your key. Every suggestion runs through the same parse-tree validation pipeline as the deterministic patterns, with a decision trace and a reject button. No built-in model, no data leaving your machine unless you choose it.

Opt-in only

Deterministic patterns run first and free. The LLM is called only for what's left.

Validated

LLM output is parsed and validated like any other resolution — not trusted blindly.

Your provider

Claude · OpenAI-compatible · Ollama · MCP. Your key, your endpoint, your data.

Auditable

Full decision trace and a one-click reject on every proposed resolution.

Released under the MIT License.