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title: MCP server setup
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description: Set up the SigMap MCP server for Claude Code, Cursor, and Windsurf. On-demand codebase access with 20 tools over stdio. Zero npm install.
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description: Set up the SigMap MCP server for Claude Code, Cursor, and Windsurf. On-demand codebase access with 21 tools over stdio. Zero npm install.
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Give Claude Code, Cursor, and Windsurf on-demand access to your codebase signatures. Zero npm install.
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The SigMap MCP server exposes 20 tools over the stdio Model Context Protocol. Your AI agent calls only what it needs — keeping token costs low.
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The SigMap MCP server exposes 21 tools over the stdio Model Context Protocol. Your AI agent calls only what it needs — keeping token costs low.
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> **Setup time: under 2 minutes.** Use `sigmap --setup` for automatic configuration.
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## 11 available tools
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::: tip New in v6.3.0 — native tool registration
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Claude Code and Codex now receive the full tool list at MCP startup without a discovery round-trip. The server declares all 20 tools in the `initialize` response, so your AI sees them immediately. No config change needed — upgrade via `npm install -g sigmap@latest`.
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Claude Code and Codex now receive the full tool list at MCP startup without a discovery round-trip. The server declares all 21 tools in the `initialize` response, so your AI sees them immediately. No config change needed — upgrade via `npm install -g sigmap@latest`.
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:::
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All tools are available on-demand — your AI agent calls only what it needs.
sigmap note "<text>" Append a note to the cross-session decision log
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sigmap note List recent notes (also: note --list <N>)
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sigmap status Show repo state — branch, dirty files, index freshness, notes
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---
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## MCP server — 20 tools
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## MCP server — 21 tools
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Start with `sigmap --mcp` (stdio JSON-RPC). Configure once:
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Input: { content: string }
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```
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### get_budget
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Session spend ledger — estimated tokens SigMap has emitted this session (chars/4 estimates from the local gain log), optional budget remaining, and context freshness. Scope honesty: counts only SigMap output, NOT the whole chat's spend. Check this mid-session and degrade gracefully when near budget: prefer terse encoding, squeeze large outputs, summarize-then-drop context. Local-only; no LLM, no network.
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```
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Input: { session?: string, budgetTokens?: number }
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