sigmap MCP Server
manojmallick/sigmap
[](https://agentrank-ai.com/tool/manojmallick--sigmap/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) ~97% token reduction for AI coding sessions — zero deps, 38 languages, MCP server
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
manojmallick/sigmap is a JavaScript MCP server licensed under MIT. ~97% token reduction for AI coding sessions — zero deps, 38 languages, MCP server Topics: claude, cursor, llm, mcp, token-reduction, ai, code-context, github-copilot, zero-dependencies, cli, code-intelligence, developer-tools, openai, retrieval, ai-code-review, ai-grounding, code-signatures, deterministic, hallucination-detection, verifiable-ai.
Ranked #209 out of 24846 indexed tools.
In the top 1% of all indexed tools.
Has 11 contributors.
Ecosystem
Score Breakdown
646 stars → growing community
Last commit 29d ago → recently updated
226/248 issues closed → responsive maintainer
11 contributors → active community
No dependents → no downstream usage
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
Matched Queries
From the README
<div align="center"> # ⚡ SigMap **SigMap is the deterministic, verifiable grounding layer for AI code work.** </div> --- ## Try it now **No install required.** Run instantly on any machine: ```bash npx sigmap npx sigmap ask "Where is auth handled?" ``` Zero config. Zero dependencies. Under 10 seconds. --- ## What is SigMap? SigMap builds a **deterministic, auditable signature-and-evidence map** of your codebase — no LLM calls, no embeddings, byte-stable output — so AI agents, CI, and reviewers can *trust and verify* which files and symbols are real before acting. Same repo in, same map out, every time. That map is exactly what agentic grep is worst at: reproducible, auditable context an agent can consume without a copy-paste, and a grounding check that proves an AI answer is anchored to real signatures and line numbers. Token reduction comes for free — but trust is the point. **Model-agnostic.** Works with: - **Cloud LLMs:** Claude, GPT-4, Copilot, Gemini - **Open-source aRead full README on GitHub →
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