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sigmap MCP Server

manojmallick/sigmap

Score: 92.2 → 0% Rank #209 MCP Server
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~97% token reduction for AI coding sessions — zero deps, 38 languages, MCP server

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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

JavaScript MIT
claudecursorllmmcptoken-reductionaicode-contextgithub-copilotzero-dependenciesclicode-intelligencedeveloper-toolsopenairetrievalai-code-reviewai-groundingcode-signaturesdeterministichallucination-detectionverifiable-ai

Score Breakdown

StarsFreshnessIssue HealthContributorsDependents
Stars 15% 646

646 stars → growing community

Freshness 25% 29d ago

Last commit 29d ago → recently updated

Issue Health 25% 91%

226/248 issues closed → responsive maintainer

Contributors 10% 11

11 contributors → active community

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A
PyPI Downloads N/A
Forks 51
Description Good
License MIT

Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →

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AgentRank score for manojmallick/sigmap
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Matched Queries

"mcp server""mcp-server"topic:mcp

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 a
Read full README on GitHub →

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