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Mantic.sh
A structural code search engine for Al agents.
Install
$
npx mantic.sh@latest "your search query"Claude Code
claude mcp add mantic-sh -- npx mantic.sh@latest "your search query"Cursor / Claude Desktop (mcp.json)
{
"mcpServers": {
"mantic-sh": {
"command": "npx",
"args": [
"mantic.sh@latest",
"\"your",
"search",
"query\""
]
}
}
}Install command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →Mantic.sh
Summary
Mantic is a context-aware code search engine that prioritizes relevance over raw speed. After testing across 5 repositories (cal.com, next.js, tensorflow, supabase, chromium), it demonstrates superior result quality compared to grep/ripgrep, despite some trade-offs in speed for very large codebases.
Overall Assessment: 4/5 - Excellent for AI agents, good for developers, needs speed optimization for 100K+ file repos.
What's New in v1.0.25
Enterprise-Grade Context Infrastructure
- Semantic Reranking (Hybrid Intelligence): Combines heuristic speed with neural understanding. Uses local embeddings (
transformers.js) to find "conceptually relevant" code even without exact keyword matches.- Usage:
mantic "verify user" --semantic
- Usage:
- Code Intelligence: Deep understanding of your codebase structure using Tree-sitter.
- Go to Definition:
mantic goto UserServicereturns the exact line number across your entire monorepo. - Find References:
mantic references handleLoginfinds every usage, respecting.gitignore.
- Go to Definition:
- Learned Context (Team Memories): Mantic now remembers which files solved previous queries. These patterns are saved locally (
.mantic/search-patterns.json) and can be committed to git to share knowledge across your team. - Python Support: Now includes first-class support for Python imports in the dependency graph.
- Security & Stability:
- Regex DoS protection for user inputs.
- Command injection mitigations for VS Code extension.
- Safe fallback for non-git directories (scans allow-listed extensions).
Performance Update: v1.0.25 is ~2x faster than previous versions, scanning Chromium (481K files) in <2 seconds.
Tested on 481K files (Chromium) with 100% multi-repo accuracy.
See the CHANGELOG for detailed release notes.
Table of Contents
- About the Project
- Proprietary vs Mantic
- Performance Benchmarks
- Accuracy & Relevance
- Feature Comparison
- Use Case Recommendations
- Installation
- Usage
- Agent Rules
- How It Works
- License
About the Project
Mantic is an infrastructure layer designed to remove unnecessary context retrieval overhead for AI agents. It infers intent from file structure and metadata rather than brute-force reading content, enabling retrieval speeds faster than human reaction time.
Key Benefits
- Speed: Retrieval is consistently under 500ms for most repos, under 4s for massive monorepos (Chromium).
- Efficiency: Reduces token usage by up to 63% by filtering irrelevant files before reading.
- Privacy: Runs entirely locally with zero data egress.
Proprietary vs Mantic (Cost Analysis)
For a team of 100 developers performing 100 searches per day (approx. 3M searches/year):
| Tool | Annual Cost (Est.) | Per-Search Cost | Privacy |
|---|---|---|---|
| Mantic | $0 | $0 | Local-First |
| Vector Embeddings (DIY) | $1,680 - $10,950* | $0.0005 - $0.003 | Cloud |
| SaaS Alternatives | $46,800+ | $0.015+ | Cloud |
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