cortex-works/cortex-works-minimal
A hyper-optimized MCP server that supercharges AI coding agents. Outperforms built-in IDE tools with AST-based precision editing and native OS control, drastically reducing LLM token consumption.
Overview
cortex-works/cortex-works-minimal is a Rust MCP server licensed under MIT. A hyper-optimized MCP server that supercharges AI coding agents. Outperforms built-in IDE tools with AST-based precision editing and native OS control, drastically reducing LLM token consumption. Topics: ai-agents, ai-coding, ast-parsing, cursor-ide, ide-tools, llm-tools, mcp, mcp-server, rust, token-optimization, vscode-copilot.
Ranked #5 out of 104 indexed tools.
In the top 5% of all indexed tools.
Actively maintained with commits in the last week.
Ecosystem
Score Breakdown
6 stars → early stage
Last commit today → actively maintained
No issues filed → no history to score
1 contributor → solo project
No dependents → no downstream usage
Weights: Freshness 25% · Issue Health 25% · Dependents 25% · Stars 15% · Contributors 10% · How we score →
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From the README
# cortex-works (minimal) > **One binary. 14 tools. Built to make AI agents faster, cheaper, and more precise.** `cortex-works-minimal` is a lean MCP server for AI-powered IDEs. It replaces slow, token-hungry IDE tooling with a disciplined surface of 14 surgical tools — covering repo mapping, symbol analysis, structural editing, semantic search, filesystem work, and bounded shell execution. ✅ **Cross-platform tested:** macOS, Windows, and Ubuntu (other Linux distros may work too). ```bash cargo build --release -p cortex-mcp ./target/release/cortex-mcp # wire to your IDE via MCP stdio ``` --- ## Why Agents Perform Better Here Standard IDE tools expose the filesystem as a flat text surface. Agents waste tokens reading full files to find the three lines they need, burning context on boilerplate and build artifacts that should never appear in a prompt. `cortex-works` is designed around the opposite principle: **return exactly what the agent needs, nothing more.** ### Token EfficiRead full README on GitHub →
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