No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by GlitterKill · MCP Server · ★ 483
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is sdl-mcp safe to install? View the security audit →
SYMBOL DELTA LEDGER Cards-first code context for AI coding agents Stop feeding entire files into the context window.Start giving agents exactly the code intelligence they need. What's the problem? Every time an AI coding agent reads a file to answer a question, it consumes thousands of tokens. Most of those tokens are irrelevant to the task. The agent doesn't need 500 lines of a file to know that takes a and returns a — but it reads them anyway, because that's all it has. Multiply that across a debugging session touching 20 files and you've burned 40,000+ tokens on context gathering alone. SDL-MCP fixes this. It indexes your codebase into a searchable symbol graph and serves precisely the right amount of context through a controlled escalation path. An agent that uses SDL-MCP understands your code better while consuming a fraction of the
| Stars | 483 |
| Forks | 31 |
| Language | TypeScript |
| Category | MCP Server |
| Quality Score | 68.7668023947218/100 |
| Last Updated | 2026-09-16 |
| Created | 2026-02-08 |
| Platforms | mcp, node |
| Est. Tokens | ~26k |
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sdl-mcp is Symbol Delta Ledger (SDL-MCP) is a policy-centered context budget layer for coding agents: Symbol-graph intelligence combined with precision tools. It turns sprawling codebases into compact, high-sig. It is categorized as a MCP Server with 483 GitHub stars.
sdl-mcp is primarily written in TypeScript. It covers topics such as agent-context, agent-tools, agentic-coding.
You can find installation instructions and usage details in the sdl-mcp GitHub repository at github.com/GlitterKill/sdl-mcp. The project has 483 stars and 31 forks, indicating an active community.
The top alternatives to sdl-mcp on Agent Skills Hub include codex-cli-best-practice, roam-code, claude-code-hooks. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: