Flagged: spawns subprocesses. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by andreisirbu91-lab · MCP Server · ★ 104
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is MCPSpend safe to install? View the security audit →
MCPSpend Know what your AI agents really cost. Real-time cost tracking for every MCP tool call across Cursor, Claude Desktop, Windsurf, and VS Code. mcpspend.com · Smithery · npm · Open VSX · Glama One-command install Auto-detects Claude Desktop, Cursor, Windsurf, VS Code (user + workspace), and Claude Code (user + pro
| Stars | 104 |
| Forks | 2 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 66.1993725197756/100 |
| Open Issues | 2 |
| Last Updated | 2026-08-31 |
| Created | 2026-05-22 |
| Platforms | claude-code, mcp, node |
| Est. Tokens | ~15k |
These tools work well together with MCPSpend for enhanced workflows:
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MCPSpend is Real-time cost observability for Model Context Protocol (MCP) tool calls. Wraps any MCP server, attributes spend per tool/project/customer. Free tier 25K calls/mo. EU-hosted. It is categorized as a MCP Server with 104 GitHub stars.
MCPSpend is primarily written in TypeScript. It covers topics such as ai-agents, ai-observability, claude-desktop.
You can find installation instructions and usage details in the MCPSpend GitHub repository at github.com/andreisirbu91-lab/MCPSpend. The project has 104 stars and 2 forks, indicating an active community.
MCPSpend is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to MCPSpend on Agent Skills Hub include mcp-mongo-server, mcp-dock, notion-mcp-server. 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: