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 IBM · MCP Server · ★ 4.5k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is mcp-context-forge safe to install? View the security audit →
ContextForge An open source registry and proxy that federates MCP, A2A, and REST/gRPC APIs with centralized governance, discovery, and observability. Optimizes Agent & Tool calling, and supports plugins. [![Deploy to
| Stars | 4,515 |
| Forks | 886 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 72.0333751542074/100 |
| Open Issues | 971 |
| Last Updated | 2026-09-22 |
| Created | 2025-05-08 |
| Platforms | docker, k8s, mcp, python |
| Est. Tokens | ~23k |
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mcp-context-forge is An AI Gateway, registry, and proxy that sits in front of any MCP, A2A, or REST/gRPC APIs, exposing a unified endpoint with centralized discovery, guardrails and management. Optimizes Agent & Tool call. It is categorized as a MCP Server with 4.5k GitHub stars.
mcp-context-forge is primarily written in Python. It covers topics such as agents, ai, api-gateway.
You can find installation instructions and usage details in the mcp-context-forge GitHub repository at github.com/IBM/mcp-context-forge. The project has 4.5k stars and 886 forks, indicating an active community.
mcp-context-forge is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to mcp-context-forge on Agent Skills Hub include mcp-agent, bytebot, valuecell. 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: